From a8aea997f875803459414992105042be4e00fada Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 1 Nov 2023 19:56:11 +0800 Subject: [PATCH 001/200] Update qcnn.py 1. Now accepts arbitrary 2-qubit circuit blocks as input 2. Switched from scipy.optimize.minimize to qibo.optimizers.optimize --- src/qibo/models/qcnn.py | 55 +++++++++++++++++++++++++++-------------- 1 file changed, 36 insertions(+), 19 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 5d569facac..6604c32f4a 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -1,6 +1,7 @@ import numpy as np -from qibo import Circuit, gates +from qibo import gates, set_backend +from qibo.models import Circuit class QuantumCNN: @@ -16,6 +17,7 @@ class QuantumCNN: nclasses (int): number of classes to be classified. Default setting of 2 (phases). params: initial list of variational parameters. If not provided, all parameters will be initialized to zero. + twoqubitansatz (Qibo.models.Circuit object): A two qubit ansatz that can be input by the user to form the two qubit ansatz. Example: .. testcode:: import qibo @@ -42,12 +44,17 @@ class QuantumCNN: """ - def __init__(self, nqubits, nlayers, nclasses=2, params=None): + def __init__(self, nqubits, nlayers, nclasses=2, params=None, twoqubitansatz = None, Dividend = 2): self.nclasses = nclasses self.nqubits = nqubits self.nlayers = nlayers - - self.nparams_conv = 15 + self.twoqubitansatz = twoqubitansatz + + if self.twoqubitansatz == None: + self.nparams_conv = 15 + else: + self.nparams_conv = len(self.twoqubitansatz.get_parameters()) + self.nparams_pool = 6 self.nparams_layer = self.nparams_conv + self.nparams_pool self.measured_qubits = int(np.ceil(np.log2(self.nclasses))) @@ -160,17 +167,23 @@ def two_qubit_unitary(self, bits, symbols): Returns: Circuit containing the unitaries added to the specified qubits. """ - - c = Circuit(self.nqubits) - c += self.one_qubit_unitary(bits[0], symbols[0:3]) - c += self.one_qubit_unitary(bits[1], symbols[3:6]) - c.add(gates.RZZ(bits[0], bits[1], symbols[6])) - c.add(gates.RYY(bits[0], bits[1], symbols[7])) - c.add(gates.RXX(bits[0], bits[1], symbols[8])) - - c += self.one_qubit_unitary(bits[0], symbols[9:12]) - c += self.one_qubit_unitary(bits[1], symbols[12:]) - + + if self.twoqubitansatz == None: + c = Circuit(self.nqubits) + c += self.one_qubit_unitary(bits[0], symbols[0:3]) + c += self.one_qubit_unitary(bits[1], symbols[3:6]) + c.add(gates.RZZ(bits[0], bits[1], symbols[6])) + c.add(gates.RYY(bits[0], bits[1], symbols[7])) + c.add(gates.RXX(bits[0], bits[1], symbols[8])) + + c += self.one_qubit_unitary(bits[0], symbols[9:12]) + c += self.one_qubit_unitary(bits[1], symbols[12:]) + + else: + c = Circuit(self.nqubits) + c.add(self.twoqubitansatz.on_qubits(bits[0], bits[1])) + c.set_parameters(symbols[0:self.nparams_conv]) + return c def two_qubit_pool(self, source_qubit, sink_qubit, symbols): @@ -219,6 +232,7 @@ def set_circuit_params(self, angles, has_bias=False): pool_params = params[ param_start + self.nparams_conv : param_start + self.nparams_layer ] + #print(pool_params) pool_params += [-pool_params[2], -pool_params[1], -pool_params[0]] expanded_params += conv_params * int(nleft if nleft > 2 else 1) expanded_params += pool_params * int(nleft / 2) @@ -313,13 +327,16 @@ def minimize( Returns: numpy.float64 with value of the minimum found, numpy.ndarray with the optimal angles. """ - from scipy.optimize import minimize + from qibo.optimizers import optimize + + set_backend("numpy") - result = minimize( + if method == "sgd": + set_backend("tensorflow") + + loss, optimal_angles, result = optimize( self.Cost_function, init_theta, args=(data, labels, nshots), method=method ) - loss = result.fun - optimal_angles = result.x self._optimal_angles = optimal_angles From fa205a2d234c6e6dec7b459a36c75a9da6a04cc4 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 1 Nov 2023 21:10:15 +0800 Subject: [PATCH 002/200] Update test_models_qcnn.py Update test for qcnn upgrade: 1. Now accepts arbitrary 2-qubit circuit blocks as input 2. Switched from scipy.optimize.minimize to qibo.optimizers.optimize --- tests/test_models_qcnn.py | 42 +++++++++++++++++++++++++++++++++++++-- 1 file changed, 40 insertions(+), 2 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 871e73ed8d..096f639326 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,8 +3,9 @@ import numpy as np import pytest -from qibo import Circuit, gates -from qibo.models.qcnn import QuantumCNN +from qibo.models import Circuit +from qibo import gates +from QuantumCNNwAnsatz import QuantumCNN num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] @@ -303,3 +304,40 @@ def test_qcnn_training(): predictions.append(1) labels = np.array([[1], [-1], [1]]) test_qcnn.Accuracy(labels, predictions) + +def test_two_qubit_ansatz(): + c = Circuit(2) + c.add(gates.H(0)) + c.add(gates.RX(0,0)) + c.add(gates.CNOT(1,0)) + test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + +def test_two_qubit_ansatz_training(): + c = Circuit(2) + c.add(gates.H(0)) + c.add(gates.RX(0,0)) + c.add(gates.CNOT(1,0)) + test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + + data = np.zeros([2, 16]) + for i in range(2): + data_i = np.random.rand(16) + data[i] = data_i / np.linalg.norm(data_i) + labels = [[1], [-1]] + + totalNParams = test_qcnn.nparams_layer*2 + init_theta = [0 for i in range(totalNParams+1)] #totalNParams+1 to account for bias parameter. + + result = test_qcnn.minimize( + init_theta, data=data, labels=labels, nshots=10000, method="Powell" + ) + + # test Predictions function + predictions = [] + for n in range(len(data)): + predictions.append(test_qcnn.predict(data[n], nshots=10000)[0]) + + # test Accuracy function + predictions.append(1) + labels = np.array([[1], [-1], [1]]) + test_qcnn.Accuracy(labels, predictions) From eb12cadbda0c1c00269da7e38818074109870eb3 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 1 Nov 2023 21:28:05 +0800 Subject: [PATCH 003/200] Update test_models_qcnn.py correction --- tests/test_models_qcnn.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 096f639326..7bb1cd5127 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,9 +3,8 @@ import numpy as np import pytest -from qibo.models import Circuit +from qibo.models import Circuit, qcnn from qibo import gates -from QuantumCNNwAnsatz import QuantumCNN num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] From c369f5714b2e30726a5b3d473adc371395941fc7 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 1 Nov 2023 23:45:15 +0800 Subject: [PATCH 004/200] Update test_models_qcnn.py From 8cb02f7218ac68b3649c4b31eda92357cd1c5a45 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Tue, 7 Nov 2023 16:00:52 +0800 Subject: [PATCH 005/200] Update test_models_qcnn.py fix pytest --- tests/test_models_qcnn.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 7bb1cd5127..98cb1c442e 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,8 +3,9 @@ import numpy as np import pytest -from qibo.models import Circuit, qcnn from qibo import gates +from qibo.models import Circuit +from qibo.models.qcnn import QuantumCNN num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] From fecdcb857cc189c266b8b60a2186b23f506960b1 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Tue, 7 Nov 2023 18:09:55 +0800 Subject: [PATCH 006/200] Update qcnn.py fix #print --- src/qibo/models/qcnn.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 6604c32f4a..fadb0f2788 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -232,7 +232,6 @@ def set_circuit_params(self, angles, has_bias=False): pool_params = params[ param_start + self.nparams_conv : param_start + self.nparams_layer ] - #print(pool_params) pool_params += [-pool_params[2], -pool_params[1], -pool_params[0]] expanded_params += conv_params * int(nleft if nleft > 2 else 1) expanded_params += pool_params * int(nleft / 2) From 321c16729d27bc61d9de0e2f1837967ccad0e4ae Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 8 Nov 2023 05:10:52 +0800 Subject: [PATCH 007/200] Update test_models_qcnn.py fix pytest for 100% coverage of updated qcnn class --- tests/test_models_qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 98cb1c442e..3148e2c2e4 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -292,7 +292,7 @@ def test_qcnn_training(): test_qcnn = QuantumCNN(nqubits=4, nlayers=1, nclasses=2, params=init_theta) testcircuit = test_qcnn._circuit result = test_qcnn.minimize( - init_theta, data=data, labels=labels, nshots=10000, method="Powell" + init_theta, data=data, labels=labels, nshots=10000, method="sgd" ) # test Predictions function From 8d6fdaa0df623e770104d8bfe87524554bea048d Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Wed, 8 Nov 2023 18:52:00 +0800 Subject: [PATCH 008/200] Update test_models_qcnn.py install tensorflow --- tests/test_models_qcnn.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 3148e2c2e4..e4361d9558 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,4 +1,5 @@ import math +import subprocess, sys import numpy as np import pytest @@ -7,6 +8,8 @@ from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN +subprocess.call([sys.executable, '-m', 'pip', 'install', 'tensorflow']) + num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] From 3aac965664c0bdd96ee6c1d77c3cb875d97a69e0 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 05:57:27 +0800 Subject: [PATCH 009/200] Update qcnn.py remove backend settings in minimize --- src/qibo/models/qcnn.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index fadb0f2788..6a35c77813 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -322,16 +322,11 @@ def minimize( data: the training data to be used in the minimization. labels: the corresponding ground truth for the training data. nshots: int number of runs of the circuit during the sampling process (default=10000). - method: str 'classical optimizer for the minimization'. All methods from scipy.optimize.minmize are suported (default='Powell'). + method: str 'classical optimizer for the minimization'. All methods from qibo.optimizers.optimize are suported (default='Powell'). Returns: numpy.float64 with value of the minimum found, numpy.ndarray with the optimal angles. """ from qibo.optimizers import optimize - - set_backend("numpy") - - if method == "sgd": - set_backend("tensorflow") loss, optimal_angles, result = optimize( self.Cost_function, init_theta, args=(data, labels, nshots), method=method From 470622ad0bdd964c666ece64eb3c171fa364be90 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 05:59:51 +0800 Subject: [PATCH 010/200] Update test_models_qcnn.py remove explicit sgd check since use case follows as per qibo.optimizer.optimize --- tests/test_models_qcnn.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index e4361d9558..98cb1c442e 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,5 +1,4 @@ import math -import subprocess, sys import numpy as np import pytest @@ -8,8 +7,6 @@ from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN -subprocess.call([sys.executable, '-m', 'pip', 'install', 'tensorflow']) - num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] @@ -295,7 +292,7 @@ def test_qcnn_training(): test_qcnn = QuantumCNN(nqubits=4, nlayers=1, nclasses=2, params=init_theta) testcircuit = test_qcnn._circuit result = test_qcnn.minimize( - init_theta, data=data, labels=labels, nshots=10000, method="sgd" + init_theta, data=data, labels=labels, nshots=10000, method="Powell" ) # test Predictions function From d61ed1606e6eece6b5fa0d2a43a804b4880c7487 Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 14:11:12 +0800 Subject: [PATCH 011/200] Update qcnn.py make initial state copy in Predictions function if backend is qibojit --- src/qibo/models/qcnn.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 6a35c77813..6b8e4e1433 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -264,7 +264,11 @@ def Predictions(self, circuit, theta, init_state, nshots=10000): numpy.array() with predictions for each qubit, for the initial state. """ bias = np.array(theta[0 : self.measured_qubits]) - circuit_exec = circuit(init_state, nshots) + if qibo.get_backend()=='qibojit': + init_state_copy = init_state.copy() + else: + init_state_copy = init_state + circuit_exec = circuit(init_state_copy, nshots) result = circuit_exec.frequencies(binary=False) prediction = np.zeros(self.measured_qubits) From 5d0139f8b05be32bbb3ec8fd71dfdd9ff8ab67cf Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 14:14:52 +0800 Subject: [PATCH 012/200] Update test_models_qcnn.py test qibojit backend case to create copy of initial state --- tests/test_models_qcnn.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 98cb1c442e..61459b80e6 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,6 +3,7 @@ import numpy as np import pytest +import qibo from qibo import gates from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN @@ -313,6 +314,9 @@ def test_two_qubit_ansatz(): test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) def test_two_qubit_ansatz_training(): + # test qibojit case (copy initial state as quick-fix for in-place update) + qibo.set_backend("qibojit") + c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0,0)) From baa44b30913d067e07e52c47b4dd04cb0f33969f Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 14:16:15 +0800 Subject: [PATCH 013/200] Update qcnn.py add import qibo to check backend --- src/qibo/models/qcnn.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 6b8e4e1433..cc68ac6ddf 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -1,5 +1,6 @@ import numpy as np +import qibo from qibo import gates, set_backend from qibo.models import Circuit From fe22938f27761011c308da062ddf640b17021b5a Mon Sep 17 00:00:00 2001 From: jykhoo1987 <90653892+jykhoo1987@users.noreply.github.com> Date: Thu, 9 Nov 2023 16:39:45 +0800 Subject: [PATCH 014/200] Update qcnn.py add copy flag during initialization --- src/qibo/models/qcnn.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index cc68ac6ddf..692b25519d 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -45,11 +45,17 @@ class QuantumCNN: """ - def __init__(self, nqubits, nlayers, nclasses=2, params=None, twoqubitansatz = None, Dividend = 2): + def __init__(self, nqubits, nlayers, nclasses=2, params=None, twoqubitansatz = None, Dividend = 2, copy_init_state=None): self.nclasses = nclasses self.nqubits = nqubits self.nlayers = nlayers self.twoqubitansatz = twoqubitansatz + + if copy_init_state is None: + if qibo.get_backend()[:7]=='qibojit': + self.copy_init_state = True + else: + self.copy_init_state = False if self.twoqubitansatz == None: self.nparams_conv = 15 @@ -265,7 +271,7 @@ def Predictions(self, circuit, theta, init_state, nshots=10000): numpy.array() with predictions for each qubit, for the initial state. """ bias = np.array(theta[0 : self.measured_qubits]) - if qibo.get_backend()=='qibojit': + if self.copy_init_state is True: init_state_copy = init_state.copy() else: init_state_copy = init_state From ae83dbc66d8b4fdd15da1738a793617c2cfe1bb1 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 9 Nov 2023 10:55:20 +0000 Subject: [PATCH 015/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/models/qcnn.py | 31 ++++++++++++++++++++----------- tests/test_models_qcnn.py | 22 +++++++++++++--------- 2 files changed, 33 insertions(+), 20 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 692b25519d..8abae35dbd 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -45,23 +45,32 @@ class QuantumCNN: """ - def __init__(self, nqubits, nlayers, nclasses=2, params=None, twoqubitansatz = None, Dividend = 2, copy_init_state=None): + def __init__( + self, + nqubits, + nlayers, + nclasses=2, + params=None, + twoqubitansatz=None, + Dividend=2, + copy_init_state=None, + ): self.nclasses = nclasses self.nqubits = nqubits self.nlayers = nlayers self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if qibo.get_backend()[:7]=='qibojit': + if qibo.get_backend()[:7] == "qibojit": self.copy_init_state = True else: self.copy_init_state = False - + if self.twoqubitansatz == None: self.nparams_conv = 15 else: self.nparams_conv = len(self.twoqubitansatz.get_parameters()) - + self.nparams_pool = 6 self.nparams_layer = self.nparams_conv + self.nparams_pool self.measured_qubits = int(np.ceil(np.log2(self.nclasses))) @@ -174,23 +183,23 @@ def two_qubit_unitary(self, bits, symbols): Returns: Circuit containing the unitaries added to the specified qubits. """ - - if self.twoqubitansatz == None: + + if self.twoqubitansatz == None: c = Circuit(self.nqubits) c += self.one_qubit_unitary(bits[0], symbols[0:3]) c += self.one_qubit_unitary(bits[1], symbols[3:6]) c.add(gates.RZZ(bits[0], bits[1], symbols[6])) c.add(gates.RYY(bits[0], bits[1], symbols[7])) c.add(gates.RXX(bits[0], bits[1], symbols[8])) - + c += self.one_qubit_unitary(bits[0], symbols[9:12]) c += self.one_qubit_unitary(bits[1], symbols[12:]) - + else: c = Circuit(self.nqubits) c.add(self.twoqubitansatz.on_qubits(bits[0], bits[1])) - c.set_parameters(symbols[0:self.nparams_conv]) - + c.set_parameters(symbols[0 : self.nparams_conv]) + return c def two_qubit_pool(self, source_qubit, sink_qubit, symbols): @@ -338,7 +347,7 @@ def minimize( numpy.float64 with value of the minimum found, numpy.ndarray with the optimal angles. """ from qibo.optimizers import optimize - + loss, optimal_angles, result = optimize( self.Cost_function, init_theta, args=(data, labels, nshots), method=method ) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 61459b80e6..7e9168b007 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -306,22 +306,24 @@ def test_qcnn_training(): labels = np.array([[1], [-1], [1]]) test_qcnn.Accuracy(labels, predictions) + def test_two_qubit_ansatz(): c = Circuit(2) c.add(gates.H(0)) - c.add(gates.RX(0,0)) - c.add(gates.CNOT(1,0)) - test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + c.add(gates.RX(0, 0)) + c.add(gates.CNOT(1, 0)) + test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) + def test_two_qubit_ansatz_training(): # test qibojit case (copy initial state as quick-fix for in-place update) qibo.set_backend("qibojit") - + c = Circuit(2) c.add(gates.H(0)) - c.add(gates.RX(0,0)) - c.add(gates.CNOT(1,0)) - test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + c.add(gates.RX(0, 0)) + c.add(gates.CNOT(1, 0)) + test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) data = np.zeros([2, 16]) for i in range(2): @@ -329,8 +331,10 @@ def test_two_qubit_ansatz_training(): data[i] = data_i / np.linalg.norm(data_i) labels = [[1], [-1]] - totalNParams = test_qcnn.nparams_layer*2 - init_theta = [0 for i in range(totalNParams+1)] #totalNParams+1 to account for bias parameter. + totalNParams = test_qcnn.nparams_layer * 2 + init_theta = [ + 0 for i in range(totalNParams + 1) + ] # totalNParams+1 to account for bias parameter. result = test_qcnn.minimize( init_theta, data=data, labels=labels, nshots=10000, method="Powell" From fb49d45dc7410ebff7a4e07eeb9032dcbb625b0e Mon Sep 17 00:00:00 2001 From: rahul Date: Thu, 23 Nov 2023 10:47:07 +0100 Subject: [PATCH 016/200] remove dividend from src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 8abae35dbd..bc26ed7e0f 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -52,7 +52,6 @@ def __init__( nclasses=2, params=None, twoqubitansatz=None, - Dividend=2, copy_init_state=None, ): self.nclasses = nclasses From 6af5b684f1a691dd5675fa26c65884321d0958f0 Mon Sep 17 00:00:00 2001 From: rahul Date: Thu, 23 Nov 2023 10:48:13 +0100 Subject: [PATCH 017/200] Update src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index bc26ed7e0f..ba79f6d47d 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -60,7 +60,7 @@ def __init__( self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if qibo.get_backend()[:7] == "qibojit": + if "qibojit" in qibo.get_backend(): self.copy_init_state = True else: self.copy_init_state = False From cff29f8809b7276f4cb3b0e390271b46d24fd9ae Mon Sep 17 00:00:00 2001 From: rahul Date: Mon, 11 Dec 2023 02:46:14 +0800 Subject: [PATCH 018/200] Update qcnn.py update in response to comments. --- src/qibo/models/qcnn.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index ba79f6d47d..49b1123304 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -1,7 +1,6 @@ import numpy as np -import qibo -from qibo import gates, set_backend +from qibo import gates, get_backend from qibo.models import Circuit @@ -18,15 +17,16 @@ class QuantumCNN: nclasses (int): number of classes to be classified. Default setting of 2 (phases). params: initial list of variational parameters. If not provided, all parameters will be initialized to zero. - twoqubitansatz (Qibo.models.Circuit object): A two qubit ansatz that can be input by the user to form the two qubit ansatz. + twoqubitansatz (Qibo.models.Circuit object): A two qubit ansatz that can be input by the user to form the two qubit ansatz used in the convolutional circuit. Example: .. testcode:: - import qibo - from qibo.models.qcnn import QuantumCNN + import math - import qibo import numpy as np import random + import qibo + from qibo.models.qcnn import QuantumCNN + qibo.set_backend("numpy") data = np.random.rand(16) @@ -60,7 +60,7 @@ def __init__( self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if "qibojit" in qibo.get_backend(): + if "qibojit" in get_backend(): self.copy_init_state = True else: self.copy_init_state = False From ce5441e89dd14ae0e88e451422a17f559635942c Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sun, 10 Dec 2023 18:46:35 +0000 Subject: [PATCH 019/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 49b1123304..92a940102c 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -20,7 +20,7 @@ class QuantumCNN: twoqubitansatz (Qibo.models.Circuit object): A two qubit ansatz that can be input by the user to form the two qubit ansatz used in the convolutional circuit. Example: .. testcode:: - + import math import numpy as np import random From bbae84691b675f2d1e3dc27afb8ee9a46a4c6c4e Mon Sep 17 00:00:00 2001 From: rahul Date: Mon, 11 Dec 2023 02:49:26 +0800 Subject: [PATCH 020/200] Update test_models_qcnn.py The last two training tests now test both qibojit and numpy backends. --- tests/test_models_qcnn.py | 49 ++++++++++++++++++--------------------- 1 file changed, 22 insertions(+), 27 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 7e9168b007..cc8ed5e2c9 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,17 +1,15 @@ import math - import numpy as np -import pytest -import qibo -from qibo import gates +import pytest + from qibo.models import Circuit +from qibo import gates, set_backend from qibo.models.qcnn import QuantumCNN num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] - def test_classifier_circuit2(): """ """ nqubits = 2 @@ -275,10 +273,18 @@ def test_1_qubit_classifier_circuit_error(): except: pass +def test_two_qubit_ansatz(): + c = Circuit(2) + c.add(gates.H(0)) + c.add(gates.RX(0,0)) + c.add(gates.CNOT(1,0)) + test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) -def test_qcnn_training(): +def test_qcnn_training(backend): + set_backend(backend) import random - # generate 2 random states and labels for pytest data = np.zeros([2, 16]) for i in range(2): @@ -304,26 +310,16 @@ def test_qcnn_training(): # test Accuracy function predictions.append(1) labels = np.array([[1], [-1], [1]]) - test_qcnn.Accuracy(labels, predictions) - - -def test_two_qubit_ansatz(): - c = Circuit(2) - c.add(gates.H(0)) - c.add(gates.RX(0, 0)) - c.add(gates.CNOT(1, 0)) - test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) -def test_two_qubit_ansatz_training(): - # test qibojit case (copy initial state as quick-fix for in-place update) - qibo.set_backend("qibojit") - +def test_two_qubit_ansatz_training(backend): + set_backend(backend) c = Circuit(2) c.add(gates.H(0)) - c.add(gates.RX(0, 0)) - c.add(gates.CNOT(1, 0)) - test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) + c.add(gates.RX(0,0)) + c.add(gates.CNOT(1,0)) + test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) data = np.zeros([2, 16]) for i in range(2): @@ -331,10 +327,8 @@ def test_two_qubit_ansatz_training(): data[i] = data_i / np.linalg.norm(data_i) labels = [[1], [-1]] - totalNParams = test_qcnn.nparams_layer * 2 - init_theta = [ - 0 for i in range(totalNParams + 1) - ] # totalNParams+1 to account for bias parameter. + totalNParams = test_qcnn.nparams_layer*2 + init_theta = [0 for i in range(totalNParams+1)] #totalNParams+1 to account for bias parameter. result = test_qcnn.minimize( init_theta, data=data, labels=labels, nshots=10000, method="Powell" @@ -349,3 +343,4 @@ def test_two_qubit_ansatz_training(): predictions.append(1) labels = np.array([[1], [-1], [1]]) test_qcnn.Accuracy(labels, predictions) + From 09d7e01810af3ac06a92fb413366b863caca6b43 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sun, 10 Dec 2023 18:49:46 +0000 Subject: [PATCH 021/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_models_qcnn.py | 32 ++++++++++++++++++-------------- 1 file changed, 18 insertions(+), 14 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index cc8ed5e2c9..1a22ab80ba 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,15 +1,16 @@ import math -import numpy as np -import pytest +import numpy as np +import pytest -from qibo.models import Circuit from qibo import gates, set_backend +from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] + def test_classifier_circuit2(): """ """ nqubits = 2 @@ -273,18 +274,20 @@ def test_1_qubit_classifier_circuit_error(): except: pass + def test_two_qubit_ansatz(): c = Circuit(2) c.add(gates.H(0)) - c.add(gates.RX(0,0)) - c.add(gates.CNOT(1,0)) - test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + c.add(gates.RX(0, 0)) + c.add(gates.CNOT(1, 0)) + test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_qcnn_training(backend): set_backend(backend) import random + # generate 2 random states and labels for pytest data = np.zeros([2, 16]) for i in range(2): @@ -311,15 +314,15 @@ def test_qcnn_training(backend): predictions.append(1) labels = np.array([[1], [-1], [1]]) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_two_qubit_ansatz_training(backend): set_backend(backend) c = Circuit(2) c.add(gates.H(0)) - c.add(gates.RX(0,0)) - c.add(gates.CNOT(1,0)) - test_qcnn = QuantumCNN(4,2,2, twoqubitansatz = c) + c.add(gates.RX(0, 0)) + c.add(gates.CNOT(1, 0)) + test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) data = np.zeros([2, 16]) for i in range(2): @@ -327,8 +330,10 @@ def test_two_qubit_ansatz_training(backend): data[i] = data_i / np.linalg.norm(data_i) labels = [[1], [-1]] - totalNParams = test_qcnn.nparams_layer*2 - init_theta = [0 for i in range(totalNParams+1)] #totalNParams+1 to account for bias parameter. + totalNParams = test_qcnn.nparams_layer * 2 + init_theta = [ + 0 for i in range(totalNParams + 1) + ] # totalNParams+1 to account for bias parameter. result = test_qcnn.minimize( init_theta, data=data, labels=labels, nshots=10000, method="Powell" @@ -343,4 +348,3 @@ def test_two_qubit_ansatz_training(backend): predictions.append(1) labels = np.array([[1], [-1], [1]]) test_qcnn.Accuracy(labels, predictions) - From f34ca9659304afec35aa14c1b32faa62ec301684 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 9 Jan 2024 16:15:03 +0800 Subject: [PATCH 022/200] Update src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 92a940102c..1f64e967ef 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -17,7 +17,7 @@ class QuantumCNN: nclasses (int): number of classes to be classified. Default setting of 2 (phases). params: initial list of variational parameters. If not provided, all parameters will be initialized to zero. - twoqubitansatz (Qibo.models.Circuit object): A two qubit ansatz that can be input by the user to form the two qubit ansatz used in the convolutional circuit. + twoqubitansatz (:class:`qibo.models.Circuit`): a two qubit ansatz that can be input by the user to form the two qubit ansatz used in the convolutional circuit. Example: .. testcode:: From d4c0374ee5f91a3481b3b01095d444a1128f7198 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 9 Jan 2024 17:36:37 +0800 Subject: [PATCH 023/200] added backend parameter to all the tests --- tests/test_models_qcnn.py | 24 +++++++++++------------- 1 file changed, 11 insertions(+), 13 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 86af4e070b..c873aaf945 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -11,7 +11,7 @@ angles0 = [i * math.pi / num_angles for i in range(num_angles)] -def test_classifier_circuit2(): +def test_classifier_circuit2(backend): """ """ nqubits = 2 nlayers = int(nqubits / 2) @@ -35,7 +35,7 @@ def test_classifier_circuit2(): np.testing.assert_allclose(statevector.imag, real_vector.imag, atol=1e-5) -def get_real_vector2(): +def get_real_vector2(backend): nqubits = 2 bits = range(nqubits) init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # @@ -75,7 +75,7 @@ def get_real_vector2(): return a -def test_classifier_circuit4(): +def test_classifier_circuit4(backend): """ """ nqubits = 4 nlayers = int(nqubits / 2) @@ -93,7 +93,7 @@ def test_classifier_circuit4(): np.testing.assert_allclose(statevector.imag, real_vector.imag, atol=1e-5) -def get_real_vector4(): +def get_real_vector4(backend): nqubits = 4 init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # angles = angles0 @@ -231,7 +231,7 @@ def get_real_vector4(): return a -def one_qubit_unitary(nqubits, bit, symbols): +def one_qubit_unitary(nqubits, bit, symbols, backend): c = Circuit(nqubits) c.add(gates.RX(bit, symbols[0])) c.add(gates.RY(bit, symbols[1])) @@ -240,42 +240,42 @@ def one_qubit_unitary(nqubits, bit, symbols): return c -def RXX_unitary(nqubits, bit0, bit1, angle): +def RXX_unitary(nqubits, bit0, bit1, angle, backend): c = Circuit(nqubits) c.add(gates.RXX(bit0, bit1, angle)) return c -def RYY_unitary(nqubits, bit0, bit1, angle): +def RYY_unitary(nqubits, bit0, bit1, angle, backend): c = Circuit(nqubits) c.add(gates.RYY(bit0, bit1, angle)) return c -def RZZ_unitary(nqubits, bit0, bit1, angle): +def RZZ_unitary(nqubits, bit0, bit1, angle, backend): c = Circuit(nqubits) c.add(gates.RZZ(bit0, bit1, angle)) return c -def CNOT_unitary(nqubits, bit0, bit1): +def CNOT_unitary(nqubits, bit0, bit1, backend): c = Circuit(nqubits) c.add(gates.CNOT(bit0, bit1)) return c -def test_1_qubit_classifier_circuit_error(): +def test_1_qubit_classifier_circuit_error(backend): try: QuantumCNN(nqubits=1, nlayers=1, nclasses=2) except: pass -def test_two_qubit_ansatz(): +def test_two_qubit_ansatz(backend): c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) @@ -283,7 +283,6 @@ def test_two_qubit_ansatz(): test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_qcnn_training(backend): set_backend(backend) import random @@ -315,7 +314,6 @@ def test_qcnn_training(backend): labels = np.array([[1], [-1], [1]]) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_two_qubit_ansatz_training(backend): set_backend(backend) c = Circuit(2) From 0c5302333d882527d342c3056717cfd1b3441358 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 9 Jan 2024 18:38:46 +0800 Subject: [PATCH 024/200] small fixes --- tests/test_models_qcnn.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index c873aaf945..ed1d6e84af 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,7 +3,7 @@ import numpy as np import pytest -from qibo import gates, set_backend +from qibo import gates from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN @@ -28,7 +28,7 @@ def test_classifier_circuit2(backend): # circuit = qcnn._circuit statevector = circuit(init_state).state() - real_vector = get_real_vector2() + real_vector = get_real_vector2(backend) # to compare statevector and real_vector np.testing.assert_allclose(statevector.real, real_vector.real, atol=1e-5) @@ -86,7 +86,7 @@ def test_classifier_circuit4(backend): circuit = qcnn.Classifier_circuit(angles) statevector = circuit(init_state).state() - real_vector = get_real_vector4() + real_vector = get_real_vector4(backend) # to compare statevector and real_vector np.testing.assert_allclose(statevector.real, real_vector.real, atol=1e-5) @@ -284,7 +284,6 @@ def test_two_qubit_ansatz(backend): def test_qcnn_training(backend): - set_backend(backend) import random # generate 2 random states and labels for pytest @@ -315,7 +314,6 @@ def test_qcnn_training(backend): def test_two_qubit_ansatz_training(backend): - set_backend(backend) c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) From 82a892d4de3f794c47e1ce01a1f3edffc20c19ff Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 9 Jan 2024 19:04:49 +0800 Subject: [PATCH 025/200] small fixes --- tests/test_models_qcnn.py | 116 +++++++++++++++++++------------------- 1 file changed, 58 insertions(+), 58 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index ed1d6e84af..9f5d66d5fc 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -44,29 +44,29 @@ def get_real_vector2(backend): # convolution k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), init_state + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), init_state ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) k += 3 # pooling ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) - a = np.dot(CNOT_unitary(nqubits, bits[0], bits[1]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[0], bits[1], backend).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[ksink : ksink + 3]) + one_qubit_unitary(nqubits, bits[1], angles[ksink : ksink + 3], backend) .invert() .unitary(), a, @@ -105,81 +105,81 @@ def get_real_vector4(backend): b1 = 1 k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), init_state + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), init_state ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) b0 = 2 b1 = 3 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) b0 = 1 b1 = 2 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) b0 = 3 b1 = 0 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) # pooling - layer 1 k = 15 # k+=3 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) - a = np.dot(CNOT_unitary(nqubits, bits[0], bits[2]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[0], bits[2], backend).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[ksink : ksink + 3]) + one_qubit_unitary(nqubits, bits[2], angles[ksink : ksink + 3], backend) .invert() .unitary(), a, @@ -187,12 +187,12 @@ def get_real_vector4(backend): k = 15 # k+=3 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) - a = np.dot(CNOT_unitary(nqubits, bits[1], bits[3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[1], bits[3], backend).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3]) + one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) .invert() .unitary(), a, @@ -200,29 +200,29 @@ def get_real_vector4(backend): # convolution - layer 2 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) k += 3 # pooling - layer 2 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) - a = np.dot(CNOT_unitary(nqubits, bits[2], bits[3]).unitary(), a) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[2], bits[3], backend).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3]) + one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) .invert() .unitary(), a, From d6e9c081b2f0eb28d9246050abdbe357f6f3be2b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 9 Jan 2024 11:05:08 +0000 Subject: [PATCH 026/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_models_qcnn.py | 174 ++++++++++++++++++++++++++++---------- 1 file changed, 130 insertions(+), 44 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 9f5d66d5fc..eb31d246ee 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -44,10 +44,13 @@ def get_real_vector2(backend): # convolution k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), init_state + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), + init_state, ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a + ) k += 3 a = np.dot(RZZ_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) k += 1 @@ -55,15 +58,23 @@ def get_real_vector2(backend): k += 1 a = np.dot(RXX_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a + ) k += 3 # pooling ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a + ) a = np.dot(CNOT_unitary(nqubits, bits[0], bits[1], backend).unitary(), a) a = np.dot( one_qubit_unitary(nqubits, bits[1], angles[ksink : ksink + 3], backend) @@ -105,78 +116,137 @@ def get_real_vector4(backend): b1 = 1 k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), init_state + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), + init_state, ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) b0 = 2 b1 = 3 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) b0 = 1 b1 = 2 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) b0 = 3 b1 = 0 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a) + a = np.dot( + RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a + ) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a + ) # pooling - layer 1 k = 15 # k+=3 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a + ) a = np.dot(CNOT_unitary(nqubits, bits[0], bits[2], backend).unitary(), a) a = np.dot( one_qubit_unitary(nqubits, bits[2], angles[ksink : ksink + 3], backend) @@ -187,9 +257,13 @@ def get_real_vector4(backend): k = 15 # k+=3 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a + ) a = np.dot(CNOT_unitary(nqubits, bits[1], bits[3], backend).unitary(), a) a = np.dot( one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) @@ -200,9 +274,13 @@ def get_real_vector4(backend): # convolution - layer 2 k = 0 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a + ) k += 3 a = np.dot(RZZ_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) k += 1 @@ -210,16 +288,24 @@ def get_real_vector4(backend): k += 1 a = np.dot(RXX_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) k += 1 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a + ) k += 3 # pooling - layer 2 ksink = k - a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a + ) k += 3 - a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a) + a = np.dot( + one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a + ) a = np.dot(CNOT_unitary(nqubits, bits[2], bits[3], backend).unitary(), a) a = np.dot( one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) From 5bbe8b9b2b8c795187fd63266ecc09e06480065d Mon Sep 17 00:00:00 2001 From: rahul Date: Thu, 11 Jan 2024 14:24:15 +0800 Subject: [PATCH 027/200] testing --- tests/test_models_qcnn.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index eb31d246ee..17e1fe1575 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,10 +3,14 @@ import numpy as np import pytest -from qibo import gates +from qibo import gates, get_backend from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN +import warnings + +text = str(get_backend()) + num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] @@ -400,6 +404,7 @@ def test_qcnn_training(backend): def test_two_qubit_ansatz_training(backend): + warnings.warn(UserWarning("{}".format(text))) c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) From ed9ad977a966c096cdcfda5f78b15a95d2bf4f1f Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 11 Jan 2024 06:24:36 +0000 Subject: [PATCH 028/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_models_qcnn.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 17e1fe1575..e6b5c6b569 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,4 +1,5 @@ import math +import warnings import numpy as np import pytest @@ -7,8 +8,6 @@ from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN -import warnings - text = str(get_backend()) num_angles = 21 From 0f3993b7a2bf05db5fc965f3f0e681e8dddeef21 Mon Sep 17 00:00:00 2001 From: rahul Date: Thu, 11 Jan 2024 14:57:45 +0800 Subject: [PATCH 029/200] test --- tests/test_models_qcnn.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index e6b5c6b569..9d7f858f64 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,14 +1,12 @@ import math -import warnings import numpy as np import pytest -from qibo import gates, get_backend +from qibo import gates from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN -text = str(get_backend()) num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] @@ -403,7 +401,6 @@ def test_qcnn_training(backend): def test_two_qubit_ansatz_training(backend): - warnings.warn(UserWarning("{}".format(text))) c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) From 6ed2ae8c4f8ec1a0e914d5e0e33fc8c27aaf80bc Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 11 Jan 2024 06:58:04 +0000 Subject: [PATCH 030/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_models_qcnn.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 9d7f858f64..eb31d246ee 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -7,7 +7,6 @@ from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN - num_angles = 21 angles0 = [i * math.pi / num_angles for i in range(num_angles)] From 687705f4e6ed061caa49625dc06b8be52bc44e98 Mon Sep 17 00:00:00 2001 From: rahul Date: Thu, 11 Jan 2024 14:58:45 +0800 Subject: [PATCH 031/200] test (hopefully will fix) --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 1f64e967ef..51146ff34e 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -60,7 +60,7 @@ def __init__( self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if "qibojit" in get_backend(): + if ("qibojit" in get_backend()) or ("qibojit-numba" in get_backend()) or ("qibojit-cuquantum" in get_backend()) or ("qibojit-cupy" in get_backend()): self.copy_init_state = True else: self.copy_init_state = False From c95ec9252ca1a9361fa444a65e0e950cbf07b3a1 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 11 Jan 2024 06:59:03 +0000 Subject: [PATCH 032/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/models/qcnn.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 51146ff34e..640904e6ee 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -60,7 +60,12 @@ def __init__( self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if ("qibojit" in get_backend()) or ("qibojit-numba" in get_backend()) or ("qibojit-cuquantum" in get_backend()) or ("qibojit-cupy" in get_backend()): + if ( + ("qibojit" in get_backend()) + or ("qibojit-numba" in get_backend()) + or ("qibojit-cuquantum" in get_backend()) + or ("qibojit-cupy" in get_backend()) + ): self.copy_init_state = True else: self.copy_init_state = False From 2d6037e8ec616200edd1f368a3b6994b814b488c Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Tue, 16 Jan 2024 13:04:51 +0400 Subject: [PATCH 033/200] split star transpiler into placer and router --- src/qibo/transpiler/placer.py | 77 +++++++++++++ src/qibo/transpiler/router.py | 102 +++++++++++++++++ src/qibo/transpiler/star_connectivity.py | 126 --------------------- tests/test_transpiler_router.py | 74 +++++++++++- tests/test_transpiler_star_connectivity.py | 98 ---------------- 5 files changed, 251 insertions(+), 226 deletions(-) delete mode 100644 src/qibo/transpiler/star_connectivity.py delete mode 100644 tests/test_transpiler_star_connectivity.py diff --git a/src/qibo/transpiler/placer.py b/src/qibo/transpiler/placer.py index 96c5ae04d0..1d1940f236 100644 --- a/src/qibo/transpiler/placer.py +++ b/src/qibo/transpiler/placer.py @@ -84,6 +84,83 @@ def _find_gates_qubits_pairs(circuit: Circuit): return gates_qubits_pairs +class StarConnectivityPlacer(Placer): + """Find an optimized qubit placement for the following connectivity: + + q + | + q -- q -- q + | + q + + Args: + connectivity (:class:`networkx.Graph`): chip connectivity, not used for this transpiler. + middle_qubit (int, optional): qubit id of the qubit that is in the middle of the star. + """ + + def __init__(self, connectivity=None, middle_qubit: int = 2): + self.middle_qubit = middle_qubit + self.connectivity = connectivity + + def __call__(self, circuit: Circuit): + """Apply the transpiler transformation on a given circuit. + + Args: + circuit (:class:`qibo.models.circuit.Circuit`): The original Qibo circuit to transform. + This circuit must contain up to two-qubit gates. + + Returns: + (dict): physical to logical qubit mapping. + """ + + # find the number of qubits for hardware circuit + nqubits = max(circuit.nqubits, self.middle_qubit + 1) + hardware_qubits = list(range(nqubits)) + + for i, gate in enumerate(circuit.queue): + if len(gate.qubits) > 2: + raise_error( + PlacementError, + "Gates targeting more than 2 qubits are not supported", + ) + if len(gate.qubits) == 2: + if self.middle_qubit not in gate.qubits: + new_middle = self._find_connected_qubit( + gate.qubits, circuit.queue[i + 1 :], hardware_qubits + ) + hardware_qubits[self.middle_qubit], hardware_qubits[new_middle] = ( + new_middle, + self.middle_qubit, + ) + break + + return dict( + zip(["q" + str(i) for i in range(circuit.nqubits)], range(circuit.nqubits)) + ) + + def _find_connected_qubit(qubits, queue, hardware_qubits): + """ + Finds which qubit should be mapped to hardware middle qubit + by looking at the two-qubit gates that follow. + """ + possible_qubits = set(qubits) + for next_gate in queue: + if len(next_gate.qubits) > 2: + raise_error( + PlacementError, + "Gates targeting more than 2 qubits are not supported", + ) + if len(next_gate.qubits) == 2: + possible_qubits &= {hardware_qubits.index(q) for q in next_gate.qubits} + if not possible_qubits: + # freedom of choice + return qubits[0] + elif len(possible_qubits) == 1: + return possible_qubits.pop() + # freedom of choice + return qubits[0] + + class Trivial(Placer): """Place qubits according to the following notation: diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 00e6a86da5..617e234581 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -40,6 +40,108 @@ def assert_connectivity(connectivity: nx.Graph, circuit: Circuit): ) +class StarConnectivityRouter(Router): + """Transforms an arbitrary circuit to one that can be executed on hardware. + + This transpiler produces a circuit that respects the following connectivity: + + q + | + q -- q -- q + | + q + + by adding SWAP gates when needed. + + Args: + connectivity (:class:`networkx.Graph`): chip connectivity, not used for this transpiler. + middle_qubit (int, optional): qubit id of the qubit that is in the middle of the star. + """ + + def __init__(self, connectivity=None, middle_qubit: int = 2): + self.middle_qubit = middle_qubit + self.connectivity = connectivity + + def __call__(self, circuit: Circuit, initial_layout=None): + """Apply the transpiler transformation on a given circuit. + + Args: + circuit (:class:`qibo.models.circuit.Circuit`): The original Qibo circuit to transform. + This circuit must contain up to two-qubit gates. + initial_layout (dict): initial physical-to-logical qubit mapping, + use `qibo.transpiler.placer.StarConnectivityPlacer` for better performance. + + Returns: + (:class:`qibo.models.circuit.Circuit`, list): circuit that performs the same operation + as the original but respects the hardware connectivity, + and list that maps logical to hardware qubits. + """ + + middle_qubit = self.middle_qubit + nqubits = max(circuit.nqubits, middle_qubit + 1) + # new circuit object that will be compatible with hardware connectivity + new = circuit.__class__(nqubits) + # list to maps logical to hardware qubits + hardware_qubits = list(initial_layout.values()) + + for i, gate in enumerate(circuit.queue): + # map gate qubits to hardware + qubits = tuple(hardware_qubits.index(q) for q in gate.qubits) + if isinstance(gate, gates.M): + new_gate = gates.M(*qubits, **gate.init_kwargs) + new_gate.result = gate.result + new.add(new_gate) + continue + + if len(qubits) > 2: + raise ConnectivityError( + "Gates targeting more than two qubits are not supported." + ) + + elif len(qubits) == 2 and middle_qubit not in qubits: + # find which qubit should be moved + new_middle = _find_connected_qubit( + qubits, circuit.queue[i + 1 :], hardware_qubits + ) + # update hardware qubits according to the swap + hardware_qubits[middle_qubit], hardware_qubits[new_middle] = ( + hardware_qubits[new_middle], + hardware_qubits[middle_qubit], + ) + new.add(gates.SWAP(middle_qubit, new_middle)) + # update gate qubits according to the new swap + qubits = tuple(hardware_qubits.index(q) for q in gate.qubits) + + # add gate to the hardware circuit + if isinstance(gate, gates.Unitary): + # gates.Unitary requires matrix as first argument + matrix = gate.init_args[0] + new.add(gate.__class__(matrix, *qubits, **gate.init_kwargs)) + else: + new.add(gate.__class__(*qubits, **gate.init_kwargs)) + hardware_qubits_keys = ["q" + str(i) for i in range(5)] + return new, dict(zip(hardware_qubits_keys, hardware_qubits)) + + +def _find_connected_qubit(qubits, queue, hardware_qubits): + """Helper method for :meth:`qibo.transpiler.StarConnectivity`. + + Finds which qubit should be mapped to hardware middle qubit + by looking at the two-qubit gates that follow. + """ + possible_qubits = set(qubits) + for next_gate in queue: + if len(next_gate.qubits) == 2: + possible_qubits &= {hardware_qubits.index(q) for q in next_gate.qubits} + if not possible_qubits: + # freedom of choice + return qubits[0] + elif len(possible_qubits) == 1: + return possible_qubits.pop() + # freedom of choice + return qubits[0] + + class CircuitMap: """Class that stores the circuit and physical-logical mapping during routing. diff --git a/src/qibo/transpiler/star_connectivity.py b/src/qibo/transpiler/star_connectivity.py deleted file mode 100644 index 693df030c1..0000000000 --- a/src/qibo/transpiler/star_connectivity.py +++ /dev/null @@ -1,126 +0,0 @@ -from qibo import Circuit, gates -from qibo.transpiler.abstract import Router -from qibo.transpiler.router import ConnectivityError - - -# TODO: split into routing plus placer steps -class StarConnectivity(Router): - """Transforms an arbitrary circuit to one that can be executed on hardware. - - This transpiler produces a circuit that respects the following connectivity: - - q - | - q -- q -- q - | - q - - by adding SWAP gates when needed. - - Args: - connectivity (:class:`networkx.Graph`): chip connectivity, not used for this transpiler. - middle_qubit (int, optional): qubit id of the qubit that is in the middle of the star. - """ - - def __init__(self, connectivity=None, middle_qubit: int = 2): - self.middle_qubit = middle_qubit - self.connectivity = connectivity - - def __call__(self, circuit: Circuit, initial_layout=None): - """Apply the transpiler transformation on a given circuit. - - Args: - circuit (:class:`qibo.models.circuit.Circuit`): The original Qibo circuit to transform. - This circuit must contain up to two-qubit gates. - - Returns: - (:class:`qibo.models.circuit.Circuit`, list): circuit that performs the same operation - as the original but respects the hardware connectivity, - and list that maps logical to hardware qubits. - """ - - middle_qubit = self.middle_qubit - # find the number of qubits for hardware circuit - if circuit.nqubits == 1: - nqubits = 1 - else: - nqubits = max(circuit.nqubits, middle_qubit + 1) - # new circuit object that will be compatible with hardware connectivity - new = circuit.__class__(nqubits) - # list to maps logical to hardware qubits - hardware_qubits = list(range(nqubits)) - - # find initial qubit mapping - for i, gate in enumerate(circuit.queue): - if len(gate.qubits) == 2: - if middle_qubit not in gate.qubits: - new_middle = _find_connected_qubit( - gate.qubits, circuit.queue[i + 1 :], hardware_qubits - ) - hardware_qubits[middle_qubit], hardware_qubits[new_middle] = ( - hardware_qubits[new_middle], - hardware_qubits[middle_qubit], - ) - break - - # the first SWAP is not needed as it can be applied via virtual mapping - add_swap = False - for i, gate in enumerate(circuit.queue): - # map gate qubits to hardware - qubits = tuple(hardware_qubits.index(q) for q in gate.qubits) - if isinstance(gate, gates.M): - new_gate = gates.M(*qubits, **gate.init_kwargs) - new_gate.result = gate.result - new.add(new_gate) - continue - - if len(qubits) > 2: - raise ConnectivityError( - "Gates targeting more than two qubits are not supported." - ) - - elif len(qubits) == 2 and middle_qubit not in qubits: - # find which qubit should be moved to 0 - new_middle = _find_connected_qubit( - qubits, circuit.queue[i + 1 :], hardware_qubits - ) - # update hardware qubits according to the swap - hardware_qubits[middle_qubit], hardware_qubits[new_middle] = ( - hardware_qubits[new_middle], - hardware_qubits[middle_qubit], - ) - if add_swap: - new.add(gates.SWAP(middle_qubit, new_middle)) - # update gate qubits according to the new swap - qubits = tuple(hardware_qubits.index(q) for q in gate.qubits) - - # add gate to the hardware circuit - if isinstance(gate, gates.Unitary): - # gates.Unitary requires matrix as first argument - matrix = gate.init_args[0] - new.add(gate.__class__(matrix, *qubits, **gate.init_kwargs)) - else: - new.add(gate.__class__(*qubits, **gate.init_kwargs)) - if len(qubits) == 2: - add_swap = True - hardware_qubits_keys = ["q" + str(i) for i in range(5)] - return new, dict(zip(hardware_qubits_keys, hardware_qubits)) - - -def _find_connected_qubit(qubits, queue, hardware_qubits): - """Helper method for :meth:`qibo.transpiler.StarConnectivity`. - - Finds which qubit should be mapped to hardware middle qubit - by looking at the two-qubit gates that follow. - """ - possible_qubits = set(qubits) - for next_gate in queue: - if len(next_gate.qubits) == 2: - possible_qubits &= {hardware_qubits.index(q) for q in next_gate.qubits} - if not possible_qubits: - # freedom of choice - return qubits[0] - elif len(possible_qubits) == 1: - return possible_qubits.pop() - # freedom of choice - return qubits[0] diff --git a/tests/test_transpiler_router.py b/tests/test_transpiler_router.py index 716f0f02bd..420b1d3a81 100644 --- a/tests/test_transpiler_router.py +++ b/tests/test_transpiler_router.py @@ -10,8 +10,21 @@ assert_circuit_equivalence, restrict_connectivity_qubits, ) -from qibo.transpiler.placer import Custom, Random, Subgraph, Trivial, assert_placement -from qibo.transpiler.router import CircuitMap, Sabre, ShortestPaths, assert_connectivity +from qibo.transpiler.placer import ( + Custom, + Random, + StarConnectivityPlacer, + Subgraph, + Trivial, + assert_placement, +) +from qibo.transpiler.router import ( + CircuitMap, + Sabre, + ShortestPaths, + StarConnectivityRouter, + assert_connectivity, +) def star_connectivity(): @@ -331,3 +344,60 @@ def test_restrict_qubits(router_algorithm): ) assert_connectivity(restricted_connectivity, routed_circ) assert_placement(routed_circ, final_layout, connectivity=restricted_connectivity) + + +def test_star_error_multi_qubit(): + circuit = Circuit(3) + circuit.add(gates.TOFFOLI(0, 1, 2)) + transpiler = StarConnectivityRouter(middle_qubit=2) + with pytest.raises(ConnectivityError): + transpiled, hardware_qubits = transpiler(circuit) + + +@pytest.mark.parametrize("nqubits", [1, 2, 3, 4, 5]) +@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) +@pytest.mark.parametrize("depth", [2, 10]) +@pytest.mark.parametrize("measurements", [True, False]) +def test_star_fix_connectivity(nqubits, depth, middle_qubit, measurements): + """Checks that the transpiled circuit can be executed and is equivalent to original.""" + original = generate_random_circuit(nqubits, depth, middle_qubit=middle_qubit) + if measurements: + original.add(gates.M(0)) + transpiler = StarConnectivityRouter(middle_qubit=middle_qubit) + transpiled, hardware_qubits = transpiler(original) + final_state = backend.execute_circuit(transpiled).state() + target_state = backend.execute_circuit(original).state() + hardware_qubits = list(hardware_qubits.values()) + target_state = _transpose_qubits(target_state, hardware_qubits) + np.testing.assert_allclose(final_state, target_state) + + +@pytest.mark.parametrize("nqubits", [2, 3, 4, 5]) +@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) +@pytest.mark.parametrize("unitary_dim", [1, 2]) +@pytest.mark.parametrize("depth", [2, 10]) +def test_fix_connectivity_unitaries(nqubits, unitary_dim, depth, middle_qubit): + """Checks that the transpiled circuit can be executed and is equivalent to original + when using unitaries.""" + # find the number of qubits for hardware circuit + n_hardware_qubits = max(nqubits, middle_qubit + 1) + + original = Circuit(n_hardware_qubits) + pairs = list(itertools.combinations(range(n_hardware_qubits), unitary_dim)) + for _ in range(depth): + qubits = pairs[int(np.random.randint(len(pairs)))] + original.add( + gates.Unitary( + random_unitary(2**unitary_dim, backend=NumpyBackend()), *qubits + ) + ) + + transpiler = StarConnectivity(middle_qubit=middle_qubit) + transpiled, hardware_qubits = transpiler(original) + # check that execution results agree with original (using simulation) + backend = NumpyBackend() + final_state = backend.execute_circuit(transpiled).state() + target_state = backend.execute_circuit(original).state() + hardware_qubits = list(hardware_qubits.values()) + target_state = _transpose_qubits(target_state, hardware_qubits) + np.testing.assert_allclose(final_state, target_state) diff --git a/tests/test_transpiler_star_connectivity.py b/tests/test_transpiler_star_connectivity.py deleted file mode 100644 index 2330afd76c..0000000000 --- a/tests/test_transpiler_star_connectivity.py +++ /dev/null @@ -1,98 +0,0 @@ -import itertools - -import numpy as np -import pytest - -from qibo import gates -from qibo.backends import NumpyBackend -from qibo.models import Circuit -from qibo.quantum_info.random_ensembles import random_unitary -from qibo.transpiler._exceptions import ConnectivityError -from qibo.transpiler.pipeline import _transpose_qubits -from qibo.transpiler.star_connectivity import StarConnectivity - - -def generate_random_circuit(nqubits, depth, seed=None, middle_qubit=2): - """Generate random circuits one-qubit rotations and CZ gates.""" - # find the number of qubits for hardware circuit - if nqubits == 1: - hardware_qubits = 1 - else: - hardware_qubits = max(nqubits, middle_qubit + 1) - - pairs = list(itertools.combinations(range(hardware_qubits), 2)) - if seed is not None: # pragma: no cover - np.random.seed(seed) - - rotations = [gates.RX, gates.RY, gates.RZ] - circuit = Circuit(hardware_qubits) - for _ in range(depth): - for i in range(hardware_qubits): - # generate a random rotation - rotation = rotations[int(np.random.randint(0, 3))] - theta = 2 * np.pi * np.random.random() - circuit.add(rotation(i, theta=theta)) - # add CZ gates on random qubit pairs - for i in np.random.randint(0, len(pairs), len(pairs)): - q1, q2 = pairs[i] - circuit.add(gates.CZ(q1, q2)) - - return circuit - - -def test_error_multi_qubit(): - circuit = Circuit(3) - circuit.add(gates.TOFFOLI(0, 1, 2)) - transpiler = StarConnectivity(middle_qubit=2) - with pytest.raises(ConnectivityError): - transpiled, hardware_qubits = transpiler(circuit) - - -@pytest.mark.parametrize("nqubits", [1, 2, 3, 4, 5]) -@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) -@pytest.mark.parametrize("depth", [2, 10]) -@pytest.mark.parametrize("measurements", [True, False]) -def test_fix_connectivity(nqubits, depth, middle_qubit, measurements): - """Checks that the transpiled circuit can be executed and is equivalent to original.""" - original = generate_random_circuit(nqubits, depth, middle_qubit=middle_qubit) - if measurements: - original.add(gates.M(0)) - transpiler = StarConnectivity(middle_qubit=middle_qubit) - transpiled, hardware_qubits = transpiler(original) - backend = NumpyBackend() - final_state = backend.execute_circuit(transpiled).state() - target_state = backend.execute_circuit(original).state() - hardware_qubits = list(hardware_qubits.values()) - target_state = _transpose_qubits(target_state, hardware_qubits) - np.testing.assert_allclose(final_state, target_state) - - -@pytest.mark.parametrize("nqubits", [2, 3, 4, 5]) -@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) -@pytest.mark.parametrize("unitary_dim", [1, 2]) -@pytest.mark.parametrize("depth", [2, 10]) -def test_fix_connectivity_unitaries(nqubits, unitary_dim, depth, middle_qubit): - """Checks that the transpiled circuit can be executed and is equivalent to original - when using unitaries.""" - # find the number of qubits for hardware circuit - n_hardware_qubits = max(nqubits, middle_qubit + 1) - - original = Circuit(n_hardware_qubits) - pairs = list(itertools.combinations(range(n_hardware_qubits), unitary_dim)) - for _ in range(depth): - qubits = pairs[int(np.random.randint(len(pairs)))] - original.add( - gates.Unitary( - random_unitary(2**unitary_dim, backend=NumpyBackend()), *qubits - ) - ) - - transpiler = StarConnectivity(middle_qubit=middle_qubit) - transpiled, hardware_qubits = transpiler(original) - # check that execution results agree with original (using simulation) - backend = NumpyBackend() - final_state = backend.execute_circuit(transpiled).state() - target_state = backend.execute_circuit(original).state() - hardware_qubits = list(hardware_qubits.values()) - target_state = _transpose_qubits(target_state, hardware_qubits) - np.testing.assert_allclose(final_state, target_state) From 3177c277c52a008f9937ae1e7b3c41239ea8d6c6 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 17 Jan 2024 12:48:14 +0400 Subject: [PATCH 034/200] tests --- src/qibo/transpiler/__init__.py | 12 +++++++++--- src/qibo/transpiler/pipeline.py | 13 ++++++++----- src/qibo/transpiler/placer.py | 4 ++-- src/qibo/transpiler/router.py | 2 +- src/qibo/transpiler/test.py | 19 +++++++++++++++++++ 5 files changed, 39 insertions(+), 11 deletions(-) create mode 100644 src/qibo/transpiler/test.py diff --git a/src/qibo/transpiler/__init__.py b/src/qibo/transpiler/__init__.py index 3ed3779d69..bfe576776c 100644 --- a/src/qibo/transpiler/__init__.py +++ b/src/qibo/transpiler/__init__.py @@ -1,6 +1,12 @@ from qibo.transpiler.optimizer import Preprocessing, Rearrange from qibo.transpiler.pipeline import Passes -from qibo.transpiler.placer import Custom, Random, ReverseTraversal, Subgraph, Trivial -from qibo.transpiler.router import Sabre, ShortestPaths -from qibo.transpiler.star_connectivity import StarConnectivity +from qibo.transpiler.placer import ( + Custom, + Random, + ReverseTraversal, + StarConnectivityPlacer, + Subgraph, + Trivial, +) +from qibo.transpiler.router import Sabre, ShortestPaths, StarConnectivityRouter from qibo.transpiler.unroller import NativeGates diff --git a/src/qibo/transpiler/pipeline.py b/src/qibo/transpiler/pipeline.py index d1bd6fdc6c..4452a90eca 100644 --- a/src/qibo/transpiler/pipeline.py +++ b/src/qibo/transpiler/pipeline.py @@ -10,9 +10,12 @@ from qibo.transpiler._exceptions import TranspilerPipelineError from qibo.transpiler.abstract import Optimizer, Placer, Router from qibo.transpiler.optimizer import Preprocessing -from qibo.transpiler.placer import Trivial, assert_placement -from qibo.transpiler.router import ConnectivityError, assert_connectivity -from qibo.transpiler.star_connectivity import StarConnectivity +from qibo.transpiler.placer import StarConnectivityPlacer, Trivial, assert_placement +from qibo.transpiler.router import ( + ConnectivityError, + StarConnectivityRouter, + assert_connectivity, +) from qibo.transpiler.unroller import ( DecompositionError, NativeGates, @@ -203,9 +206,9 @@ def default(self): # preprocessing default_passes.append(Preprocessing(connectivity=self.connectivity)) # default placer pass - default_passes.append(Trivial(connectivity=self.connectivity)) + default_passes.append(StarConnectivityPlacer(connectivity=self.connectivity)) # default router pass - default_passes.append(StarConnectivity()) + default_passes.append(StarConnectivityRouter(connectivity=self.connectivity)) # default unroller pass default_passes.append(Unroller(native_gates=self.native_gates)) diff --git a/src/qibo/transpiler/placer.py b/src/qibo/transpiler/placer.py index 1d1940f236..48160ec72b 100644 --- a/src/qibo/transpiler/placer.py +++ b/src/qibo/transpiler/placer.py @@ -135,10 +135,10 @@ def __call__(self, circuit: Circuit): break return dict( - zip(["q" + str(i) for i in range(circuit.nqubits)], range(circuit.nqubits)) + zip(["q" + str(i) for i in range(circuit.nqubits)], hardware_qubits) ) - def _find_connected_qubit(qubits, queue, hardware_qubits): + def _find_connected_qubit(self, qubits, queue, hardware_qubits): """ Finds which qubit should be mapped to hardware middle qubit by looking at the two-qubit gates that follow. diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 617e234581..3f94ea1df1 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -62,7 +62,7 @@ def __init__(self, connectivity=None, middle_qubit: int = 2): self.middle_qubit = middle_qubit self.connectivity = connectivity - def __call__(self, circuit: Circuit, initial_layout=None): + def __call__(self, circuit: Circuit, initial_layout: dict): """Apply the transpiler transformation on a given circuit. Args: diff --git a/src/qibo/transpiler/test.py b/src/qibo/transpiler/test.py new file mode 100644 index 0000000000..63c08dca53 --- /dev/null +++ b/src/qibo/transpiler/test.py @@ -0,0 +1,19 @@ +from qibo import gates +from qibo.models import Circuit +from qibo.transpiler.placer import StarConnectivityPlacer +from qibo.transpiler.router import StarConnectivityRouter + +circ = Circuit(3) +circ.add(gates.H(0)) +circ.add(gates.H(1)) +circ.add(gates.CZ(0, 1)) +circ.add(gates.CZ(1, 2)) +circ.add(gates.CZ(0, 2)) + +placer = StarConnectivityPlacer(middle_qubit=2) +lay = placer(circ) +print(lay) +router = StarConnectivityRouter() +transpiled, final = router(circuit=circ, initial_layout=lay) +print(transpiled.draw()) +print(final) From 4a78a0338eed45abe5d263fd29c29c5c52c99043 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 17 Jan 2024 16:05:58 +0400 Subject: [PATCH 035/200] fixed tests --- src/qibo/transpiler/placer.py | 4 +- src/qibo/transpiler/router.py | 2 +- src/qibo/transpiler/test.py | 19 --------- tests/test_transpiler_placer.py | 12 ++++++ tests/test_transpiler_router.py | 71 ++++++++++++--------------------- 5 files changed, 40 insertions(+), 68 deletions(-) delete mode 100644 src/qibo/transpiler/test.py diff --git a/src/qibo/transpiler/placer.py b/src/qibo/transpiler/placer.py index 48160ec72b..1817c04df2 100644 --- a/src/qibo/transpiler/placer.py +++ b/src/qibo/transpiler/placer.py @@ -134,9 +134,7 @@ def __call__(self, circuit: Circuit): ) break - return dict( - zip(["q" + str(i) for i in range(circuit.nqubits)], hardware_qubits) - ) + return dict(zip(["q" + str(i) for i in range(nqubits)], hardware_qubits)) def _find_connected_qubit(self, qubits, queue, hardware_qubits): """ diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 3f94ea1df1..558fc7f6ba 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -80,7 +80,7 @@ def __call__(self, circuit: Circuit, initial_layout: dict): middle_qubit = self.middle_qubit nqubits = max(circuit.nqubits, middle_qubit + 1) # new circuit object that will be compatible with hardware connectivity - new = circuit.__class__(nqubits) + new = Circuit(nqubits) # list to maps logical to hardware qubits hardware_qubits = list(initial_layout.values()) diff --git a/src/qibo/transpiler/test.py b/src/qibo/transpiler/test.py deleted file mode 100644 index 63c08dca53..0000000000 --- a/src/qibo/transpiler/test.py +++ /dev/null @@ -1,19 +0,0 @@ -from qibo import gates -from qibo.models import Circuit -from qibo.transpiler.placer import StarConnectivityPlacer -from qibo.transpiler.router import StarConnectivityRouter - -circ = Circuit(3) -circ.add(gates.H(0)) -circ.add(gates.H(1)) -circ.add(gates.CZ(0, 1)) -circ.add(gates.CZ(1, 2)) -circ.add(gates.CZ(0, 2)) - -placer = StarConnectivityPlacer(middle_qubit=2) -lay = placer(circ) -print(lay) -router = StarConnectivityRouter() -transpiled, final = router(circuit=circ, initial_layout=lay) -print(transpiled.draw()) -print(final) diff --git a/tests/test_transpiler_placer.py b/tests/test_transpiler_placer.py index 434037e7a4..f89e3671e1 100644 --- a/tests/test_transpiler_placer.py +++ b/tests/test_transpiler_placer.py @@ -9,6 +9,7 @@ Custom, Random, ReverseTraversal, + StarConnectivityPlacer, Subgraph, Trivial, _find_gates_qubits_pairs, @@ -321,3 +322,14 @@ def test_reverse_traversal_restricted(): assert_placement( circuit=circuit, layout=layout, connectivity=restricted_connectivity ) + + +def test_star_connectivity_placer(): + circ = Circuit(3) + circ.add(gates.CZ(0, 1)) + circ.add(gates.CZ(1, 2)) + circ.add(gates.CZ(0, 2)) + placer = StarConnectivityPlacer(middle_qubit=2) + layout = placer(circ) + assert_placement(circ, layout) + assert layout == {"q0": 0, "q1": 2, "q2": 1} diff --git a/tests/test_transpiler_router.py b/tests/test_transpiler_router.py index 420b1d3a81..bc58aa332f 100644 --- a/tests/test_transpiler_router.py +++ b/tests/test_transpiler_router.py @@ -27,11 +27,11 @@ ) -def star_connectivity(): +def star_connectivity(middle_qubit=2): Q = [i for i in range(5)] chip = nx.Graph() chip.add_nodes_from(Q) - graph_list = [(Q[i], Q[2]) for i in range(5) if i != 2] + graph_list = [(Q[i], Q[middle_qubit]) for i in range(5) if i != middle_qubit] chip.add_edges_from(graph_list) return chip @@ -351,53 +351,34 @@ def test_star_error_multi_qubit(): circuit.add(gates.TOFFOLI(0, 1, 2)) transpiler = StarConnectivityRouter(middle_qubit=2) with pytest.raises(ConnectivityError): - transpiled, hardware_qubits = transpiler(circuit) + transpiled, hardware_qubits = transpiler( + initial_layout={"q0": 0, "q1": 1, "q2": 2}, circuit=circuit + ) @pytest.mark.parametrize("nqubits", [1, 2, 3, 4, 5]) -@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) +@pytest.mark.parametrize("middle_qubit", [3, 4]) @pytest.mark.parametrize("depth", [2, 10]) @pytest.mark.parametrize("measurements", [True, False]) -def test_star_fix_connectivity(nqubits, depth, middle_qubit, measurements): - """Checks that the transpiled circuit can be executed and is equivalent to original.""" - original = generate_random_circuit(nqubits, depth, middle_qubit=middle_qubit) +def test_star_router(nqubits, depth, middle_qubit, measurements): + circuit = generate_random_circuit(nqubits, depth) + connectivity = star_connectivity(middle_qubit) if measurements: - original.add(gates.M(0)) + circuit.add(gates.M(0)) transpiler = StarConnectivityRouter(middle_qubit=middle_qubit) - transpiled, hardware_qubits = transpiler(original) - final_state = backend.execute_circuit(transpiled).state() - target_state = backend.execute_circuit(original).state() - hardware_qubits = list(hardware_qubits.values()) - target_state = _transpose_qubits(target_state, hardware_qubits) - np.testing.assert_allclose(final_state, target_state) - - -@pytest.mark.parametrize("nqubits", [2, 3, 4, 5]) -@pytest.mark.parametrize("middle_qubit", [0, 1, 2, 3, 4]) -@pytest.mark.parametrize("unitary_dim", [1, 2]) -@pytest.mark.parametrize("depth", [2, 10]) -def test_fix_connectivity_unitaries(nqubits, unitary_dim, depth, middle_qubit): - """Checks that the transpiled circuit can be executed and is equivalent to original - when using unitaries.""" - # find the number of qubits for hardware circuit - n_hardware_qubits = max(nqubits, middle_qubit + 1) - - original = Circuit(n_hardware_qubits) - pairs = list(itertools.combinations(range(n_hardware_qubits), unitary_dim)) - for _ in range(depth): - qubits = pairs[int(np.random.randint(len(pairs)))] - original.add( - gates.Unitary( - random_unitary(2**unitary_dim, backend=NumpyBackend()), *qubits - ) - ) - - transpiler = StarConnectivity(middle_qubit=middle_qubit) - transpiled, hardware_qubits = transpiler(original) - # check that execution results agree with original (using simulation) - backend = NumpyBackend() - final_state = backend.execute_circuit(transpiled).state() - target_state = backend.execute_circuit(original).state() - hardware_qubits = list(hardware_qubits.values()) - target_state = _transpose_qubits(target_state, hardware_qubits) - np.testing.assert_allclose(final_state, target_state) + placer = StarConnectivityPlacer(middle_qubit=middle_qubit) + initial_layout = placer(circuit=circuit) + transpiled_circuit, final_qubit_map = transpiler( + circuit=circuit, initial_layout=initial_layout + ) + assert_connectivity(connectivity, transpiled_circuit) + assert_placement(transpiled_circuit, final_qubit_map) + matched_original = Circuit(max(circuit.nqubits, middle_qubit + 1)) + for gate in circuit.queue: + matched_original.add(gate) + assert_circuit_equivalence( + original_circuit=matched_original, + transpiled_circuit=transpiled_circuit, + final_map=final_qubit_map, + initial_map=initial_layout, + ) From 92a152cb690ae5708a964da022ff6e6a70982644 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Thu, 18 Jan 2024 14:41:05 +0400 Subject: [PATCH 036/200] fixed coverage --- tests/test_transpiler_placer.py | 8 ++++++++ tests/test_transpiler_router.py | 25 +++++++++++++++++++++---- 2 files changed, 29 insertions(+), 4 deletions(-) diff --git a/tests/test_transpiler_placer.py b/tests/test_transpiler_placer.py index f89e3671e1..3df725a112 100644 --- a/tests/test_transpiler_placer.py +++ b/tests/test_transpiler_placer.py @@ -333,3 +333,11 @@ def test_star_connectivity_placer(): layout = placer(circ) assert_placement(circ, layout) assert layout == {"q0": 0, "q1": 2, "q2": 1} + + +def test_star_connectivity_placer_error(): + circ = Circuit(3) + circ.add(gates.TOFFOLI(0, 1, 2)) + placer = StarConnectivityPlacer(middle_qubit=2) + with pytest.raises(PlacementError): + layout = placer(circ) diff --git a/tests/test_transpiler_router.py b/tests/test_transpiler_router.py index bc58aa332f..2cf2364fe9 100644 --- a/tests/test_transpiler_router.py +++ b/tests/test_transpiler_router.py @@ -1,9 +1,13 @@ +import itertools + import networkx as nx import numpy as np import pytest from qibo import gates +from qibo.backends import NumpyBackend from qibo.models import Circuit +from qibo.quantum_info.random_ensembles import random_unitary from qibo.transpiler._exceptions import ConnectivityError from qibo.transpiler.optimizer import Preprocessing from qibo.transpiler.pipeline import ( @@ -356,13 +360,26 @@ def test_star_error_multi_qubit(): ) -@pytest.mark.parametrize("nqubits", [1, 2, 3, 4, 5]) -@pytest.mark.parametrize("middle_qubit", [3, 4]) +@pytest.mark.parametrize("nqubits", [1, 3, 5]) +@pytest.mark.parametrize("middle_qubit", [0, 2, 4]) @pytest.mark.parametrize("depth", [2, 10]) @pytest.mark.parametrize("measurements", [True, False]) -def test_star_router(nqubits, depth, middle_qubit, measurements): - circuit = generate_random_circuit(nqubits, depth) +@pytest.mark.parametrize("unitaries", [True, False]) +def test_star_router(nqubits, depth, middle_qubit, measurements, unitaries): + unitary_dim = min(2, nqubits) connectivity = star_connectivity(middle_qubit) + if unitaries: + circuit = Circuit(nqubits) + pairs = list(itertools.combinations(range(nqubits), unitary_dim)) + for _ in range(depth): + qubits = pairs[int(np.random.randint(len(pairs)))] + circuit.add( + gates.Unitary( + random_unitary(2**unitary_dim, backend=NumpyBackend()), *qubits + ) + ) + else: + circuit = generate_random_circuit(nqubits, depth) if measurements: circuit.add(gates.M(0)) transpiler = StarConnectivityRouter(middle_qubit=middle_qubit) From c6e323a25874cae24493dcb64ad66332c2602eed Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Fri, 19 Jan 2024 13:35:27 +0400 Subject: [PATCH 037/200] fix coverage --- tests/test_transpiler_placer.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/tests/test_transpiler_placer.py b/tests/test_transpiler_placer.py index 3df725a112..801304bc31 100644 --- a/tests/test_transpiler_placer.py +++ b/tests/test_transpiler_placer.py @@ -335,8 +335,11 @@ def test_star_connectivity_placer(): assert layout == {"q0": 0, "q1": 2, "q2": 1} -def test_star_connectivity_placer_error(): +@pytest.mark.parametrize("first", [True, False]) +def test_star_connectivity_placer_error(first): circ = Circuit(3) + if first: + circ.add(gates.CZ(0, 1)) circ.add(gates.TOFFOLI(0, 1, 2)) placer = StarConnectivityPlacer(middle_qubit=2) with pytest.raises(PlacementError): From e10c04383df081002e9262c21d16cd54253aa610 Mon Sep 17 00:00:00 2001 From: Rahul Arvind Date: Tue, 23 Jan 2024 15:48:25 +0800 Subject: [PATCH 038/200] Testing using capsys --- pyproject.toml | 8 +------- tests/test_models_qcnn.py | 8 +++++++- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 1209f86ad7..ef72a489af 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -95,10 +95,4 @@ output-format = "colorized" [tool.pytest.ini_options] testpaths = ['tests/'] filterwarnings = ['ignore::RuntimeWarning'] -addopts = [ - '--cov=qibo', - '--cov-append', - '--cov-report=xml', - '--cov-report=html', - '--durations=60', -] + diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index eb31d246ee..43e9718dfa 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -4,6 +4,7 @@ import pytest from qibo import gates +from qibo import get_backend from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN @@ -11,8 +12,13 @@ angles0 = [i * math.pi / num_angles for i in range(num_angles)] -def test_classifier_circuit2(backend): +def test_classifier_circuit2(backend, capsys, mad): """ """ + + with capsys.disabled(): + backender = get_backend() + print(str(backender)) + nqubits = 2 nlayers = int(nqubits / 2) init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # From de0d253f24ae3c20d9a155b0da913753cbb6240e Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 23 Jan 2024 07:50:19 +0000 Subject: [PATCH 039/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pyproject.toml | 1 - tests/test_models_qcnn.py | 3 +-- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index ef72a489af..61641cc190 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -95,4 +95,3 @@ output-format = "colorized" [tool.pytest.ini_options] testpaths = ['tests/'] filterwarnings = ['ignore::RuntimeWarning'] - diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 43e9718dfa..2c58653193 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,8 +3,7 @@ import numpy as np import pytest -from qibo import gates -from qibo import get_backend +from qibo import gates, get_backend from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN From 27eefac7de76abb400fe0879a0c5bbdf9b08d6dc Mon Sep 17 00:00:00 2001 From: Rahul Arvind Date: Tue, 23 Jan 2024 16:02:48 +0800 Subject: [PATCH 040/200] Conftest test --- tests/test_models_qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 43e9718dfa..bfb37084ea 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -12,7 +12,7 @@ angles0 = [i * math.pi / num_angles for i in range(num_angles)] -def test_classifier_circuit2(backend, capsys, mad): +def test_classifier_circuit2(backend, capsys): """ """ with capsys.disabled(): From d578f96a34fffe47ce3eaf806266ee25d2e036d8 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 23 Jan 2024 16:47:34 +0800 Subject: [PATCH 041/200] Update pyproject.toml --- pyproject.toml | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 61641cc190..1209f86ad7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -95,3 +95,10 @@ output-format = "colorized" [tool.pytest.ini_options] testpaths = ['tests/'] filterwarnings = ['ignore::RuntimeWarning'] +addopts = [ + '--cov=qibo', + '--cov-append', + '--cov-report=xml', + '--cov-report=html', + '--durations=60', +] From 4bad7cc199c7864a1b789a0885b1ee1b08872838 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 23 Jan 2024 18:17:02 +0400 Subject: [PATCH 042/200] refactoring `random_statevector` --- src/qibo/quantum_info/random_ensembles.py | 24 +++++------------------ 1 file changed, 5 insertions(+), 19 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 9ef63a653d..d831da5c84 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -415,7 +415,7 @@ def random_quantum_channel( return super_op -def random_statevector(dims: int, haar: bool = False, seed=None, backend=None): +def random_statevector(dims: int, seed=None, backend=None): """Creates a random statevector :math:`\\ket{\\psi}`. .. math:: @@ -427,10 +427,6 @@ def random_statevector(dims: int, haar: bool = False, seed=None, backend=None): Args: dims (int): dimension of the matrix. - haar (bool, optional): if ``True``, statevector is created by sampling a - Haar random unitary :math:`U_{\\text{haar}}` and acting with it on a - random computational basis state :math:`\\ket{k}`, i.e. - :math:`\\ket{\\psi} = U_{\\text{haar}} \\ket{k}`. Defaults to ``False``. seed (int or :class:`numpy.random.Generator`, optional): Either a generator of random numbers or a fixed seed to initialize a generator. If ``None``, initializes a generator with a random seed. Defaults to ``None``. @@ -445,9 +441,6 @@ def random_statevector(dims: int, haar: bool = False, seed=None, backend=None): if dims <= 0: raise_error(ValueError, "dim must be of type int and >= 1") - if not isinstance(haar, bool): - raise_error(TypeError, f"haar must be type bool, but it is type {type(haar)}.") - if ( seed is not None and not isinstance(seed, int) @@ -464,18 +457,11 @@ def random_statevector(dims: int, haar: bool = False, seed=None, backend=None): np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed ) - if not haar: - # sample real and imag parts of complex amplitude in [-1, 1] - state = 1j * (2 * local_state.random(dims) - 1) - state += 2 * local_state.random(dims) - 1 - state /= np.linalg.norm(state) - state = backend.cast(state, dtype=state.dtype) - else: - # select a random column of a haar random unitary - k = local_state.integers(low=0, high=dims) - state = random_unitary(dims, measure="haar", seed=seed, backend=backend)[:, k] + state = local_state.standard_normal(dims).astype(complex) + state += 1.0j * local_state.standard_normal(dims) + state /= np.linalg.norm(state) - return state + return backend.cast(state, dtype=state.dtype) def random_density_matrix( From 4b64d1956efb36707ec04f3fddbb5baeac5cfa1a Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 23 Jan 2024 18:19:13 +0400 Subject: [PATCH 043/200] adjust `random_density_matrix` --- src/qibo/quantum_info/random_ensembles.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index d831da5c84..495081c1c9 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -567,7 +567,7 @@ def random_density_matrix( if pure: state = random_statevector(dims, seed=seed, backend=backend) - state = np.outer(state, np.transpose(np.conj(state))) + state = np.outer(state, np.conj(state)) else: if metric in ["hilbert-schmidt", "ginibre"]: state = random_gaussian_matrix( @@ -583,7 +583,7 @@ def random_density_matrix( state, random_gaussian_matrix(dims, rank, seed=seed, backend=backend) ) state = np.dot(state, np.transpose(np.conj(state))) - state = state / np.trace(state) + state /= np.trace(state) state = backend.cast(state, dtype=state.dtype) From f9bb2a7e6fa00548d77512b5709f129bcd3f12d0 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 23 Jan 2024 18:20:12 +0400 Subject: [PATCH 044/200] adjust tests --- tests/test_quantum_info_random.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/tests/test_quantum_info_random.py b/tests/test_quantum_info_random.py index 01000ab822..0c46afe4ab 100644 --- a/tests/test_quantum_info_random.py +++ b/tests/test_quantum_info_random.py @@ -228,25 +228,21 @@ def test_random_quantum_channel(backend, representation, measure, rank, order): ) -@pytest.mark.parametrize("haar", [False, True]) @pytest.mark.parametrize("seed", [None, 10, np.random.default_rng(10)]) -def test_random_statevector(backend, haar, seed): +def test_random_statevector(backend, seed): with pytest.raises(TypeError): dims = "10" random_statevector(dims, backend=backend) with pytest.raises(ValueError): dims = 0 random_statevector(dims, backend=backend) - with pytest.raises(TypeError): - dims = 2 - random_statevector(dims, haar=1, backend=backend) with pytest.raises(TypeError): dims = 2 random_statevector(dims, seed=0.1, backend=backend) # tests if random statevector is a pure state dims = 4 - state = random_statevector(dims, haar=haar, seed=seed, backend=backend) + state = random_statevector(dims, seed=seed, backend=backend) backend.assert_allclose(purity(state) <= 1.0 + PRECISION_TOL, True) backend.assert_allclose(purity(state) >= 1.0 - PRECISION_TOL, True) From 9c761843944d0e6c1d67a897aea29db162ae6bc0 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 23 Jan 2024 18:22:19 +0400 Subject: [PATCH 045/200] fix `haar_integral` --- src/qibo/quantum_info/utils.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/src/qibo/quantum_info/utils.py b/src/qibo/quantum_info/utils.py index eb5a447d8d..991b23172a 100644 --- a/src/qibo/quantum_info/utils.py +++ b/src/qibo/quantum_info/utils.py @@ -339,9 +339,7 @@ def haar_integral( rand_unit_density, dtype=rand_unit_density.dtype ) for _ in range(samples): - haar_state = np.reshape( - random_statevector(dim, haar=True, backend=backend), (-1, 1) - ) + haar_state = np.reshape(random_statevector(dim, backend=backend), (-1, 1)) rho = haar_state @ np.conj(np.transpose(haar_state)) From 90252c54aba927e675277f74e1a1e2882e6baf20 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 24 Jan 2024 12:33:12 +0400 Subject: [PATCH 046/200] find connected qubit improved --- src/qibo/transpiler/placer.py | 30 ++++++------------------------ src/qibo/transpiler/router.py | 17 ++++++++++++----- 2 files changed, 18 insertions(+), 29 deletions(-) diff --git a/src/qibo/transpiler/placer.py b/src/qibo/transpiler/placer.py index 1817c04df2..c6b1f8f5fb 100644 --- a/src/qibo/transpiler/placer.py +++ b/src/qibo/transpiler/placer.py @@ -8,6 +8,7 @@ from qibo.models import Circuit from qibo.transpiler._exceptions import PlacementError from qibo.transpiler.abstract import Placer, Router +from qibo.transpiler.router import _find_connected_qubit def assert_placement( @@ -125,8 +126,11 @@ def __call__(self, circuit: Circuit): ) if len(gate.qubits) == 2: if self.middle_qubit not in gate.qubits: - new_middle = self._find_connected_qubit( - gate.qubits, circuit.queue[i + 1 :], hardware_qubits + new_middle = _find_connected_qubit( + gate.qubits, + circuit.queue[i + 1 :], + hardware_qubits, + error=PlacementError, ) hardware_qubits[self.middle_qubit], hardware_qubits[new_middle] = ( new_middle, @@ -136,28 +140,6 @@ def __call__(self, circuit: Circuit): return dict(zip(["q" + str(i) for i in range(nqubits)], hardware_qubits)) - def _find_connected_qubit(self, qubits, queue, hardware_qubits): - """ - Finds which qubit should be mapped to hardware middle qubit - by looking at the two-qubit gates that follow. - """ - possible_qubits = set(qubits) - for next_gate in queue: - if len(next_gate.qubits) > 2: - raise_error( - PlacementError, - "Gates targeting more than 2 qubits are not supported", - ) - if len(next_gate.qubits) == 2: - possible_qubits &= {hardware_qubits.index(q) for q in next_gate.qubits} - if not possible_qubits: - # freedom of choice - return qubits[0] - elif len(possible_qubits) == 1: - return possible_qubits.pop() - # freedom of choice - return qubits[0] - class Trivial(Placer): """Place qubits according to the following notation: diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 558fc7f6ba..82f6ac1b7e 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -101,7 +101,10 @@ def __call__(self, circuit: Circuit, initial_layout: dict): elif len(qubits) == 2 and middle_qubit not in qubits: # find which qubit should be moved new_middle = _find_connected_qubit( - qubits, circuit.queue[i + 1 :], hardware_qubits + qubits, + circuit.queue[i + 1 :], + hardware_qubits, + error=ConnectivityError, ) # update hardware qubits according to the swap hardware_qubits[middle_qubit], hardware_qubits[new_middle] = ( @@ -123,22 +126,26 @@ def __call__(self, circuit: Circuit, initial_layout: dict): return new, dict(zip(hardware_qubits_keys, hardware_qubits)) -def _find_connected_qubit(qubits, queue, hardware_qubits): - """Helper method for :meth:`qibo.transpiler.StarConnectivity`. +def _find_connected_qubit(qubits, queue, hardware_qubits, error): + """Helper method for :meth:`qibo.transpiler.router.StarConnectivityRouter` + and :meth:`qibo.transpiler.router.StarConnectivityPlacer`. Finds which qubit should be mapped to hardware middle qubit by looking at the two-qubit gates that follow. """ possible_qubits = set(qubits) for next_gate in queue: + if len(next_gate.qubits) > 2: + raise_error( + error, + "Gates targeting more than 2 qubits are not supported", + ) if len(next_gate.qubits) == 2: possible_qubits &= {hardware_qubits.index(q) for q in next_gate.qubits} if not possible_qubits: - # freedom of choice return qubits[0] elif len(possible_qubits) == 1: return possible_qubits.pop() - # freedom of choice return qubits[0] From f31d5c508d3e1ff7866ad8aa30e90605de9ed6e1 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 27 Jan 2024 09:46:41 +0400 Subject: [PATCH 047/200] test new random generation --- src/qibo/quantum_info/random_ensembles.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 495081c1c9..3309bdc5b0 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -454,7 +454,9 @@ def random_statevector(dims: int, seed=None, backend=None): backend = GlobalBackend() local_state = ( - np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed + backend.np.random.default_rng(seed) + if seed is None or isinstance(seed, int) + else seed ) state = local_state.standard_normal(dims).astype(complex) From 380a80b30f4e311f8953d613f088f51298bc1ab7 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 27 Jan 2024 09:51:43 +0400 Subject: [PATCH 048/200] revamp seed --- src/qibo/quantum_info/random_ensembles.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 3309bdc5b0..c2fac74687 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -453,11 +453,13 @@ def random_statevector(dims: int, seed=None, backend=None): if backend is None: # pragma: no cover backend = GlobalBackend() - local_state = ( - backend.np.random.default_rng(seed) - if seed is None or isinstance(seed, int) - else seed - ) + if seed is None or isinstance(seed, int): + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + local_state = backend.np.random.default_rng(seed) + else: + local_state = np.random.default_rng(seed) + else: + local_state = seed state = local_state.standard_normal(dims).astype(complex) state += 1.0j * local_state.standard_normal(dims) From 514e4143fe30352632353c2ea296ac97184f6b89 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 08:39:13 +0400 Subject: [PATCH 049/200] fix coverage --- src/qibo/quantum_info/random_ensembles.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index c2fac74687..abe58141b4 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -454,7 +454,10 @@ def random_statevector(dims: int, seed=None, backend=None): backend = GlobalBackend() if seed is None or isinstance(seed, int): - if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + if backend.__class__.__name__ in [ + "CupyBackend", + "CuQuantumBackend", + ]: # pragma: no cover local_state = backend.np.random.default_rng(seed) else: local_state = np.random.default_rng(seed) From fef4cb5bf232c161184123bf6a6e8332d8e51661 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 08:52:03 +0400 Subject: [PATCH 050/200] create `entanglement.py` --- src/qibo/quantum_info/entanglement.py | 298 ++++++++++++++++++++++++++ 1 file changed, 298 insertions(+) create mode 100644 src/qibo/quantum_info/entanglement.py diff --git a/src/qibo/quantum_info/entanglement.py b/src/qibo/quantum_info/entanglement.py new file mode 100644 index 0000000000..7f006655d6 --- /dev/null +++ b/src/qibo/quantum_info/entanglement.py @@ -0,0 +1,298 @@ +"""Submodules with entanglement measures.""" + +import numpy as np + +from qibo.backends import GlobalBackend +from qibo.config import PRECISION_TOL, raise_error +from qibo.quantum_info.metrics import fidelity, purity + + +def concurrence(state, bipartition, check_purity: bool = True, backend=None): + """Calculates concurrence of a pure bipartite quantum state + :math:`\\rho \\in \\mathcal{H}_{A} \\otimes \\mathcal{H}_{B}` as + + .. math:: + C(\\rho) = \\sqrt{2 \\, (\\text{tr}^{2}(\\rho) - \\text{tr}(\\rho_{A}^{2}))} \\, , + + where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density operator + obtained by tracing out the qubits in the ``bipartition`` :math:`B`. + + Args: + state (ndarray): statevector or density matrix. + bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. + check_purity (bool, optional): if ``True``, checks if ``state`` is pure. If ``False``, + it assumes ``state`` is pure . Defaults to ``True``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + Returns: + float: Concurrence of :math:`\\rho`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if ( + (len(state.shape) not in [1, 2]) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if isinstance(check_purity, bool) is False: + raise_error( + TypeError, + f"check_purity must be type bool, but it is type {type(check_purity)}.", + ) + + nqubits = int(np.log2(state.shape[0])) + + if check_purity is True: + purity_total_system = purity(state) + + mixed = bool(abs(purity_total_system - 1.0) > PRECISION_TOL) + if mixed is True: + raise_error( + NotImplementedError, + "concurrence only implemented for pure quantum states.", + ) + + reduced_density_matrix = ( + backend.partial_trace(state, bipartition, nqubits) + if len(state.shape) == 1 + else backend.partial_trace_density_matrix(state, bipartition, nqubits) + ) + + purity_reduced = purity(reduced_density_matrix) + if purity_reduced - 1.0 > 0.0: + purity_reduced = round(purity_reduced, 7) + + concur = np.sqrt(2 * (1 - purity_reduced)) + + return concur + + +def entanglement_of_formation( + state, bipartition, base: float = 2, check_purity: bool = True, backend=None +): + """Calculates the entanglement of formation :math:`E_{f}` of a pure bipartite + quantum state :math:`\\rho`, which is given by + + .. math:: + E_{f} = H([1 - x, x]) \\, , + + where + + .. math:: + x = \\frac{1 + \\sqrt{1 - C^{2}(\\rho)}}{2} \\, , + + :math:`C(\\rho)` is the :func:`qibo.quantum_info.concurrence` of :math:`\\rho`, + and :math:`H` is the :func:`qibo.quantum_info.shannon_entropy`. + + Args: + state (ndarray): statevector or density matrix. + bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. + base (float): the base of the log in :func:`qibo.quantum_info.shannon_entropy`. + Defaults to :math:`2`. + check_purity (bool, optional): if ``True``, checks if ``state`` is pure. If ``False``, + it assumes ``state`` is pure . Default: ``True``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + + Returns: + float: entanglement of formation of state :math:`\\rho`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + from qibo.quantum_info.utils import shannon_entropy # pylint: disable=C0415 + + concur = concurrence( + state, bipartition=bipartition, check_purity=check_purity, backend=backend + ) + concur = (1 + np.sqrt(1 - concur**2)) / 2 + probabilities = [1 - concur, concur] + + ent_of_form = shannon_entropy(probabilities, base=base, backend=backend) + + return ent_of_form + + +def entanglement_fidelity( + channel, nqubits: int, state=None, check_hermitian: bool = False, backend=None +): + """Entanglement fidelity :math:`F_{\\mathcal{E}}` of a ``channel`` :math:`\\mathcal{E}` + on ``state`` :math:`\\rho` is given by + + .. math:: + F_{\\mathcal{E}}(\\rho) = F(\\rho_{f}, \\rho) + + where :math:`F` is the :func:`qibo.quantum_info.fidelity` function for states, + and :math:`\\rho_{f} = \\mathcal{E}_{A} \\otimes I_{B}(\\rho)` + is the state after the channel :math:`\\mathcal{E}` was applied to + partition :math:`A`. + + Args: + channel (:class:`qibo.gates.channels.Channel`): quantum channel + acting on partition :math:`A`. + nqubits (int): total number of qubits in ``state``. + state (ndarray, optional): statevector or density matrix to be evolved + by ``channel``. If ``None``, defaults to the maximally entangled state + :math:`\\frac{1}{2^{n}} \\, \\sum_{k} \\, \\ket{k}\\ket{k}`, where + :math:`n` is ``nqubits``. Defaults to ``None``. + check_hermitian (bool, optional): if ``True``, checks if the final state + :math:`\\rho_{f}` is Hermitian. If ``False``, it assumes it is Hermitian. + Defaults to ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + Returns: + float: Entanglement fidelity :math:`F_{\\mathcal{E}}`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(nqubits, int) is False: + raise_error( + TypeError, f"nqubits must be type int, but it is type {type(nqubits)}." + ) + + if nqubits <= 0: + raise_error( + ValueError, f"nqubits must be a positive integer, but it is {nqubits}." + ) + + if state is not None and ( + (len(state.shape) not in [1, 2]) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if isinstance(check_hermitian, bool) is False: + raise_error( + TypeError, + f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", + ) + + if state is None: + state = backend.plus_density_matrix(nqubits) + + # necessary because this function do support repeated execution, + # so it has to default to density matrices + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + state_final = backend.apply_channel_density_matrix(channel, state, nqubits) + + entang_fidelity = fidelity( + state_final, state, check_hermitian=check_hermitian, backend=backend + ) + + return entang_fidelity + + +def meyer_wallach_entanglement(circuit, backend=None): + """Computes the Meyer-Wallach entanglement Q of the `circuit`, + + .. math:: + Q(\\theta) = 1 - \\frac{1}{N} \\, \\sum_{k} \\, + \\text{tr}\\left(\\rho_{k^{2}}(\\theta)\\right) \\, . + + Args: + circuit (:class:`qibo.models.Circuit`): Parametrized circuit. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + Returns: + float: Meyer-Wallach entanglement. + """ + + if backend is None: # pragma: no cover + backend = GlobalBackend() + + circuit.density_matrix = True + nqubits = circuit.nqubits + + rho = backend.execute_circuit(circuit).state() + + ent = 0 + for j in range(nqubits): + trace_q = list(range(nqubits)) + trace_q.pop(j) + + rho_r = backend.partial_trace_density_matrix(rho, trace_q, nqubits) + + trace = purity(rho_r) + + ent += trace + + entanglement = 1 - ent / nqubits + + return entanglement + + +def entangling_capability(circuit, samples: int, seed=None, backend=None): + """Returns the entangling capability :math:`\\text{Ent}` of a parametrized + circuit, which is average Meyer-Wallach entanglement Q of the circuit, i.e. + + .. math:: + \\text{Ent} = \\frac{2}{S}\\sum_{k}Q_k \\, , + + where :math:`S` is the number of samples. + + Args: + circuit (:class:`qibo.models.Circuit`): Parametrized circuit. + samples (int): number of samples to estimate the integral. + seed (int or :class:`numpy.random.Generator`, optional): Either a generator of random + numbers or a fixed seed to initialize a generator. If ``None``, initializes + a generator with a random seed. Default: ``None``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + Returns: + float: Entangling capability. + """ + + if isinstance(samples, int) is False: + raise_error( + TypeError, f"samples must be type int, but it is type {type(samples)}." + ) + + if ( + seed is not None + and not isinstance(seed, int) + and not isinstance(seed, np.random.Generator) + ): + raise_error( + TypeError, "seed must be either type int or numpy.random.Generator." + ) + + if backend is None: # pragma: no cover + backend = GlobalBackend() + + local_state = ( + np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed + ) + + res = [] + for _ in range(samples): + params = local_state.uniform(-np.pi, np.pi, circuit.trainable_gates.nparams) + circuit.set_parameters(params) + entanglement = meyer_wallach_entanglement(circuit, backend=backend) + res.append(entanglement) + + capability = 2 * np.real(np.sum(res)) / samples + + return capability From e9bef500baae1a2dd84341fe15d0020d2f99e623 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 08:52:14 +0400 Subject: [PATCH 051/200] create `entropies.py` --- src/qibo/quantum_info/entropies.py | 158 +++++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 src/qibo/quantum_info/entropies.py diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py new file mode 100644 index 0000000000..82e557772c --- /dev/null +++ b/src/qibo/quantum_info/entropies.py @@ -0,0 +1,158 @@ +"""Submodule with entropy measures.""" + +import numpy as np + +from qibo.backends import GlobalBackend +from qibo.config import raise_error +from qibo.quantum_info.metrics import _check_hermitian_or_not_gpu, purity + + +def entropy( + state, + base: float = 2, + check_hermitian: bool = False, + return_spectrum: bool = False, + backend=None, +): + """The von-Neumann entropy :math:`S(\\rho)` of a quantum ``state`` :math:`\\rho`, which + is given by + + .. math:: + S(\\rho) = - \\text{tr}\\left[\\rho \\, \\log(\\rho)\\right] + + Args: + state (ndarray): statevector or density matrix. + base (float, optional): the base of the log. Defaults to :math:`2`. + check_hermitian (bool, optional): if ``True``, checks if ``state`` is Hermitian. + If ``False``, it assumes ``state`` is Hermitian . + Defaults to ``False``. + return_spectrum: if ``True``, returns ``entropy`` and + :math:`-\\log_{\\textup{b}}(\\textup{eigenvalues})`, where :math:`b` is ``base``. + If ``False``, returns only ``entropy``. Default is ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: The von-Neumann entropy :math:`S` of ``state`` :math:`\\rho`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if ( + (len(state.shape) >= 3) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if isinstance(check_hermitian, bool) is False: + raise_error( + TypeError, + f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", + ) + + if purity(state) == 1.0: + if return_spectrum: + return 0.0, backend.cast([1.0], dtype=float) + + return 0.0 + + if check_hermitian is False or _check_hermitian_or_not_gpu(state, backend=backend): + eigenvalues = np.linalg.eigvalsh(state) + else: + eigenvalues = np.linalg.eigvals(state) + + if base == 2: + log_prob = np.where(eigenvalues > 0, np.log2(eigenvalues), 0.0) + elif base == 10: + log_prob = np.where(eigenvalues > 0, np.log10(eigenvalues), 0.0) + elif base == np.e: + log_prob = np.where(eigenvalues > 0, np.log(eigenvalues), 0.0) + else: + log_prob = np.where(eigenvalues > 0, np.log(eigenvalues) / np.log(base), 0.0) + + ent = -np.sum(eigenvalues * log_prob) + # absolute value if entropy == 0.0 to avoid returning -0.0 + ent = np.abs(ent) if ent == 0.0 else ent + + ent = float(ent) + + if return_spectrum: + log_prob = backend.cast(log_prob, dtype=log_prob.dtype) + return ent, -log_prob + + return ent + + +def entanglement_entropy( + state, + bipartition, + base: float = 2, + check_hermitian: bool = False, + return_spectrum: bool = False, + backend=None, +): + """Calculates the entanglement entropy :math:`S` of bipartition :math:`A` + of ``state`` :math:`\\rho`. This is given by + + .. math:: + S(\\rho_{A}) = -\\text{tr}(\\rho_{A} \\, \\log(\\rho_{A})) \\, , + + where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density matrix calculated + by tracing out the ``bipartition`` :math:`B`. + + Args: + state (ndarray): statevector or density matrix. + bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. + base (float, optional): the base of the log. Defaults to :math: `2`. + check_hermitian (bool, optional): if ``True``, checks if :math:`\\rho_{A}` is Hermitian. + If ``False``, it assumes ``state`` is Hermitian . Default: ``False``. + return_spectrum: if ``True``, returns ``entropy`` and eigenvalues of ``state``. + If ``False``, returns only ``entropy``. Default is ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if ( + (len(state.shape) not in [1, 2]) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + nqubits = int(np.log2(state.shape[0])) + + reduced_density_matrix = ( + backend.partial_trace(state, bipartition, nqubits) + if len(state.shape) == 1 + else backend.partial_trace_density_matrix(state, bipartition, nqubits) + ) + + entropy_entanglement = entropy( + reduced_density_matrix, + base=base, + check_hermitian=check_hermitian, + return_spectrum=return_spectrum, + backend=backend, + ) + + return entropy_entanglement From f989054996c2f09f797c2e12ce85b418dcf1b126 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 08:52:32 +0400 Subject: [PATCH 052/200] move functions to `entanglement.py` and `entropies.py` --- src/qibo/quantum_info/metrics.py | 442 ------------------------------- 1 file changed, 442 deletions(-) diff --git a/src/qibo/quantum_info/metrics.py b/src/qibo/quantum_info/metrics.py index eb29f1b486..f11225f9d9 100644 --- a/src/qibo/quantum_info/metrics.py +++ b/src/qibo/quantum_info/metrics.py @@ -57,273 +57,6 @@ def impurity(state): return 1 - purity(state) -def concurrence(state, bipartition, check_purity: bool = True, backend=None): - """Calculates concurrence of a pure bipartite quantum state - :math:`\\rho \\in \\mathcal{H}_{A} \\otimes \\mathcal{H}_{B}` as - - .. math:: - C(\\rho) = \\sqrt{2 \\, (\\text{tr}^{2}(\\rho) - \\text{tr}(\\rho_{A}^{2}))} \\, , - - where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density operator - obtained by tracing out the qubits in the ``bipartition`` :math:`B`. - - Args: - state (ndarray): statevector or density matrix. - bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. - check_purity (bool, optional): if ``True``, checks if ``state`` is pure. If ``False``, - it assumes ``state`` is pure . Defaults to ``True``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - Returns: - float: Concurrence of :math:`\\rho`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if ( - (len(state.shape) not in [1, 2]) - or (len(state) == 0) - or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) - ): - raise_error( - TypeError, - f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", - ) - - if isinstance(check_purity, bool) is False: - raise_error( - TypeError, - f"check_purity must be type bool, but it is type {type(check_purity)}.", - ) - - nqubits = int(np.log2(state.shape[0])) - - if check_purity is True: - purity_total_system = purity(state) - - mixed = bool(abs(purity_total_system - 1.0) > PRECISION_TOL) - if mixed is True: - raise_error( - NotImplementedError, - "concurrence only implemented for pure quantum states.", - ) - - reduced_density_matrix = ( - backend.partial_trace(state, bipartition, nqubits) - if len(state.shape) == 1 - else backend.partial_trace_density_matrix(state, bipartition, nqubits) - ) - - purity_reduced = purity(reduced_density_matrix) - if purity_reduced - 1.0 > 0.0: - purity_reduced = round(purity_reduced, 7) - - concur = np.sqrt(2 * (1 - purity_reduced)) - - return concur - - -def entanglement_of_formation( - state, bipartition, base: float = 2, check_purity: bool = True, backend=None -): - """Calculates the entanglement of formation :math:`E_{f}` of a pure bipartite - quantum state :math:`\\rho`, which is given by - - .. math:: - E_{f} = H([1 - x, x]) \\, , - - where - - .. math:: - x = \\frac{1 + \\sqrt{1 - C^{2}(\\rho)}}{2} \\, , - - :math:`C(\\rho)` is the :func:`qibo.quantum_info.concurrence` of :math:`\\rho`, - and :math:`H` is the :func:`qibo.quantum_info.shannon_entropy`. - - Args: - state (ndarray): statevector or density matrix. - bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. - base (float): the base of the log in :func:`qibo.quantum_info.shannon_entropy`. - Defaults to :math:`2`. - check_purity (bool, optional): if ``True``, checks if ``state`` is pure. If ``False``, - it assumes ``state`` is pure . Default: ``True``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - - Returns: - float: entanglement of formation of state :math:`\\rho`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - from qibo.quantum_info.utils import shannon_entropy # pylint: disable=C0415 - - concur = concurrence( - state, bipartition=bipartition, check_purity=check_purity, backend=backend - ) - concur = (1 + np.sqrt(1 - concur**2)) / 2 - probabilities = [1 - concur, concur] - - ent_of_form = shannon_entropy(probabilities, base=base, backend=backend) - - return ent_of_form - - -def entropy( - state, - base: float = 2, - check_hermitian: bool = False, - return_spectrum: bool = False, - backend=None, -): - """The von-Neumann entropy :math:`S(\\rho)` of a quantum ``state`` :math:`\\rho`, which - is given by - - .. math:: - S(\\rho) = - \\text{tr}\\left[\\rho \\, \\log(\\rho)\\right] - - Args: - state (ndarray): statevector or density matrix. - base (float, optional): the base of the log. Defaults to :math:`2`. - check_hermitian (bool, optional): if ``True``, checks if ``state`` is Hermitian. - If ``False``, it assumes ``state`` is Hermitian . - Defaults to ``False``. - return_spectrum: if ``True``, returns ``entropy`` and - :math:`-\\log_{\\textup{b}}(\\textup{eigenvalues})`, where :math:`b` is ``base``. - If ``False``, returns only ``entropy``. Default is ``False``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses - :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. - - Returns: - float: The von-Neumann entropy :math:`S` of ``state`` :math:`\\rho`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if ( - (len(state.shape) >= 3) - or (len(state) == 0) - or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) - ): - raise_error( - TypeError, - f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", - ) - - if base <= 0.0: - raise_error(ValueError, "log base must be non-negative.") - - if isinstance(check_hermitian, bool) is False: - raise_error( - TypeError, - f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", - ) - - if purity(state) == 1.0: - if return_spectrum: - return 0.0, backend.cast([1.0], dtype=float) - - return 0.0 - - if check_hermitian is False or _check_hermitian_or_not_gpu(state, backend=backend): - eigenvalues = np.linalg.eigvalsh(state) - else: - eigenvalues = np.linalg.eigvals(state) - - if base == 2: - log_prob = np.where(eigenvalues > 0, np.log2(eigenvalues), 0.0) - elif base == 10: - log_prob = np.where(eigenvalues > 0, np.log10(eigenvalues), 0.0) - elif base == np.e: - log_prob = np.where(eigenvalues > 0, np.log(eigenvalues), 0.0) - else: - log_prob = np.where(eigenvalues > 0, np.log(eigenvalues) / np.log(base), 0.0) - - ent = -np.sum(eigenvalues * log_prob) - # absolute value if entropy == 0.0 to avoid returning -0.0 - ent = np.abs(ent) if ent == 0.0 else ent - - ent = float(ent) - - if return_spectrum: - log_prob = backend.cast(log_prob, dtype=log_prob.dtype) - return ent, -log_prob - - return ent - - -def entanglement_entropy( - state, - bipartition, - base: float = 2, - check_hermitian: bool = False, - return_spectrum: bool = False, - backend=None, -): - """Calculates the entanglement entropy :math:`S` of bipartition :math:`A` - of ``state`` :math:`\\rho`. This is given by - - .. math:: - S(\\rho_{A}) = -\\text{tr}(\\rho_{A} \\, \\log(\\rho_{A})) \\, , - - where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density matrix calculated - by tracing out the ``bipartition`` :math:`B`. - - Args: - state (ndarray): statevector or density matrix. - bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. - base (float, optional): the base of the log. Defaults to :math: `2`. - check_hermitian (bool, optional): if ``True``, checks if :math:`\\rho_{A}` is Hermitian. - If ``False``, it assumes ``state`` is Hermitian . Default: ``False``. - return_spectrum: if ``True``, returns ``entropy`` and eigenvalues of ``state``. - If ``False``, returns only ``entropy``. Default is ``False``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses - :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. - - Returns: - float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if base <= 0.0: - raise_error(ValueError, "log base must be non-negative.") - - if ( - (len(state.shape) not in [1, 2]) - or (len(state) == 0) - or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) - ): - raise_error( - TypeError, - f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", - ) - - nqubits = int(np.log2(state.shape[0])) - - reduced_density_matrix = ( - backend.partial_trace(state, bipartition, nqubits) - if len(state.shape) == 1 - else backend.partial_trace_density_matrix(state, bipartition, nqubits) - ) - - entropy_entanglement = entropy( - reduced_density_matrix, - base=base, - check_hermitian=check_hermitian, - return_spectrum=return_spectrum, - backend=backend, - ) - - return entropy_entanglement - - def trace_distance(state, target, check_hermitian: bool = False, backend=None): """Trace distance between two quantum states, :math:`\\rho` and :math:`\\sigma`: @@ -634,84 +367,6 @@ def bures_distance(state, target, check_hermitian: bool = False, backend=None): return distance -def entanglement_fidelity( - channel, nqubits: int, state=None, check_hermitian: bool = False, backend=None -): - """Entanglement fidelity :math:`F_{\\mathcal{E}}` of a ``channel`` :math:`\\mathcal{E}` - on ``state`` :math:`\\rho` is given by - - .. math:: - F_{\\mathcal{E}}(\\rho) = F(\\rho_{f}, \\rho) - - where :math:`F` is the :func:`qibo.quantum_info.fidelity` function for states, - and :math:`\\rho_{f} = \\mathcal{E}_{A} \\otimes I_{B}(\\rho)` - is the state after the channel :math:`\\mathcal{E}` was applied to - partition :math:`A`. - - Args: - channel (:class:`qibo.gates.channels.Channel`): quantum channel - acting on partition :math:`A`. - nqubits (int): total number of qubits in ``state``. - state (ndarray, optional): statevector or density matrix to be evolved - by ``channel``. If ``None``, defaults to the maximally entangled state - :math:`\\frac{1}{2^{n}} \\, \\sum_{k} \\, \\ket{k}\\ket{k}`, where - :math:`n` is ``nqubits``. Defaults to ``None``. - check_hermitian (bool, optional): if ``True``, checks if the final state - :math:`\\rho_{f}` is Hermitian. If ``False``, it assumes it is Hermitian. - Defaults to ``False``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - Returns: - float: Entanglement fidelity :math:`F_{\\mathcal{E}}`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if isinstance(nqubits, int) is False: - raise_error( - TypeError, f"nqubits must be type int, but it is type {type(nqubits)}." - ) - - if nqubits <= 0: - raise_error( - ValueError, f"nqubits must be a positive integer, but it is {nqubits}." - ) - - if state is not None and ( - (len(state.shape) not in [1, 2]) - or (len(state) == 0) - or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) - ): - raise_error( - TypeError, - f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", - ) - - if isinstance(check_hermitian, bool) is False: - raise_error( - TypeError, - f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", - ) - - if state is None: - state = backend.plus_density_matrix(nqubits) - - # necessary because this function do support repeated execution, - # so it has to default to density matrices - if len(state.shape) == 1: - state = np.outer(state, np.conj(state)) - - state_final = backend.apply_channel_density_matrix(channel, state, nqubits) - - entang_fidelity = fidelity( - state_final, state, check_hermitian=check_hermitian, backend=backend - ) - - return entang_fidelity - - def process_fidelity(channel, target=None, check_unitary: bool = False, backend=None): """Process fidelity between a quantum ``channel`` :math:`\\mathcal{E}` and a ``target`` unitary channel :math:`U`. The process fidelity is defined as @@ -1008,103 +663,6 @@ def diamond_norm(channel, target=None, backend=None, **kwargs): return solution -def meyer_wallach_entanglement(circuit, backend=None): - """Computes the Meyer-Wallach entanglement Q of the `circuit`, - - .. math:: - Q(\\theta) = 1 - \\frac{1}{N} \\, \\sum_{k} \\, - \\text{tr}\\left(\\rho_{k^{2}}(\\theta)\\right) \\, . - - Args: - circuit (:class:`qibo.models.Circuit`): Parametrized circuit. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - Returns: - float: Meyer-Wallach entanglement. - """ - - if backend is None: # pragma: no cover - backend = GlobalBackend() - - circuit.density_matrix = True - nqubits = circuit.nqubits - - rho = backend.execute_circuit(circuit).state() - - ent = 0 - for j in range(nqubits): - trace_q = list(range(nqubits)) - trace_q.pop(j) - - rho_r = backend.partial_trace_density_matrix(rho, trace_q, nqubits) - - trace = purity(rho_r) - - ent += trace - - entanglement = 1 - ent / nqubits - - return entanglement - - -def entangling_capability(circuit, samples: int, seed=None, backend=None): - """Returns the entangling capability :math:`\\text{Ent}` of a parametrized - circuit, which is average Meyer-Wallach entanglement Q of the circuit, i.e. - - .. math:: - \\text{Ent} = \\frac{2}{S}\\sum_{k}Q_k \\, , - - where :math:`S` is the number of samples. - - Args: - circuit (:class:`qibo.models.Circuit`): Parametrized circuit. - samples (int): number of samples to estimate the integral. - seed (int or :class:`numpy.random.Generator`, optional): Either a generator of random - numbers or a fixed seed to initialize a generator. If ``None``, initializes - a generator with a random seed. Default: ``None``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - Returns: - float: Entangling capability. - """ - - if isinstance(samples, int) is False: - raise_error( - TypeError, f"samples must be type int, but it is type {type(samples)}." - ) - - if ( - seed is not None - and not isinstance(seed, int) - and not isinstance(seed, np.random.Generator) - ): - raise_error( - TypeError, "seed must be either type int or numpy.random.Generator." - ) - - if backend is None: # pragma: no cover - backend = GlobalBackend() - - local_state = ( - np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed - ) - - res = [] - for _ in range(samples): - params = local_state.uniform(-np.pi, np.pi, circuit.trainable_gates.nparams) - circuit.set_parameters(params) - entanglement = meyer_wallach_entanglement(circuit, backend=backend) - res.append(entanglement) - - capability = 2 * np.real(np.sum(res)) / samples - - return capability - - def expressibility( circuit, power_t: int, From a34e4cca4c7a73d914d09e34e2668531697ab1ca Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 08:59:29 +0400 Subject: [PATCH 053/200] split tests --- tests/test_quantum_info_entanglement.py | 175 ++++++++++++++ tests/test_quantum_info_entropies.py | 130 +++++++++++ tests/test_quantum_info_metrics.py | 294 ------------------------ 3 files changed, 305 insertions(+), 294 deletions(-) create mode 100644 tests/test_quantum_info_entanglement.py create mode 100644 tests/test_quantum_info_entropies.py diff --git a/tests/test_quantum_info_entanglement.py b/tests/test_quantum_info_entanglement.py new file mode 100644 index 0000000000..a98cf1909b --- /dev/null +++ b/tests/test_quantum_info_entanglement.py @@ -0,0 +1,175 @@ +import numpy as np +import pytest + +from qibo import Circuit, gates +from qibo.config import PRECISION_TOL +from qibo.quantum_info.entanglement import ( + concurrence, + entanglement_fidelity, + entanglement_of_formation, + entangling_capability, + meyer_wallach_entanglement, +) +from qibo.quantum_info.random_ensembles import random_density_matrix, random_statevector + + +@pytest.mark.parametrize("check_purity", [True, False]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("bipartition", [[0], [1]]) +def test_concurrence_and_formation(backend, bipartition, base, check_purity): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = concurrence( + state, bipartition=bipartition, check_purity=check_purity, backend=backend + ) + with pytest.raises(TypeError): + state = random_statevector(4, backend=backend) + test = concurrence( + state, bipartition=bipartition, check_purity="True", backend=backend + ) + + if check_purity is True: + with pytest.raises(NotImplementedError): + state = backend.identity_density_matrix(2, normalize=False) + test = concurrence(state, bipartition=bipartition, backend=backend) + + nqubits = 2 + dim = 2**nqubits + state = random_statevector(dim, backend=backend) + concur = concurrence( + state, bipartition=bipartition, check_purity=check_purity, backend=backend + ) + ent_form = entanglement_of_formation( + state, + bipartition=bipartition, + base=base, + check_purity=check_purity, + backend=backend, + ) + backend.assert_allclose(0.0 <= concur <= np.sqrt(2), True) + backend.assert_allclose(0.0 <= ent_form <= 1.0, True) + + state = np.kron( + random_density_matrix(2, pure=True, backend=backend), + random_density_matrix(2, pure=True, backend=backend), + ) + concur = concurrence(state, bipartition, check_purity=check_purity, backend=backend) + ent_form = entanglement_of_formation( + state, + bipartition=bipartition, + base=base, + check_purity=check_purity, + backend=backend, + ) + backend.assert_allclose(concur, 0.0, atol=10 * PRECISION_TOL) + backend.assert_allclose(ent_form, 0.0, atol=PRECISION_TOL) + + +@pytest.mark.parametrize("check_hermitian", [False, True]) +@pytest.mark.parametrize("nqubits", [4, 6]) +@pytest.mark.parametrize("channel", [gates.DepolarizingChannel]) +def test_entanglement_fidelity(backend, channel, nqubits, check_hermitian): + with pytest.raises(TypeError): + test = entanglement_fidelity( + channel, nqubits=[0], check_hermitian=check_hermitian, backend=backend + ) + with pytest.raises(ValueError): + test = entanglement_fidelity( + channel, nqubits=0, check_hermitian=check_hermitian, backend=backend + ) + with pytest.raises(TypeError): + state = np.random.rand(2, 3, 2) + state = backend.cast(state, dtype=state.dtype) + test = entanglement_fidelity( + channel, + nqubits, + state=state, + check_hermitian=check_hermitian, + backend=backend, + ) + with pytest.raises(TypeError): + state = random_statevector(2, backend=backend) + test = entanglement_fidelity( + channel, nqubits, state=state, check_hermitian="False", backend=backend + ) + + channel = channel([0, 1], 0.5) + + # test on maximally entangled state + ent_fid = entanglement_fidelity( + channel, nqubits=nqubits, check_hermitian=check_hermitian, backend=backend + ) + backend.assert_allclose(ent_fid, 0.625, atol=PRECISION_TOL) + + # test with a state vector + state = backend.plus_state(nqubits) + ent_fid = entanglement_fidelity( + channel, + nqubits=nqubits, + state=state, + check_hermitian=check_hermitian, + backend=backend, + ) + backend.assert_allclose(ent_fid, 0.625, atol=PRECISION_TOL) + + # test on maximally mixed state + state = backend.identity_density_matrix(nqubits) + ent_fid = entanglement_fidelity( + channel, + nqubits=nqubits, + state=state, + check_hermitian=check_hermitian, + backend=backend, + ) + backend.assert_allclose(ent_fid, 1.0, atol=PRECISION_TOL) + + +def test_meyer_wallach_entanglement(backend): + nqubits = 2 + + circuit1 = Circuit(nqubits) + circuit1.add([gates.RX(0, np.pi / 4)] for _ in range(nqubits)) + + circuit2 = Circuit(nqubits) + circuit2.add([gates.RX(0, np.pi / 4)] for _ in range(nqubits)) + circuit2.add(gates.CNOT(0, 1)) + + backend.assert_allclose( + meyer_wallach_entanglement(circuit1, backend=backend), 0.0, atol=PRECISION_TOL + ) + + backend.assert_allclose( + meyer_wallach_entanglement(circuit2, backend=backend), 0.5, atol=PRECISION_TOL + ) + + +@pytest.mark.parametrize("seed", [None, 10, np.random.default_rng(10)]) +def test_entangling_capability(backend, seed): + with pytest.raises(TypeError): + circuit = Circuit(1) + samples = 0.5 + entangling_capability(circuit, samples, seed=seed, backend=backend) + with pytest.raises(TypeError): + circuit = Circuit(1) + entangling_capability(circuit, samples=10, seed="10", backend=backend) + + nqubits = 2 + samples = 100 + + c1 = Circuit(nqubits) + c1.add([gates.RX(q, 0, trainable=True) for q in range(nqubits)]) + c1.add(gates.CNOT(0, 1)) + c1.add([gates.RX(q, 0, trainable=True) for q in range(nqubits)]) + ent_mw1 = entangling_capability(c1, samples, seed=seed, backend=backend) + + c2 = Circuit(nqubits) + c2.add(gates.H(0)) + c2.add(gates.CNOT(0, 1)) + c2.add(gates.RX(0, 0, trainable=True)) + ent_mw2 = entangling_capability(c2, samples, seed=seed, backend=backend) + + c3 = Circuit(nqubits) + ent_mw3 = entangling_capability(c3, samples, seed=seed, backend=backend) + + backend.assert_allclose(ent_mw3 < ent_mw1 < ent_mw2, True) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py new file mode 100644 index 0000000000..774ec11fcd --- /dev/null +++ b/tests/test_quantum_info_entropies.py @@ -0,0 +1,130 @@ +import numpy as np +import pytest + +from qibo.config import PRECISION_TOL +from qibo.quantum_info.entropies import entanglement_entropy, entropy +from qibo.quantum_info.random_ensembles import random_statevector, random_unitary + + +@pytest.mark.parametrize("check_hermitian", [False, True]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +def test_entropy(backend, base, check_hermitian): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = entropy( + state, base=base, check_hermitian=check_hermitian, backend=backend + ) + with pytest.raises(ValueError): + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + test = entropy(state, base=0, check_hermitian=check_hermitian, backend=backend) + with pytest.raises(TypeError): + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + test = entropy(state, base=base, check_hermitian="False", backend=backend) + + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + with pytest.raises(NotImplementedError): + state = random_unitary(4, backend=backend) + test = entropy(state, base=base, check_hermitian=True, backend=backend) + else: + state = random_unitary(4, backend=backend) + test = entropy(state, base=base, check_hermitian=True, backend=backend) + + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + backend.assert_allclose(entropy(state, backend=backend), 0.0, atol=PRECISION_TOL) + + state = np.array([1.0, 0.0, 0.0, 0.0]) + state = np.outer(state, state) + state = backend.cast(state, dtype=state.dtype) + + nqubits = 2 + state = backend.identity_density_matrix(nqubits) + if base == 2: + test = 2.0 + elif base == 10: + test = 0.6020599913279624 + elif base == np.e: + test = 1.3862943611198906 + else: + test = 0.8613531161467861 + + backend.assert_allclose( + entropy(state, base, check_hermitian=check_hermitian, backend=backend), test + ) + + +@pytest.mark.parametrize("check_hermitian", [False, True]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("bipartition", [[0], [1]]) +def test_entanglement_entropy(backend, bipartition, base, check_hermitian): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + with pytest.raises(ValueError): + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=0, + check_hermitian=check_hermitian, + backend=backend, + ) + if backend.__class__.__name__ == "CupyBackend": + with pytest.raises(NotImplementedError): + state = random_unitary(4, backend=backend) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=True, + backend=backend, + ) + + # Bell state + state = np.array([1.0, 0.0, 0.0, 1.0]) / np.sqrt(2) + state = backend.cast(state, dtype=state.dtype) + + entang_entrop = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + + if base == 2: + test = 1.0 + elif base == 10: + test = 0.30102999566398125 + elif base == np.e: + test = 0.6931471805599454 + else: + test = 0.4306765580733931 + + backend.assert_allclose(entang_entrop, test, atol=PRECISION_TOL) + + # Product state + state = np.kron( + random_statevector(2, backend=backend), random_statevector(2, backend=backend) + ) + + entang_entrop = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + + backend.assert_allclose(entang_entrop, 0.0, atol=PRECISION_TOL) diff --git a/tests/test_quantum_info_metrics.py b/tests/test_quantum_info_metrics.py index 0e7b86f21b..793bb510a5 100644 --- a/tests/test_quantum_info_metrics.py +++ b/tests/test_quantum_info_metrics.py @@ -7,13 +7,7 @@ average_gate_fidelity, bures_angle, bures_distance, - concurrence, diamond_norm, - entanglement_entropy, - entanglement_fidelity, - entanglement_of_formation, - entangling_capability, - entropy, expressibility, fidelity, frame_potential, @@ -21,7 +15,6 @@ hilbert_schmidt_distance, impurity, infidelity, - meyer_wallach_entanglement, process_fidelity, process_infidelity, purity, @@ -30,7 +23,6 @@ from qibo.quantum_info.random_ensembles import ( random_density_matrix, random_hermitian, - random_statevector, random_unitary, ) from qibo.quantum_info.superoperator_transformations import to_choi @@ -59,183 +51,6 @@ def test_purity_and_impurity(backend): backend.assert_allclose(impurity(state), 1.0 - 1.0 / dim, atol=PRECISION_TOL) -@pytest.mark.parametrize("check_purity", [True, False]) -@pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("bipartition", [[0], [1]]) -def test_concurrence_and_formation(backend, bipartition, base, check_purity): - with pytest.raises(TypeError): - state = np.random.rand(2, 3) - state = backend.cast(state, dtype=state.dtype) - test = concurrence( - state, bipartition=bipartition, check_purity=check_purity, backend=backend - ) - with pytest.raises(TypeError): - state = random_statevector(4, backend=backend) - test = concurrence( - state, bipartition=bipartition, check_purity="True", backend=backend - ) - - if check_purity is True: - with pytest.raises(NotImplementedError): - state = backend.identity_density_matrix(2, normalize=False) - test = concurrence(state, bipartition=bipartition, backend=backend) - - nqubits = 2 - dim = 2**nqubits - state = random_statevector(dim, backend=backend) - concur = concurrence( - state, bipartition=bipartition, check_purity=check_purity, backend=backend - ) - ent_form = entanglement_of_formation( - state, - bipartition=bipartition, - base=base, - check_purity=check_purity, - backend=backend, - ) - backend.assert_allclose(0.0 <= concur <= np.sqrt(2), True) - backend.assert_allclose(0.0 <= ent_form <= 1.0, True) - - state = np.kron( - random_density_matrix(2, pure=True, backend=backend), - random_density_matrix(2, pure=True, backend=backend), - ) - concur = concurrence(state, bipartition, check_purity=check_purity, backend=backend) - ent_form = entanglement_of_formation( - state, - bipartition=bipartition, - base=base, - check_purity=check_purity, - backend=backend, - ) - backend.assert_allclose(concur, 0.0, atol=10 * PRECISION_TOL) - backend.assert_allclose(ent_form, 0.0, atol=PRECISION_TOL) - - -@pytest.mark.parametrize("check_hermitian", [False, True]) -@pytest.mark.parametrize("base", [2, 10, np.e, 5]) -def test_entropy(backend, base, check_hermitian): - with pytest.raises(TypeError): - state = np.random.rand(2, 3) - state = backend.cast(state, dtype=state.dtype) - test = entropy( - state, base=base, check_hermitian=check_hermitian, backend=backend - ) - with pytest.raises(ValueError): - state = np.array([1.0, 0.0]) - state = backend.cast(state, dtype=state.dtype) - test = entropy(state, base=0, check_hermitian=check_hermitian, backend=backend) - with pytest.raises(TypeError): - state = np.array([1.0, 0.0]) - state = backend.cast(state, dtype=state.dtype) - test = entropy(state, base=base, check_hermitian="False", backend=backend) - - if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: - with pytest.raises(NotImplementedError): - state = random_unitary(4, backend=backend) - test = entropy(state, base=base, check_hermitian=True, backend=backend) - else: - state = random_unitary(4, backend=backend) - test = entropy(state, base=base, check_hermitian=True, backend=backend) - - state = np.array([1.0, 0.0]) - state = backend.cast(state, dtype=state.dtype) - backend.assert_allclose(entropy(state, backend=backend), 0.0, atol=PRECISION_TOL) - - state = np.array([1.0, 0.0, 0.0, 0.0]) - state = np.outer(state, state) - state = backend.cast(state, dtype=state.dtype) - - nqubits = 2 - state = backend.identity_density_matrix(nqubits) - if base == 2: - test = 2.0 - elif base == 10: - test = 0.6020599913279624 - elif base == np.e: - test = 1.3862943611198906 - else: - test = 0.8613531161467861 - - backend.assert_allclose( - entropy(state, base, check_hermitian=check_hermitian, backend=backend), test - ) - - -@pytest.mark.parametrize("check_hermitian", [False, True]) -@pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("bipartition", [[0], [1]]) -def test_entanglement_entropy(backend, bipartition, base, check_hermitian): - with pytest.raises(TypeError): - state = np.random.rand(2, 3) - state = backend.cast(state, dtype=state.dtype) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, - ) - with pytest.raises(ValueError): - state = np.array([1.0, 0.0]) - state = backend.cast(state, dtype=state.dtype) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=0, - check_hermitian=check_hermitian, - backend=backend, - ) - if backend.__class__.__name__ == "CupyBackend": - with pytest.raises(NotImplementedError): - state = random_unitary(4, backend=backend) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=True, - backend=backend, - ) - - # Bell state - state = np.array([1.0, 0.0, 0.0, 1.0]) / np.sqrt(2) - state = backend.cast(state, dtype=state.dtype) - - entang_entrop = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, - ) - - if base == 2: - test = 1.0 - elif base == 10: - test = 0.30102999566398125 - elif base == np.e: - test = 0.6931471805599454 - else: - test = 0.4306765580733931 - - backend.assert_allclose(entang_entrop, test, atol=PRECISION_TOL) - - # Product state - state = np.kron( - random_statevector(2, backend=backend), random_statevector(2, backend=backend) - ) - - entang_entrop = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, - ) - - backend.assert_allclose(entang_entrop, 0.0, atol=PRECISION_TOL) - - @pytest.mark.parametrize("check_hermitian", [False, True]) def test_trace_distance(backend, check_hermitian): with pytest.raises(TypeError): @@ -445,65 +260,6 @@ def test_fidelity_and_infidelity_and_bures(backend, check_hermitian): test = fidelity(state, target, check_hermitian=True, backend=backend) -@pytest.mark.parametrize("check_hermitian", [False, True]) -@pytest.mark.parametrize("nqubits", [4, 6]) -@pytest.mark.parametrize("channel", [gates.DepolarizingChannel]) -def test_entanglement_fidelity(backend, channel, nqubits, check_hermitian): - with pytest.raises(TypeError): - test = entanglement_fidelity( - channel, nqubits=[0], check_hermitian=check_hermitian, backend=backend - ) - with pytest.raises(ValueError): - test = entanglement_fidelity( - channel, nqubits=0, check_hermitian=check_hermitian, backend=backend - ) - with pytest.raises(TypeError): - state = np.random.rand(2, 3, 2) - state = backend.cast(state, dtype=state.dtype) - test = entanglement_fidelity( - channel, - nqubits, - state=state, - check_hermitian=check_hermitian, - backend=backend, - ) - with pytest.raises(TypeError): - state = random_statevector(2, backend=backend) - test = entanglement_fidelity( - channel, nqubits, state=state, check_hermitian="False", backend=backend - ) - - channel = channel([0, 1], 0.5) - - # test on maximally entangled state - ent_fid = entanglement_fidelity( - channel, nqubits=nqubits, check_hermitian=check_hermitian, backend=backend - ) - backend.assert_allclose(ent_fid, 0.625, atol=PRECISION_TOL) - - # test with a state vector - state = backend.plus_state(nqubits) - ent_fid = entanglement_fidelity( - channel, - nqubits=nqubits, - state=state, - check_hermitian=check_hermitian, - backend=backend, - ) - backend.assert_allclose(ent_fid, 0.625, atol=PRECISION_TOL) - - # test on maximally mixed state - state = backend.identity_density_matrix(nqubits) - ent_fid = entanglement_fidelity( - channel, - nqubits=nqubits, - state=state, - check_hermitian=check_hermitian, - backend=backend, - ) - backend.assert_allclose(ent_fid, 1.0, atol=PRECISION_TOL) - - def test_process_fidelity_and_infidelity(backend): d = 2 with pytest.raises(TypeError): @@ -572,56 +328,6 @@ def test_diamond_norm(backend, nqubits): backend.assert_allclose(dnorm, 0.0, atol=PRECISION_TOL) -def test_meyer_wallach_entanglement(backend): - nqubits = 2 - - circuit1 = Circuit(nqubits) - circuit1.add([gates.RX(0, np.pi / 4)] for _ in range(nqubits)) - - circuit2 = Circuit(nqubits) - circuit2.add([gates.RX(0, np.pi / 4)] for _ in range(nqubits)) - circuit2.add(gates.CNOT(0, 1)) - - backend.assert_allclose( - meyer_wallach_entanglement(circuit1, backend=backend), 0.0, atol=PRECISION_TOL - ) - - backend.assert_allclose( - meyer_wallach_entanglement(circuit2, backend=backend), 0.5, atol=PRECISION_TOL - ) - - -@pytest.mark.parametrize("seed", [None, 10, np.random.default_rng(10)]) -def test_entangling_capability(backend, seed): - with pytest.raises(TypeError): - circuit = Circuit(1) - samples = 0.5 - entangling_capability(circuit, samples, seed=seed, backend=backend) - with pytest.raises(TypeError): - circuit = Circuit(1) - entangling_capability(circuit, samples=10, seed="10", backend=backend) - - nqubits = 2 - samples = 100 - - c1 = Circuit(nqubits) - c1.add([gates.RX(q, 0, trainable=True) for q in range(nqubits)]) - c1.add(gates.CNOT(0, 1)) - c1.add([gates.RX(q, 0, trainable=True) for q in range(nqubits)]) - ent_mw1 = entangling_capability(c1, samples, seed=seed, backend=backend) - - c2 = Circuit(nqubits) - c2.add(gates.H(0)) - c2.add(gates.CNOT(0, 1)) - c2.add(gates.RX(0, 0, trainable=True)) - ent_mw2 = entangling_capability(c2, samples, seed=seed, backend=backend) - - c3 = Circuit(nqubits) - ent_mw3 = entangling_capability(c3, samples, seed=seed, backend=backend) - - backend.assert_allclose(ent_mw3 < ent_mw1 < ent_mw2, True) - - def test_expressibility(backend): with pytest.raises(TypeError): circuit = Circuit(1) From ed89806d818edfd2c961cfb2193b71c05d34206c Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 09:06:59 +0400 Subject: [PATCH 054/200] split api reference --- doc/source/api-reference/qibo.rst | 102 +++++++++++++++++------------- 1 file changed, 57 insertions(+), 45 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 2f8e7d9d92..deb571878e 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1489,35 +1489,11 @@ The destabilizers can be extracted analogously with :meth:`qibo.quantum_info.cli :member-order: bysource -Metrics -^^^^^^^ -Set of functions that are used to calculate metrics of states, (pseudo-)distance measures -between states, and distance measures between quantum channels. - -Purity -"""""" - -.. autofunction:: qibo.quantum_info.purity - - -Impurity -"""""""" - -.. autofunction:: qibo.quantum_info.impurity - - -Concurrence -""""""""""" - -.. autofunction:: qibo.quantum_info.concurrence - - -Entanglement of formation -""""""""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.entanglement_of_formation +Entropy measures +^^^^^^^^^^^^^^^^ +Set of functions to calculate entropy measures. Entropy """"""" @@ -1547,6 +1523,60 @@ Entanglement entropy when using `cupy` backend. +Entanglement measures +^^^^^^^^^^^^^^^^^^^^^ + +Set of functions to calculate entanglement measures. + + +Concurrence +""""""""""" + +.. autofunction:: qibo.quantum_info.concurrence + + +Entanglement of formation +""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.entanglement_of_formation + + +Entanglement fidelity +""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.entanglement_fidelity + + +Meyer-Wallach entanglement +"""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.meyer_wallach_entanglement + + +Entanglement capability +""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.entangling_capability + + +Metrics +^^^^^^^ + +Set of functions that are used to calculate metrics of states, (pseudo-)distance measures +between states, and distance measures between quantum channels. + +Purity +"""""" + +.. autofunction:: qibo.quantum_info.purity + + +Impurity +"""""""" + +.. autofunction:: qibo.quantum_info.impurity + + Trace distance """""""""""""" @@ -1591,12 +1621,6 @@ Bures distance .. autofunction:: qibo.quantum_info.bures_distance -Entanglement fidelity -""""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.entanglement_fidelity - - Process fidelity """""""""""""""" @@ -1627,18 +1651,6 @@ Diamond Norm .. autofunction:: qibo.quantum_info.diamond_norm -Meyer-Wallach entanglement -"""""""""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.meyer_wallach_entanglement - - -Entanglement capability -""""""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.entangling_capability - - Expressibility of parameterized quantum circuits """""""""""""""""""""""""""""""""""""""""""""""" From 5991f6216edb4fce228fcb4433647f5be56f1b10 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 09:15:33 +0400 Subject: [PATCH 055/200] fix import --- src/qibo/callbacks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/callbacks.py b/src/qibo/callbacks.py index 16d88d712a..34026bc930 100644 --- a/src/qibo/callbacks.py +++ b/src/qibo/callbacks.py @@ -125,7 +125,7 @@ def nqubits(self, n: int): ] def apply(self, backend, state): - from qibo.quantum_info.metrics import entanglement_entropy + from qibo.quantum_info.entanglement import entanglement_entropy entropy, spectrum = entanglement_entropy( state, From 8994079ddf28f6d40e52c7f84f90044f22e1e4ce Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 09:15:44 +0400 Subject: [PATCH 056/200] update `__init__.py` --- src/qibo/quantum_info/__init__.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/qibo/quantum_info/__init__.py b/src/qibo/quantum_info/__init__.py index 640fdb3e13..73124d82a1 100644 --- a/src/qibo/quantum_info/__init__.py +++ b/src/qibo/quantum_info/__init__.py @@ -1,5 +1,7 @@ from qibo.quantum_info.basis import * from qibo.quantum_info.clifford import * +from qibo.quantum_info.entanglement import * +from qibo.quantum_info.entropies import * from qibo.quantum_info.metrics import * from qibo.quantum_info.random_ensembles import * from qibo.quantum_info.superoperator_transformations import * From 68967d9f3a255d281c71d5277b4dd7c8dc076f08 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 28 Jan 2024 09:19:21 +0400 Subject: [PATCH 057/200] fix import --- src/qibo/callbacks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/callbacks.py b/src/qibo/callbacks.py index 34026bc930..77114ed42a 100644 --- a/src/qibo/callbacks.py +++ b/src/qibo/callbacks.py @@ -125,7 +125,7 @@ def nqubits(self, n: int): ] def apply(self, backend, state): - from qibo.quantum_info.entanglement import entanglement_entropy + from qibo.quantum_info.entropies import entanglement_entropy entropy, spectrum = entanglement_entropy( state, From cbeb4e6eb5cf6de55941639025523b02390fa53c Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 09:34:47 +0400 Subject: [PATCH 058/200] `shannon_entropy` from `utils` to `entropies` --- doc/source/api-reference/qibo.rst | 80 +++++++++++++-------------- src/qibo/quantum_info/entanglement.py | 6 +- src/qibo/quantum_info/entropies.py | 68 ++++++++++++++++++++++- src/qibo/quantum_info/utils.py | 66 ---------------------- tests/test_quantum_info_entropies.py | 42 +++++++++++++- tests/test_quantum_info_utils.py | 41 -------------- 6 files changed, 151 insertions(+), 152 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index deb571878e..efe2a4ef08 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1489,40 +1489,6 @@ The destabilizers can be extracted analogously with :meth:`qibo.quantum_info.cli :member-order: bysource - -Entropy measures -^^^^^^^^^^^^^^^^ - -Set of functions to calculate entropy measures. - -Entropy -""""""" - -.. autofunction:: qibo.quantum_info.entropy - -.. note:: - ``validate`` flag allows the user to choose if the function will check if input - ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the - assumption of Hermiticity, because it is faster and, more importantly, - the functions are intended to be used on Hermitian inputs. When ``validate=True`` - and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. - - -Entanglement entropy -"""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.entanglement_entropy - -.. note:: - ``validate`` flag allows the user to choose if the function will check if - the reduced density matrix resulting from tracing out ``bipartition`` from input - ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the - assumption of Hermiticity, because it is faster and, more importantly, - the functions are intended to be used on Hermitian inputs. When ``validate=True`` - and the reduced density matrix is non-Hermitian, an error will be raised - when using `cupy` backend. - - Entanglement measures ^^^^^^^^^^^^^^^^^^^^^ @@ -1559,6 +1525,46 @@ Entanglement capability .. autofunction:: qibo.quantum_info.entangling_capability +Entropy measures +^^^^^^^^^^^^^^^^ + +Set of functions to calculate entropy measures. + + +Shannon entropy +""""""""""""""" + +.. autofunction:: qibo.quantum_info.shannon_entropy + + +Entropy +""""""" + +.. autofunction:: qibo.quantum_info.entropy + +.. note:: + ``validate`` flag allows the user to choose if the function will check if input + ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + assumption of Hermiticity, because it is faster and, more importantly, + the functions are intended to be used on Hermitian inputs. When ``validate=True`` + and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. + + +Entanglement Entropy +"""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.entanglement_entropy + +.. note:: + ``validate`` flag allows the user to choose if the function will check if + the reduced density matrix resulting from tracing out ``bipartition`` from input + ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + assumption of Hermiticity, because it is faster and, more importantly, + the functions are intended to be used on Hermitian inputs. When ``validate=True`` + and the reduced density matrix is non-Hermitian, an error will be raised + when using `cupy` backend. + + Metrics ^^^^^^^ @@ -2047,12 +2053,6 @@ Hadamard Transform .. autofunction:: qibo.quantum_info.hadamard_transform -Shannon entropy -""""""""""""""" - -.. autofunction:: qibo.quantum_info.shannon_entropy - - Hellinger distance """""""""""""""""" diff --git a/src/qibo/quantum_info/entanglement.py b/src/qibo/quantum_info/entanglement.py index 7f006655d6..c2f6eda3f0 100644 --- a/src/qibo/quantum_info/entanglement.py +++ b/src/qibo/quantum_info/entanglement.py @@ -90,12 +90,12 @@ def entanglement_of_formation( x = \\frac{1 + \\sqrt{1 - C^{2}(\\rho)}}{2} \\, , :math:`C(\\rho)` is the :func:`qibo.quantum_info.concurrence` of :math:`\\rho`, - and :math:`H` is the :func:`qibo.quantum_info.shannon_entropy`. + and :math:`H` is the :func:`qibo.quantum_info.entropies.shannon_entropy`. Args: state (ndarray): statevector or density matrix. bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. - base (float): the base of the log in :func:`qibo.quantum_info.shannon_entropy`. + base (float): the base of the log in :func:`qibo.quantum_info.entropies.shannon_entropy`. Defaults to :math:`2`. check_purity (bool, optional): if ``True``, checks if ``state`` is pure. If ``False``, it assumes ``state`` is pure . Default: ``True``. @@ -110,7 +110,7 @@ def entanglement_of_formation( if backend is None: # pragma: no cover backend = GlobalBackend() - from qibo.quantum_info.utils import shannon_entropy # pylint: disable=C0415 + from qibo.quantum_info.entropies import shannon_entropy # pylint: disable=C0415 concur = concurrence( state, bipartition=bipartition, check_purity=check_purity, backend=backend diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 82e557772c..6a09d920fe 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -3,10 +3,76 @@ import numpy as np from qibo.backends import GlobalBackend -from qibo.config import raise_error +from qibo.config import PRECISION_TOL, raise_error from qibo.quantum_info.metrics import _check_hermitian_or_not_gpu, purity +def shannon_entropy(probability_array, base: float = 2, backend=None): + """Calculate the Shannon entropy of a probability array :math:`\\mathbf{p}`, which is given by + + .. math:: + H(\\mathbf{p}) = - \\sum_{k = 0}^{d^{2} - 1} \\, p_{k} \\, \\log_{b}(p_{k}) \\, , + + where :math:`d = \\text{dim}(\\mathcal{H})` is the dimension of the + Hilbert space :math:`\\mathcal{H}`, :math:`b` is the log base (default 2), + and :math:`0 \\log_{b}(0) \\equiv 0`. + + Args: + probability_array (ndarray or list): a probability array :math:`\\mathbf{p}`. + base (float): the base of the log. Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. + Defaults to ``None``. + + Returns: + (float): Shannon entropy :math:`H(\\mathcal{p})`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(probability_array, list): + probability_array = backend.cast(probability_array, dtype=float) + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if len(probability_array.shape) != 1: + raise_error( + TypeError, + f"Probability array must have dims (k,) but it has {probability_array.shape}.", + ) + + if len(probability_array) == 0: + raise_error(TypeError, "Empty array.") + + if any(probability_array < 0) or any(probability_array > 1.0): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + + if np.abs(np.sum(probability_array) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Probability array must sum to 1.") + + if base == 2: + log_prob = np.where(probability_array != 0.0, np.log2(probability_array), 0.0) + elif base == 10: + log_prob = np.where(probability_array != 0, np.log10(probability_array), 0.0) + elif base == np.e: + log_prob = np.where(probability_array != 0, np.log(probability_array), 0.0) + else: + log_prob = np.where( + probability_array != 0, np.log(probability_array) / np.log(base), 0.0 + ) + + entropy = -np.sum(probability_array * log_prob) + + # absolute value if entropy == 0.0 to avoid returning -0.0 + entropy = np.abs(entropy) if entropy == 0.0 else entropy + + return complex(entropy).real + + def entropy( state, base: float = 2, diff --git a/src/qibo/quantum_info/utils.py b/src/qibo/quantum_info/utils.py index eb5a447d8d..e13ed68f95 100644 --- a/src/qibo/quantum_info/utils.py +++ b/src/qibo/quantum_info/utils.py @@ -127,72 +127,6 @@ def hadamard_transform(array, implementation: str = "fast", backend=None): return array -def shannon_entropy(probability_array, base: float = 2, backend=None): - """Calculate the Shannon entropy of a probability array :math:`\\mathbf{p}`, which is given by - - .. math:: - H(\\mathbf{p}) = - \\sum_{k = 0}^{d^{2} - 1} \\, p_{k} \\, \\log_{b}(p_{k}) \\, , - - where :math:`d = \\text{dim}(\\mathcal{H})` is the dimension of the - Hilbert space :math:`\\mathcal{H}`, :math:`b` is the log base (default 2), - and :math:`0 \\log_{b}(0) \\equiv 0`. - - Args: - probability_array (ndarray or list): a probability array :math:`\\mathbf{p}`. - base (float): the base of the log. Defaults to :math:`2`. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. - Defaults to ``None``. - - Returns: - (float): The Shannon entropy :math:`H(\\mathcal{p})`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if isinstance(probability_array, list): - probability_array = backend.cast(probability_array, dtype=float) - - if base <= 0: - raise_error(ValueError, "log base must be non-negative.") - - if len(probability_array.shape) != 1: - raise_error( - TypeError, - f"Probability array must have dims (k,) but it has {probability_array.shape}.", - ) - - if len(probability_array) == 0: - raise_error(TypeError, "Empty array.") - - if any(probability_array < 0) or any(probability_array > 1.0): - raise_error( - ValueError, - "All elements of the probability array must be between 0. and 1..", - ) - - if np.abs(np.sum(probability_array) - 1.0) > PRECISION_TOL: - raise_error(ValueError, "Probability array must sum to 1.") - - if base == 2: - log_prob = np.where(probability_array != 0.0, np.log2(probability_array), 0.0) - elif base == 10: - log_prob = np.where(probability_array != 0, np.log10(probability_array), 0.0) - elif base == np.e: - log_prob = np.where(probability_array != 0, np.log(probability_array), 0.0) - else: - log_prob = np.where( - probability_array != 0, np.log(probability_array) / np.log(base), 0.0 - ) - - entropy = -np.sum(probability_array * log_prob) - - # absolute value if entropy == 0.0 to avoid returning -0.0 - entropy = np.abs(entropy) if entropy == 0.0 else entropy - - return complex(entropy).real - - def hellinger_distance(prob_dist_p, prob_dist_q, validate: bool = False, backend=None): """Calculate the Hellinger distance :math:`H(p, q)` between two discrete probability distributions, :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 774ec11fcd..3cc2c43f2f 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -2,10 +2,50 @@ import pytest from qibo.config import PRECISION_TOL -from qibo.quantum_info.entropies import entanglement_entropy, entropy +from qibo.quantum_info.entropies import entanglement_entropy, entropy, shannon_entropy from qibo.quantum_info.random_ensembles import random_statevector, random_unitary +def test_shannon_entropy_errors(backend): + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, -2, backend=backend) + with pytest.raises(TypeError): + prob = np.array([[1.0], [0.0]]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, backend=backend) + with pytest.raises(TypeError): + prob = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, -1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.1, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, backend=backend) + with pytest.raises(ValueError): + prob = np.array([0.5, 0.4999999]) + prob = backend.cast(prob, dtype=prob.dtype) + test = shannon_entropy(prob, backend=backend) + + +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +def test_shannon_entropy(backend, base): + prob_array = [1.0, 0.0] + result = shannon_entropy(prob_array, base, backend=backend) + backend.assert_allclose(result, 0.0) + + if base == 2: + prob_array = np.array([0.5, 0.5]) + prob_array = backend.cast(prob_array, dtype=prob_array.dtype) + result = shannon_entropy(prob_array, base, backend=backend) + backend.assert_allclose(result, 1.0) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) def test_entropy(backend, base, check_hermitian): diff --git a/tests/test_quantum_info_utils.py b/tests/test_quantum_info_utils.py index f873078bb4..d96d3dfd2b 100644 --- a/tests/test_quantum_info_utils.py +++ b/tests/test_quantum_info_utils.py @@ -14,7 +14,6 @@ hellinger_distance, hellinger_fidelity, pqc_integral, - shannon_entropy, ) @@ -90,46 +89,6 @@ def test_hadamard_transform(backend, nqubits, implementation, is_matrix): backend.assert_allclose(transformed, test_transformed, atol=PRECISION_TOL) -def test_shannon_entropy_errors(backend): - with pytest.raises(ValueError): - prob = np.array([1.0, 0.0]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, -2, backend=backend) - with pytest.raises(TypeError): - prob = np.array([[1.0], [0.0]]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, backend=backend) - with pytest.raises(TypeError): - prob = np.array([]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, backend=backend) - with pytest.raises(ValueError): - prob = np.array([1.0, -1.0]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, backend=backend) - with pytest.raises(ValueError): - prob = np.array([1.1, 0.0]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, backend=backend) - with pytest.raises(ValueError): - prob = np.array([0.5, 0.4999999]) - prob = backend.cast(prob, dtype=prob.dtype) - test = shannon_entropy(prob, backend=backend) - - -@pytest.mark.parametrize("base", [2, 10, np.e, 5]) -def test_shannon_entropy(backend, base): - prob_array = [1.0, 0.0] - result = shannon_entropy(prob_array, base, backend=backend) - backend.assert_allclose(result, 0.0) - - if base == 2: - prob_array = np.array([0.5, 0.5]) - prob_array = backend.cast(prob_array, dtype=prob_array.dtype) - result = shannon_entropy(prob_array, base, backend=backend) - backend.assert_allclose(result, 1.0) - - def test_hellinger(backend): with pytest.raises(TypeError): prob = np.random.rand(1, 2) From 44f9719bfc44eede7a621d7e9db72d658fc158bb Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 10:42:12 +0400 Subject: [PATCH 059/200] function --- src/qibo/quantum_info/entropies.py | 60 ++++++++++++++++++++++++++++++ 1 file changed, 60 insertions(+) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 6a09d920fe..759cc411fa 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -222,3 +222,63 @@ def entanglement_entropy( ) return entropy_entanglement + + +def classical_relative_entropy( + prob_dist_p, prob_dist_q, base: float = 2, validate: bool = False, backend=None +): + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(prob_dist_p, list): + prob_dist_p = backend.cast(prob_dist_p, dtype=float) + if isinstance(prob_dist_q, list): + prob_dist_q = backend.cast(prob_dist_q, dtype=float) + + if (len(prob_dist_p.shape) != 1) or (len(prob_dist_q.shape) != 1): + raise_error( + TypeError, + "Probability arrays must have dims (k,) but have " + + f"dims {prob_dist_p.shape} and {prob_dist_q.shape}.", + ) + + if (len(prob_dist_p) == 0) or (len(prob_dist_q) == 0): + raise_error(TypeError, "At least one of the arrays is empty.") + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if validate: + if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( + any(prob_dist_q < 0) or any(prob_dist_q > 1.0) + ): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "First probability array must sum to 1.") + + if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Second probability array must sum to 1.") + + entropy_p = -shannon_entropy(prob_dist_p, base=base, backend=backend) + + if base == 2: + log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) + log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) + elif base == 10: + log_prob_q = np.where(prob_dist_q != 0.0, np.log10(prob_dist_q), -np.inf) + log_prob = np.where(prob_dist_p != 0, log_prob_q, 0.0) + elif base == np.e: + log_prob_q = np.where(prob_dist_q != 0.0, np.log(prob_dist_q), -np.inf) + log_prob = np.where(prob_dist_p != 0, log_prob_q, 0.0) + else: + log_prob_q = np.where( + prob_dist_q != 0.0, np.log(prob_dist_q) / np.log(base), -np.inf + ) + log_prob = np.where(prob_dist_p != 0, log_prob_q / np.log(base), 0.0) + + relative = np.sum(prob_dist_p * log_prob) + + return entropy_p - relative From d004521f48d0aa8d26cfdc31741042e09a5922b5 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 12:16:10 +0400 Subject: [PATCH 060/200] docstring --- src/qibo/quantum_info/entropies.py | 38 ++++++++++++++++++++++++------ 1 file changed, 31 insertions(+), 7 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 759cc411fa..8c014c0af6 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -31,7 +31,8 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): backend = GlobalBackend() if isinstance(probability_array, list): - probability_array = backend.cast(probability_array, dtype=float) + # np.float64 is necessary instead of native float because of tensorflow + probability_array = backend.cast(probability_array, dtype=np.float64) if base <= 0: raise_error(ValueError, "log base must be non-negative.") @@ -227,13 +228,38 @@ def entanglement_entropy( def classical_relative_entropy( prob_dist_p, prob_dist_q, base: float = 2, validate: bool = False, backend=None ): + """Calculates the relative entropy between two discrete probability distributions. + + For probabilities :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, it is defined as + + ..math:: + D(\\mathbf{p} \\, \\| \\, \\mathbf{q}) = \\sum_{x} \\, \\mathbf{p}(x) \\, + \\log\\left( \\frac{\\mathbf{p}(x)}{\\mathbf{q}(x)} \\right) \\, . + + The classical relative entropy is also known as the + `Kullback-Leibler (KL) divergence `_. + + Args: + prob_dist_p (ndarray or list): discrete probability distribution :math:`p`. + prob_dist_q (ndarray or list): discrete probability distribution :math:`q`. + base (float): the base of the log. Defaults to :math:`2`. + validate (bool, optional): If ``True``, checks if :math:`p` and :math:`q` are proper + probability distributions. Defaults to ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + Returns: + float: Classical relative entropy between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. + """ if backend is None: # pragma: no cover backend = GlobalBackend() if isinstance(prob_dist_p, list): - prob_dist_p = backend.cast(prob_dist_p, dtype=float) + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) if isinstance(prob_dist_q, list): - prob_dist_q = backend.cast(prob_dist_q, dtype=float) + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_q = backend.cast(prob_dist_q, dtype=np.float64) if (len(prob_dist_p.shape) != 1) or (len(prob_dist_q.shape) != 1): raise_error( @@ -266,18 +292,16 @@ def classical_relative_entropy( if base == 2: log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) - log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) elif base == 10: log_prob_q = np.where(prob_dist_q != 0.0, np.log10(prob_dist_q), -np.inf) - log_prob = np.where(prob_dist_p != 0, log_prob_q, 0.0) elif base == np.e: log_prob_q = np.where(prob_dist_q != 0.0, np.log(prob_dist_q), -np.inf) - log_prob = np.where(prob_dist_p != 0, log_prob_q, 0.0) else: log_prob_q = np.where( prob_dist_q != 0.0, np.log(prob_dist_q) / np.log(base), -np.inf ) - log_prob = np.where(prob_dist_p != 0, log_prob_q / np.log(base), 0.0) + + log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) relative = np.sum(prob_dist_p * log_prob) From eaa14050028616962526e8a6f7eb5522772c2e5c Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 12:16:26 +0400 Subject: [PATCH 061/200] tests --- tests/test_quantum_info_entropies.py | 67 +++++++++++++++++++++++++++- 1 file changed, 66 insertions(+), 1 deletion(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 3cc2c43f2f..d78ceca58a 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -2,7 +2,12 @@ import pytest from qibo.config import PRECISION_TOL -from qibo.quantum_info.entropies import entanglement_entropy, entropy, shannon_entropy +from qibo.quantum_info.entropies import ( + classical_relative_entropy, + entanglement_entropy, + entropy, + shannon_entropy, +) from qibo.quantum_info.random_ensembles import random_statevector, random_unitary @@ -168,3 +173,63 @@ def test_entanglement_entropy(backend, bipartition, base, check_hermitian): ) backend.assert_allclose(entang_entrop, 0.0, atol=PRECISION_TOL) + + +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("validate", [False, True]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +def test_classical_relative_entropy(backend, base, validate, kind): + with pytest.raises(TypeError): + prob = np.random.rand(1, 2) + prob_q = np.random.rand(1, 5) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, backend=backend) + with pytest.raises(TypeError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, backend=backend) + with pytest.raises(ValueError): + prob = np.array([-1, 2.0]) + prob_q = np.random.rand(1, 5)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.random.rand(1, 2)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.array([0.0, 1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, base=-2, backend=backend) + + prob_p = np.random.rand(10) + prob_q = np.random.rand(10) + prob_p /= np.sum(prob_p) + prob_q /= np.sum(prob_q) + + target = np.sum(prob_p * np.log(prob_p) / np.log(base)) - np.sum( + prob_p * np.log(prob_q) / np.log(base) + ) + + if kind is not None: + prob_p, prob_q = kind(prob_p), kind(prob_q) + + divergence = classical_relative_entropy( + prob_p, prob_q, base=base, validate=validate, backend=backend + ) + + backend.assert_allclose(divergence, target, atol=1e-5) From 75ec076aee90cc3ca6339e573c888f7f68620516 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 12:27:06 +0400 Subject: [PATCH 062/200] fix lint issues --- src/qibo/quantum_info/entropies.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 8c014c0af6..abdcbcc04d 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -66,12 +66,12 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): probability_array != 0, np.log(probability_array) / np.log(base), 0.0 ) - entropy = -np.sum(probability_array * log_prob) + shan_entropy = -np.sum(probability_array * log_prob) # absolute value if entropy == 0.0 to avoid returning -0.0 - entropy = np.abs(entropy) if entropy == 0.0 else entropy + shan_entropy = np.abs(shan_entropy) if shan_entropy == 0.0 else shan_entropy - return complex(entropy).real + return complex(shan_entropy).real def entropy( @@ -288,7 +288,7 @@ def classical_relative_entropy( if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: raise_error(ValueError, "Second probability array must sum to 1.") - entropy_p = -shannon_entropy(prob_dist_p, base=base, backend=backend) + entropy_p = -1 * shannon_entropy(prob_dist_p, base=base, backend=backend) if base == 2: log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) From bd8866062927f76244bdd30634b379710fe15ab7 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:01:23 +0400 Subject: [PATCH 063/200] api ref --- doc/source/api-reference/qibo.rst | 28 ++++++++++++++++++++++++---- 1 file changed, 24 insertions(+), 4 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index efe2a4ef08..73b3fec67b 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1545,11 +1545,31 @@ Entropy .. note:: ``validate`` flag allows the user to choose if the function will check if input ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the - assumption of Hermiticity, because it is faster and, more importantly, - the functions are intended to be used on Hermitian inputs. When ``validate=True`` + assumption of Hermiticity. This is faster and, more importantly, + this function are intended to be used on Hermitian inputs. When ``validate=True`` and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. +Relative Entropy +"""""""""""""""" + +.. autofunction:: qibo.quantum_info.relative_entropy + +.. note:: + ``validate`` flag allows the user to choose if the function will check if input + ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + assumption of Hermiticity. This is faster and, more importantly, + this function are intended to be used on Hermitian inputs. When ``validate=True`` + and either ``state`` or ``target`` is non-Hermitian, + an error will be raised when using `cupy` backend. + + +Classical Relative Entropy +"""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.classical_relative_entropy + + Entanglement Entropy """""""""""""""""""" @@ -1559,8 +1579,8 @@ Entanglement Entropy ``validate`` flag allows the user to choose if the function will check if the reduced density matrix resulting from tracing out ``bipartition`` from input ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the - assumption of Hermiticity, because it is faster and, more importantly, - the functions are intended to be used on Hermitian inputs. When ``validate=True`` + assumption of Hermiticity. This is faster and, more importantly, + this function are intended to be used on Hermitian inputs. When ``validate=True`` and the reduced density matrix is non-Hermitian, an error will be raised when using `cupy` backend. From f951653cb431ec115ab5bab8fe18c1f48ca5fdd1 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:01:34 +0400 Subject: [PATCH 064/200] minor changes --- src/qibo/quantum_info/entanglement.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/qibo/quantum_info/entanglement.py b/src/qibo/quantum_info/entanglement.py index c2f6eda3f0..7f009e367a 100644 --- a/src/qibo/quantum_info/entanglement.py +++ b/src/qibo/quantum_info/entanglement.py @@ -42,7 +42,7 @@ def concurrence(state, bipartition, check_purity: bool = True, backend=None): f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", ) - if isinstance(check_purity, bool) is False: + if not isinstance(check_purity, bool): raise_error( TypeError, f"check_purity must be type bool, but it is type {type(check_purity)}.", @@ -158,7 +158,7 @@ def entanglement_fidelity( if backend is None: # pragma: no cover backend = GlobalBackend() - if isinstance(nqubits, int) is False: + if not isinstance(nqubits, int): raise_error( TypeError, f"nqubits must be type int, but it is type {type(nqubits)}." ) @@ -178,7 +178,7 @@ def entanglement_fidelity( f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", ) - if isinstance(check_hermitian, bool) is False: + if not isinstance(check_hermitian, bool): raise_error( TypeError, f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", @@ -265,7 +265,7 @@ def entangling_capability(circuit, samples: int, seed=None, backend=None): float: Entangling capability. """ - if isinstance(samples, int) is False: + if not isinstance(samples, int): raise_error( TypeError, f"samples must be type int, but it is type {type(samples)}." ) From 3909820955c2b5882abbd90cfb88f1c3edd9be4f Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:01:50 +0400 Subject: [PATCH 065/200] function --- src/qibo/quantum_info/entropies.py | 182 +++++++++++++++++++++-------- 1 file changed, 131 insertions(+), 51 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index abdcbcc04d..7a02c4b6f6 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -119,7 +119,7 @@ def entropy( if base <= 0.0: raise_error(ValueError, "log base must be non-negative.") - if isinstance(check_hermitian, bool) is False: + if not isinstance(check_hermitian, bool): raise_error( TypeError, f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", @@ -131,7 +131,7 @@ def entropy( return 0.0 - if check_hermitian is False or _check_hermitian_or_not_gpu(state, backend=backend): + if not check_hermitian or _check_hermitian_or_not_gpu(state, backend=backend): eigenvalues = np.linalg.eigvalsh(state) else: eigenvalues = np.linalg.eigvals(state) @@ -158,46 +158,14 @@ def entropy( return ent -def entanglement_entropy( - state, - bipartition, - base: float = 2, - check_hermitian: bool = False, - return_spectrum: bool = False, - backend=None, +def relative_entropy( + state, target, base: float = 2, check_hermitian: bool = False, backend=None ): - """Calculates the entanglement entropy :math:`S` of bipartition :math:`A` - of ``state`` :math:`\\rho`. This is given by - - .. math:: - S(\\rho_{A}) = -\\text{tr}(\\rho_{A} \\, \\log(\\rho_{A})) \\, , - - where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density matrix calculated - by tracing out the ``bipartition`` :math:`B`. - - Args: - state (ndarray): statevector or density matrix. - bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. - base (float, optional): the base of the log. Defaults to :math: `2`. - check_hermitian (bool, optional): if ``True``, checks if :math:`\\rho_{A}` is Hermitian. - If ``False``, it assumes ``state`` is Hermitian . Default: ``False``. - return_spectrum: if ``True``, returns ``entropy`` and eigenvalues of ``state``. - If ``False``, returns only ``entropy``. Default is ``False``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used - in the execution. If ``None``, it uses - :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. - - Returns: - float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. - """ if backend is None: # pragma: no cover backend = GlobalBackend() - if base <= 0.0: - raise_error(ValueError, "log base must be non-negative.") - if ( - (len(state.shape) not in [1, 2]) + (len(state.shape) >= 3) or (len(state) == 0) or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) ): @@ -206,23 +174,68 @@ def entanglement_entropy( f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", ) - nqubits = int(np.log2(state.shape[0])) + if ( + (len(target.shape) >= 3) + or (len(target) == 0) + or (len(target.shape) == 2 and target.shape[0] != target.shape[1]) + ): + raise_error( + TypeError, + f"target must have dims either (k,) or (k,k), but have dims {target.shape}.", + ) - reduced_density_matrix = ( - backend.partial_trace(state, bipartition, nqubits) - if len(state.shape) == 1 - else backend.partial_trace_density_matrix(state, bipartition, nqubits) - ) + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") - entropy_entanglement = entropy( - reduced_density_matrix, - base=base, - check_hermitian=check_hermitian, - return_spectrum=return_spectrum, - backend=backend, - ) + if not isinstance(check_hermitian, bool): + raise_error( + TypeError, + f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", + ) - return entropy_entanglement + if purity(state) == 1.0 and purity(target) == 1.0: + return 0.0 + + if not check_hermitian or _check_hermitian_or_not_gpu(state, backend=backend): + eigenvalues_state = np.linalg.eigvalsh(state) + else: + eigenvalues_state = np.linalg.eigvals(state) + + if not check_hermitian or _check_hermitian_or_not_gpu(target, backend=backend): + eigenvalues_target = np.linalg.eigvalsh(target) + else: + eigenvalues_target = np.linalg.eigvals(target) + + if base == 2: + log_state = np.where(eigenvalues_state > 0, np.log2(eigenvalues_state), 0.0) + log_target = np.where( + eigenvalues_target > 0, np.log2(eigenvalues_target), -np.inf + ) + elif base == 10: + log_state = np.where(eigenvalues_state > 0, np.log10(eigenvalues_state), 0.0) + log_target = np.where( + eigenvalues_target > 0, np.log10(eigenvalues_target), -np.inf + ) + elif base == np.e: + log_state = np.where(eigenvalues_state > 0, np.log(eigenvalues_state), 0.0) + log_target = np.where( + eigenvalues_target > 0, np.log(eigenvalues_target), -np.inf + ) + else: + log_state = np.where( + eigenvalues_state > 0, np.log(eigenvalues_state) / np.log(base), 0.0 + ) + log_target = np.where( + eigenvalues_target > 0, np.log(eigenvalues_target) / np.log(base), -np.inf + ) + + log_target = np.where(eigenvalues_state != 0.0, log_target, 0.0) + + entropy_state = np.sum(eigenvalues_state * log_state) + + relative = np.sum(eigenvalues_state * log_target) + + return float(entropy_state - relative) def classical_relative_entropy( @@ -306,3 +319,70 @@ def classical_relative_entropy( relative = np.sum(prob_dist_p * log_prob) return entropy_p - relative + + +def entanglement_entropy( + state, + bipartition, + base: float = 2, + check_hermitian: bool = False, + return_spectrum: bool = False, + backend=None, +): + """Calculates the entanglement entropy :math:`S` of bipartition :math:`A` + of ``state`` :math:`\\rho`. This is given by + + .. math:: + S(\\rho_{A}) = -\\text{tr}(\\rho_{A} \\, \\log(\\rho_{A})) \\, , + + where :math:`\\rho_{A} = \\text{tr}_{B}(\\rho)` is the reduced density matrix calculated + by tracing out the ``bipartition`` :math:`B`. + + Args: + state (ndarray): statevector or density matrix. + bipartition (list or tuple or ndarray): qubits in the subsystem to be traced out. + base (float, optional): the base of the log. Defaults to :math: `2`. + check_hermitian (bool, optional): if ``True``, checks if :math:`\\rho_{A}` is Hermitian. + If ``False``, it assumes ``state`` is Hermitian . Default: ``False``. + return_spectrum: if ``True``, returns ``entropy`` and eigenvalues of ``state``. + If ``False``, returns only ``entropy``. Default is ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if ( + (len(state.shape) not in [1, 2]) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + nqubits = int(np.log2(state.shape[0])) + + reduced_density_matrix = ( + backend.partial_trace(state, bipartition, nqubits) + if len(state.shape) == 1 + else backend.partial_trace_density_matrix(state, bipartition, nqubits) + ) + + entropy_entanglement = entropy( + reduced_density_matrix, + base=base, + check_hermitian=check_hermitian, + return_spectrum=return_spectrum, + backend=backend, + ) + + return entropy_entanglement From 373f81c2d9fdf51c0475ff08c830aa04360a9b09 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:01:54 +0400 Subject: [PATCH 066/200] tests --- tests/test_quantum_info_entropies.py | 172 ++++++++++++++++++--------- 1 file changed, 114 insertions(+), 58 deletions(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index d78ceca58a..2ef5689ee4 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -6,9 +6,14 @@ classical_relative_entropy, entanglement_entropy, entropy, + relative_entropy, shannon_entropy, ) -from qibo.quantum_info.random_ensembles import random_statevector, random_unitary +from qibo.quantum_info.random_ensembles import ( + random_density_matrix, + random_statevector, + random_unitary, +) def test_shannon_entropy_errors(backend): @@ -103,77 +108,54 @@ def test_entropy(backend, base, check_hermitian): @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("bipartition", [[0], [1]]) -def test_entanglement_entropy(backend, bipartition, base, check_hermitian): +def test_relative_entropy(backend, base, check_hermitian): with pytest.raises(TypeError): state = np.random.rand(2, 3) state = backend.cast(state, dtype=state.dtype) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, + target = random_density_matrix(2, pure=True, backend=backend) + test = relative_entropy( + state, target, base=base, check_hermitian=check_hermitian, backend=backend + ) + with pytest.raises(TypeError): + target = np.random.rand(2, 3) + target = backend.cast(target, dtype=target.dtype) + state = random_density_matrix(2, pure=True, backend=backend) + test = relative_entropy( + state, target, base=base, check_hermitian=check_hermitian, backend=backend ) with pytest.raises(ValueError): state = np.array([1.0, 0.0]) state = backend.cast(state, dtype=state.dtype) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=0, - check_hermitian=check_hermitian, - backend=backend, + target = np.array([0.0, 1.0]) + target = backend.cast(target, dtype=target.dtype) + test = relative_entropy( + state, target, base=0, check_hermitian=check_hermitian, backend=backend + ) + with pytest.raises(TypeError): + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + target = np.array([0.0, 1.0]) + target = backend.cast(target, dtype=target.dtype) + test = relative_entropy( + state, target, base=base, check_hermitian="False", backend=backend ) - if backend.__class__.__name__ == "CupyBackend": - with pytest.raises(NotImplementedError): - state = random_unitary(4, backend=backend) - test = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=True, - backend=backend, - ) - - # Bell state - state = np.array([1.0, 0.0, 0.0, 1.0]) / np.sqrt(2) - state = backend.cast(state, dtype=state.dtype) - - entang_entrop = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, - ) - if base == 2: - test = 1.0 - elif base == 10: - test = 0.30102999566398125 - elif base == np.e: - test = 0.6931471805599454 - else: - test = 0.4306765580733931 + nqubits = 2 + dims = 2**nqubits - backend.assert_allclose(entang_entrop, test, atol=PRECISION_TOL) + state = random_density_matrix(dims, backend=backend) + target = backend.identity_density_matrix(nqubits, normalize=True) - # Product state - state = np.kron( - random_statevector(2, backend=backend), random_statevector(2, backend=backend) - ) + print(relative_entropy(state, target, base, check_hermitian, backend)) + print(entropy(state, base, check_hermitian=check_hermitian, backend=backend)) - entang_entrop = entanglement_entropy( - state, - bipartition=bipartition, - base=base, - check_hermitian=check_hermitian, - backend=backend, + backend.assert_allclose( + relative_entropy(state, target, base, check_hermitian, backend), + np.log(dims) / np.log(base) + - entropy(state, base=base, check_hermitian=check_hermitian, backend=backend), + atol=1e-5, ) - backend.assert_allclose(entang_entrop, 0.0, atol=PRECISION_TOL) - @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("validate", [False, True]) @@ -233,3 +215,77 @@ def test_classical_relative_entropy(backend, base, validate, kind): ) backend.assert_allclose(divergence, target, atol=1e-5) + + +@pytest.mark.parametrize("check_hermitian", [False, True]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("bipartition", [[0], [1]]) +def test_entanglement_entropy(backend, bipartition, base, check_hermitian): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + with pytest.raises(ValueError): + state = np.array([1.0, 0.0]) + state = backend.cast(state, dtype=state.dtype) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=0, + check_hermitian=check_hermitian, + backend=backend, + ) + if backend.__class__.__name__ == "CupyBackend": + with pytest.raises(NotImplementedError): + state = random_unitary(4, backend=backend) + test = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=True, + backend=backend, + ) + + # Bell state + state = np.array([1.0, 0.0, 0.0, 1.0]) / np.sqrt(2) + state = backend.cast(state, dtype=state.dtype) + + entang_entrop = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + + if base == 2: + test = 1.0 + elif base == 10: + test = 0.30102999566398125 + elif base == np.e: + test = 0.6931471805599454 + else: + test = 0.4306765580733931 + + backend.assert_allclose(entang_entrop, test, atol=PRECISION_TOL) + + # Product state + state = np.kron( + random_statevector(2, backend=backend), random_statevector(2, backend=backend) + ) + + entang_entrop = entanglement_entropy( + state, + bipartition=bipartition, + base=base, + check_hermitian=check_hermitian, + backend=backend, + ) + + backend.assert_allclose(entang_entrop, 0.0, atol=PRECISION_TOL) From 8c0d8758171dde1fce05da7891f726c51afc269b Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:19:39 +0400 Subject: [PATCH 067/200] docstring --- src/qibo/quantum_info/entropies.py | 27 +++++++++++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 7a02c4b6f6..2f9e0a03a5 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -81,8 +81,9 @@ def entropy( return_spectrum: bool = False, backend=None, ): - """The von-Neumann entropy :math:`S(\\rho)` of a quantum ``state`` :math:`\\rho`, which - is given by + """Calculates the von-Neumann entropy :math:`S(\\rho)` of a quantum ``state`` :math:`\\rho`. + + It is given by .. math:: S(\\rho) = - \\text{tr}\\left[\\rho \\, \\log(\\rho)\\right] @@ -161,6 +162,28 @@ def entropy( def relative_entropy( state, target, base: float = 2, check_hermitian: bool = False, backend=None ): + """Calculates the relative entropy :math:`S(\\rho \\, \\| \\, \\sigma)` between ``state`` :math:`\\rho` and ``target`` :math:`\\sigma`. + + It is given by + + .. math:: + S(\\rho \\, \\| \\, \\sigma) = \\text{tr}\\left[\\rho \\, \\log(\\rho)\\right] + - \\text{tr}\\left[\\rho \\, \\log(\\sigma)\\right] + + Args: + state (ndarray): statevector or density matrix :math:`\\rho`. + target (ndarray): statevector or density matrix :math:`\\sigma`. + base (float, optional): the base of the log. Defaults to :math:`2`. + check_hermitian (bool, optional): If ``True``, checks if ``state`` is Hermitian. + If ``False``, it assumes ``state`` is Hermitian . + Defaults to ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Relative (von-Neumann) entropy :math:`S(\\rho \\, \\| \\, \\sigma)`. + """ if backend is None: # pragma: no cover backend = GlobalBackend() From 8cc2ade0719f5ec408f99bab11c4899e291c5e08 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 14:35:11 +0400 Subject: [PATCH 068/200] fix coverage --- tests/test_quantum_info_entropies.py | 29 +++++++++++++++++++++++++--- 1 file changed, 26 insertions(+), 3 deletions(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 2ef5689ee4..cd5cce3362 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -146,9 +146,6 @@ def test_relative_entropy(backend, base, check_hermitian): state = random_density_matrix(dims, backend=backend) target = backend.identity_density_matrix(nqubits, normalize=True) - print(relative_entropy(state, target, base, check_hermitian, backend)) - print(entropy(state, base, check_hermitian=check_hermitian, backend=backend)) - backend.assert_allclose( relative_entropy(state, target, base, check_hermitian, backend), np.log(dims) / np.log(base) @@ -156,6 +153,32 @@ def test_relative_entropy(backend, base, check_hermitian): atol=1e-5, ) + state = backend.cast([1.0, 0.0], dtype=np.float64) + target = backend.cast([0.0, 1.0], dtype=np.float64) + + assert relative_entropy(state, target, backend=backend) == 0.0 + + # for coverage when GPUs are present + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + with pytest.raises(NotImplementedError): + state = random_unitary(4, backend=backend) + target = random_density_matrix(4, backend=backend) + test = relative_entropy( + state, target, base=base, check_hermitian=True, backend=backend + ) + with pytest.raises(NotImplementedError): + target = random_unitary(4, backend=backend) + state = random_density_matrix(4, backend=backend) + test = relative_entropy( + state, target, base=base, check_hermitian=True, backend=backend + ) + else: + state = random_unitary(4, backend=backend) + target = random_unitary(4, backend=backend) + test = relative_entropy( + state, target, base=base, check_hermitian=True, backend=backend + ) + @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("validate", [False, True]) From 1815adc31c1a9163f360f6146b9d87cb6cb95a4e Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 15:14:34 +0400 Subject: [PATCH 069/200] reorder functions --- doc/source/api-reference/qibo.rst | 12 +- src/qibo/quantum_info/entropies.py | 166 +++++++++++++-------------- tests/test_quantum_info_entropies.py | 120 +++++++++---------- 3 files changed, 149 insertions(+), 149 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 73b3fec67b..fb1c5df5dd 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1537,6 +1537,12 @@ Shannon entropy .. autofunction:: qibo.quantum_info.shannon_entropy +Classical Relative Entropy +"""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.classical_relative_entropy + + Entropy """"""" @@ -1564,12 +1570,6 @@ Relative Entropy an error will be raised when using `cupy` backend. -Classical Relative Entropy -"""""""""""""""""""""""""" - -.. autofunction:: qibo.quantum_info.classical_relative_entropy - - Entanglement Entropy """""""""""""""""""" diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 2f9e0a03a5..058b7e4a15 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -74,6 +74,89 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): return complex(shan_entropy).real +def classical_relative_entropy( + prob_dist_p, prob_dist_q, base: float = 2, validate: bool = False, backend=None +): + """Calculates the relative entropy between two discrete probability distributions. + + For probabilities :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, it is defined as + + ..math:: + D(\\mathbf{p} \\, \\| \\, \\mathbf{q}) = \\sum_{x} \\, \\mathbf{p}(x) \\, + \\log\\left( \\frac{\\mathbf{p}(x)}{\\mathbf{q}(x)} \\right) \\, . + + The classical relative entropy is also known as the + `Kullback-Leibler (KL) divergence `_. + + Args: + prob_dist_p (ndarray or list): discrete probability distribution :math:`p`. + prob_dist_q (ndarray or list): discrete probability distribution :math:`q`. + base (float): the base of the log. Defaults to :math:`2`. + validate (bool, optional): If ``True``, checks if :math:`p` and :math:`q` are proper + probability distributions. Defaults to ``False``. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + Returns: + float: Classical relative entropy between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(prob_dist_p, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) + if isinstance(prob_dist_q, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_q = backend.cast(prob_dist_q, dtype=np.float64) + + if (len(prob_dist_p.shape) != 1) or (len(prob_dist_q.shape) != 1): + raise_error( + TypeError, + "Probability arrays must have dims (k,) but have " + + f"dims {prob_dist_p.shape} and {prob_dist_q.shape}.", + ) + + if (len(prob_dist_p) == 0) or (len(prob_dist_q) == 0): + raise_error(TypeError, "At least one of the arrays is empty.") + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if validate: + if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( + any(prob_dist_q < 0) or any(prob_dist_q > 1.0) + ): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "First probability array must sum to 1.") + + if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Second probability array must sum to 1.") + + entropy_p = -1 * shannon_entropy(prob_dist_p, base=base, backend=backend) + + if base == 2: + log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) + elif base == 10: + log_prob_q = np.where(prob_dist_q != 0.0, np.log10(prob_dist_q), -np.inf) + elif base == np.e: + log_prob_q = np.where(prob_dist_q != 0.0, np.log(prob_dist_q), -np.inf) + else: + log_prob_q = np.where( + prob_dist_q != 0.0, np.log(prob_dist_q) / np.log(base), -np.inf + ) + + log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) + + relative = np.sum(prob_dist_p * log_prob) + + return entropy_p - relative + + def entropy( state, base: float = 2, @@ -261,89 +344,6 @@ def relative_entropy( return float(entropy_state - relative) -def classical_relative_entropy( - prob_dist_p, prob_dist_q, base: float = 2, validate: bool = False, backend=None -): - """Calculates the relative entropy between two discrete probability distributions. - - For probabilities :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, it is defined as - - ..math:: - D(\\mathbf{p} \\, \\| \\, \\mathbf{q}) = \\sum_{x} \\, \\mathbf{p}(x) \\, - \\log\\left( \\frac{\\mathbf{p}(x)}{\\mathbf{q}(x)} \\right) \\, . - - The classical relative entropy is also known as the - `Kullback-Leibler (KL) divergence `_. - - Args: - prob_dist_p (ndarray or list): discrete probability distribution :math:`p`. - prob_dist_q (ndarray or list): discrete probability distribution :math:`q`. - base (float): the base of the log. Defaults to :math:`2`. - validate (bool, optional): If ``True``, checks if :math:`p` and :math:`q` are proper - probability distributions. Defaults to ``False``. - backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be - used in the execution. If ``None``, it uses - :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. - Returns: - float: Classical relative entropy between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. - """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if isinstance(prob_dist_p, list): - # np.float64 is necessary instead of native float because of tensorflow - prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) - if isinstance(prob_dist_q, list): - # np.float64 is necessary instead of native float because of tensorflow - prob_dist_q = backend.cast(prob_dist_q, dtype=np.float64) - - if (len(prob_dist_p.shape) != 1) or (len(prob_dist_q.shape) != 1): - raise_error( - TypeError, - "Probability arrays must have dims (k,) but have " - + f"dims {prob_dist_p.shape} and {prob_dist_q.shape}.", - ) - - if (len(prob_dist_p) == 0) or (len(prob_dist_q) == 0): - raise_error(TypeError, "At least one of the arrays is empty.") - - if base <= 0: - raise_error(ValueError, "log base must be non-negative.") - - if validate: - if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( - any(prob_dist_q < 0) or any(prob_dist_q > 1.0) - ): - raise_error( - ValueError, - "All elements of the probability array must be between 0. and 1..", - ) - if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: - raise_error(ValueError, "First probability array must sum to 1.") - - if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: - raise_error(ValueError, "Second probability array must sum to 1.") - - entropy_p = -1 * shannon_entropy(prob_dist_p, base=base, backend=backend) - - if base == 2: - log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) - elif base == 10: - log_prob_q = np.where(prob_dist_q != 0.0, np.log10(prob_dist_q), -np.inf) - elif base == np.e: - log_prob_q = np.where(prob_dist_q != 0.0, np.log(prob_dist_q), -np.inf) - else: - log_prob_q = np.where( - prob_dist_q != 0.0, np.log(prob_dist_q) / np.log(base), -np.inf - ) - - log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) - - relative = np.sum(prob_dist_p * log_prob) - - return entropy_p - relative - - def entanglement_entropy( state, bipartition, diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index cd5cce3362..fc6d56ace6 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -56,6 +56,66 @@ def test_shannon_entropy(backend, base): backend.assert_allclose(result, 1.0) +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("validate", [False, True]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +def test_classical_relative_entropy(backend, base, validate, kind): + with pytest.raises(TypeError): + prob = np.random.rand(1, 2) + prob_q = np.random.rand(1, 5) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, backend=backend) + with pytest.raises(TypeError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, backend=backend) + with pytest.raises(ValueError): + prob = np.array([-1, 2.0]) + prob_q = np.random.rand(1, 5)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.random.rand(1, 2)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.array([0.0, 1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_relative_entropy(prob, prob_q, base=-2, backend=backend) + + prob_p = np.random.rand(10) + prob_q = np.random.rand(10) + prob_p /= np.sum(prob_p) + prob_q /= np.sum(prob_q) + + target = np.sum(prob_p * np.log(prob_p) / np.log(base)) - np.sum( + prob_p * np.log(prob_q) / np.log(base) + ) + + if kind is not None: + prob_p, prob_q = kind(prob_p), kind(prob_q) + + divergence = classical_relative_entropy( + prob_p, prob_q, base=base, validate=validate, backend=backend + ) + + backend.assert_allclose(divergence, target, atol=1e-5) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) def test_entropy(backend, base, check_hermitian): @@ -180,66 +240,6 @@ def test_relative_entropy(backend, base, check_hermitian): ) -@pytest.mark.parametrize("kind", [None, list]) -@pytest.mark.parametrize("validate", [False, True]) -@pytest.mark.parametrize("base", [2, 10, np.e, 5]) -def test_classical_relative_entropy(backend, base, validate, kind): - with pytest.raises(TypeError): - prob = np.random.rand(1, 2) - prob_q = np.random.rand(1, 5) - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, backend=backend) - with pytest.raises(TypeError): - prob = np.random.rand(1, 2)[0] - prob_q = np.array([]) - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, backend=backend) - with pytest.raises(ValueError): - prob = np.array([-1, 2.0]) - prob_q = np.random.rand(1, 5)[0] - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) - with pytest.raises(ValueError): - prob = np.random.rand(1, 2)[0] - prob_q = np.array([1.0, 0.0]) - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) - with pytest.raises(ValueError): - prob = np.array([1.0, 0.0]) - prob_q = np.random.rand(1, 2)[0] - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) - with pytest.raises(ValueError): - prob = np.array([1.0, 0.0]) - prob_q = np.array([0.0, 1.0]) - prob = backend.cast(prob, dtype=prob.dtype) - prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, base=-2, backend=backend) - - prob_p = np.random.rand(10) - prob_q = np.random.rand(10) - prob_p /= np.sum(prob_p) - prob_q /= np.sum(prob_q) - - target = np.sum(prob_p * np.log(prob_p) / np.log(base)) - np.sum( - prob_p * np.log(prob_q) / np.log(base) - ) - - if kind is not None: - prob_p, prob_q = kind(prob_p), kind(prob_q) - - divergence = classical_relative_entropy( - prob_p, prob_q, base=base, validate=validate, backend=backend - ) - - backend.assert_allclose(divergence, target, atol=1e-5) - - @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("bipartition", [[0], [1]]) From d7f885cc5a5dbeabdd05c6e7e61a1fae44728f08 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 15:59:28 +0400 Subject: [PATCH 070/200] api ref --- doc/source/api-reference/qibo.rst | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index fb1c5df5dd..5f80e763c1 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1543,6 +1543,12 @@ Classical Relative Entropy .. autofunction:: qibo.quantum_info.classical_relative_entropy +Classical Rényi Entropy +""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.classical_renyi_entropy + + Entropy """"""" @@ -1570,6 +1576,12 @@ Relative Entropy an error will be raised when using `cupy` backend. +Rényi Entropy +""""""""""""" + +.. autofunction:: qibo.quantum_info.renyi_entropy + + Entanglement Entropy """""""""""""""""""" From 935d87fd172d27d41a102bfbcf9e4ca712ac9e09 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 15:59:38 +0400 Subject: [PATCH 071/200] classical renyi entropy --- src/qibo/quantum_info/entropies.py | 139 ++++++++++++++++++++++------- 1 file changed, 106 insertions(+), 33 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 058b7e4a15..6d3492d45d 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -7,7 +7,7 @@ from qibo.quantum_info.metrics import _check_hermitian_or_not_gpu, purity -def shannon_entropy(probability_array, base: float = 2, backend=None): +def shannon_entropy(prob_dist, base: float = 2, backend=None): """Calculate the Shannon entropy of a probability array :math:`\\mathbf{p}`, which is given by .. math:: @@ -18,7 +18,7 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): and :math:`0 \\log_{b}(0) \\equiv 0`. Args: - probability_array (ndarray or list): a probability array :math:`\\mathbf{p}`. + prob_dist (ndarray or list): a probability array :math:`\\mathbf{p}`. base (float): the base of the log. Defaults to :math:`2`. backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. @@ -30,43 +30,41 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): if backend is None: # pragma: no cover backend = GlobalBackend() - if isinstance(probability_array, list): + if isinstance(prob_dist, list): # np.float64 is necessary instead of native float because of tensorflow - probability_array = backend.cast(probability_array, dtype=np.float64) + prob_dist = backend.cast(prob_dist, dtype=np.float64) if base <= 0: raise_error(ValueError, "log base must be non-negative.") - if len(probability_array.shape) != 1: + if len(prob_dist.shape) != 1: raise_error( TypeError, - f"Probability array must have dims (k,) but it has {probability_array.shape}.", + f"Probability array must have dims (k,) but it has {prob_dist.shape}.", ) - if len(probability_array) == 0: + if len(prob_dist) == 0: raise_error(TypeError, "Empty array.") - if any(probability_array < 0) or any(probability_array > 1.0): + if any(prob_dist < 0) or any(prob_dist > 1.0): raise_error( ValueError, "All elements of the probability array must be between 0. and 1..", ) - if np.abs(np.sum(probability_array) - 1.0) > PRECISION_TOL: + if np.abs(np.sum(prob_dist) - 1.0) > PRECISION_TOL: raise_error(ValueError, "Probability array must sum to 1.") if base == 2: - log_prob = np.where(probability_array != 0.0, np.log2(probability_array), 0.0) + log_prob = np.where(prob_dist != 0.0, np.log2(prob_dist), 0.0) elif base == 10: - log_prob = np.where(probability_array != 0, np.log10(probability_array), 0.0) + log_prob = np.where(prob_dist != 0, np.log10(prob_dist), 0.0) elif base == np.e: - log_prob = np.where(probability_array != 0, np.log(probability_array), 0.0) + log_prob = np.where(prob_dist != 0, np.log(prob_dist), 0.0) else: - log_prob = np.where( - probability_array != 0, np.log(probability_array) / np.log(base), 0.0 - ) + log_prob = np.where(prob_dist != 0, np.log(prob_dist) / np.log(base), 0.0) - shan_entropy = -np.sum(probability_array * log_prob) + shan_entropy = -np.sum(prob_dist * log_prob) # absolute value if entropy == 0.0 to avoid returning -0.0 shan_entropy = np.abs(shan_entropy) if shan_entropy == 0.0 else shan_entropy @@ -74,9 +72,7 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): return complex(shan_entropy).real -def classical_relative_entropy( - prob_dist_p, prob_dist_q, base: float = 2, validate: bool = False, backend=None -): +def classical_relative_entropy(prob_dist_p, prob_dist_q, base: float = 2, backend=None): """Calculates the relative entropy between two discrete probability distributions. For probabilities :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, it is defined as @@ -92,11 +88,10 @@ def classical_relative_entropy( prob_dist_p (ndarray or list): discrete probability distribution :math:`p`. prob_dist_q (ndarray or list): discrete probability distribution :math:`q`. base (float): the base of the log. Defaults to :math:`2`. - validate (bool, optional): If ``True``, checks if :math:`p` and :math:`q` are proper - probability distributions. Defaults to ``False``. backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used in the execution. If ``None``, it uses :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + Returns: float: Classical relative entropy between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. """ @@ -123,19 +118,18 @@ def classical_relative_entropy( if base <= 0: raise_error(ValueError, "log base must be non-negative.") - if validate: - if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( - any(prob_dist_q < 0) or any(prob_dist_q > 1.0) - ): - raise_error( - ValueError, - "All elements of the probability array must be between 0. and 1..", - ) - if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: - raise_error(ValueError, "First probability array must sum to 1.") + if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( + any(prob_dist_q < 0) or any(prob_dist_q > 1.0) + ): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "First probability array must sum to 1.") - if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: - raise_error(ValueError, "Second probability array must sum to 1.") + if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Second probability array must sum to 1.") entropy_p = -1 * shannon_entropy(prob_dist_p, base=base, backend=backend) @@ -157,6 +151,85 @@ def classical_relative_entropy( return entropy_p - relative +def classical_renyi_entropy(prob_dist, alpha: float, base: float = 2, backend=None): + """Calculates the classical Rényi entropy :math:`H_{\\alpha}` of a discrete probability distribution. + + For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and probability distribution + :math:`\\mathbf{p}`, the Rényi entropy is defined as + + .. math:: + H_{\\alpha}(\\mathbf{p}) = \\frac{1}{1 - \\alpha} \\, \\log\\left( \\sum_{x} + \\, \\mathbf{p}^{\\alpha}(x) \\right) \\, . + + For :math:`\\alpha \\in \\{0, 1, \\infty \\}`, it is further defined that + + .. math:: + H_{\\alpha}(\\mathbf{p}) = \\lim_{\\beta \\to \\alpha} \\, H_{\\beta}(\\mathbf{p}) \\, . + + A special case is the limit :math:`\\alpha \\to 1`, in which the classical Rényi entropy + coincides with the :func:`qibo.quantum_info.entropies.shannon_entropy`. + + Args: + prob_dist (ndarray): discrete probability distribution. + alpha (float): order of the Rényi entropy. + If :math:`\\alpha = 1`, defaults to :func:`qibo.quantum_info.entropies.shannon_entropy`. + If :math:`\\alpha = \\infty`, defaults to the + `min-entropy `_. + base (float): the base of the log. Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Rényi entropy :math:`H_{\\alpha}`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(prob_dist, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist = backend.cast(prob_dist, dtype=np.float64) + + if not isinstance(alpha, float): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if len(prob_dist.shape) != 1: + raise_error( + TypeError, + f"Probability array must have dims (k,) but it has {prob_dist.shape}.", + ) + + if len(prob_dist) == 0: + raise_error(TypeError, "Empty array.") + + if any(prob_dist < 0) or any(prob_dist > 1.0): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + + if np.abs(np.sum(prob_dist) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Probability array must sum to 1.") + + if alpha == 1.0: + return shannon_entropy(prob_dist, base=base, backend=backend) + + if alpha == np.inf: + return -1 * np.log2(max(prob_dist)) / np.log2(base) + + renyi_ent = (1 / (1 - alpha)) * np.log2(np.sum(prob_dist**alpha)) / np.log2(base) + + return renyi_ent + + def entropy( state, base: float = 2, From cb799bd281230f5f5da805e7d5d18587d1bf2634 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 15:59:48 +0400 Subject: [PATCH 072/200] remove variable --- tests/test_quantum_info_entropies.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index fc6d56ace6..392d4b108b 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -57,9 +57,8 @@ def test_shannon_entropy(backend, base): @pytest.mark.parametrize("kind", [None, list]) -@pytest.mark.parametrize("validate", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -def test_classical_relative_entropy(backend, base, validate, kind): +def test_classical_relative_entropy(backend, base, kind): with pytest.raises(TypeError): prob = np.random.rand(1, 2) prob_q = np.random.rand(1, 5) @@ -77,19 +76,19 @@ def test_classical_relative_entropy(backend, base, validate, kind): prob_q = np.random.rand(1, 5)[0] prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + test = classical_relative_entropy(prob, prob_q, backend=backend) with pytest.raises(ValueError): prob = np.random.rand(1, 2)[0] prob_q = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + test = classical_relative_entropy(prob, prob_q, backend=backend) with pytest.raises(ValueError): prob = np.array([1.0, 0.0]) prob_q = np.random.rand(1, 2)[0] prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_relative_entropy(prob, prob_q, validate=True, backend=backend) + test = classical_relative_entropy(prob, prob_q, backend=backend) with pytest.raises(ValueError): prob = np.array([1.0, 0.0]) prob_q = np.array([0.0, 1.0]) @@ -109,9 +108,7 @@ def test_classical_relative_entropy(backend, base, validate, kind): if kind is not None: prob_p, prob_q = kind(prob_p), kind(prob_q) - divergence = classical_relative_entropy( - prob_p, prob_q, base=base, validate=validate, backend=backend - ) + divergence = classical_relative_entropy(prob_p, prob_q, base=base, backend=backend) backend.assert_allclose(divergence, target, atol=1e-5) From e3474901f669a8bd17a04af0a7fe16972f1ac8e4 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 17:23:09 +0400 Subject: [PATCH 073/200] test errors --- src/qibo/quantum_info/entropies.py | 9 ++++-- tests/test_quantum_info_entropies.py | 43 ++++++++++++++++++++++++++++ 2 files changed, 49 insertions(+), 3 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 6d3492d45d..ec869ba9c9 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -1,4 +1,5 @@ """Submodule with entropy measures.""" +from typing import Union import numpy as np @@ -151,7 +152,9 @@ def classical_relative_entropy(prob_dist_p, prob_dist_q, base: float = 2, backen return entropy_p - relative -def classical_renyi_entropy(prob_dist, alpha: float, base: float = 2, backend=None): +def classical_renyi_entropy( + prob_dist, alpha: Union[float, int], base: float = 2, backend=None +): """Calculates the classical Rényi entropy :math:`H_{\\alpha}` of a discrete probability distribution. For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and probability distribution @@ -171,7 +174,7 @@ def classical_renyi_entropy(prob_dist, alpha: float, base: float = 2, backend=No Args: prob_dist (ndarray): discrete probability distribution. - alpha (float): order of the Rényi entropy. + alpha (float or int): order of the Rényi entropy. If :math:`\\alpha = 1`, defaults to :func:`qibo.quantum_info.entropies.shannon_entropy`. If :math:`\\alpha = \\infty`, defaults to the `min-entropy `_. @@ -190,7 +193,7 @@ def classical_renyi_entropy(prob_dist, alpha: float, base: float = 2, backend=No # np.float64 is necessary instead of native float because of tensorflow prob_dist = backend.cast(prob_dist, dtype=np.float64) - if not isinstance(alpha, float): + if not isinstance(alpha, (float, int)): raise_error( TypeError, f"alpha must be type float, but it is type {type(alpha)}." ) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 392d4b108b..e7d19a4ef4 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -4,6 +4,7 @@ from qibo.config import PRECISION_TOL from qibo.quantum_info.entropies import ( classical_relative_entropy, + classical_renyi_entropy, entanglement_entropy, entropy, relative_entropy, @@ -113,6 +114,48 @@ def test_classical_relative_entropy(backend, base, kind): backend.assert_allclose(divergence, target, atol=1e-5) +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [1, 2, 3, np.inf]) +def test_classical_renyi_entropy(backend, alpha, base, kind): + with pytest.raises(TypeError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha="2", backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha=-2, backend=backend) + with pytest.raises(TypeError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, base="2", backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, base=-2, backend=backend) + with pytest.raises(TypeError): + prob = np.array([[1.0], [0.0]]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(TypeError): + prob = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, -1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.1, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([0.5, 0.4999999]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) def test_entropy(backend, base, check_hermitian): From f4a6b6aa0ee56e6aeaf25b37ab8bda65a5a8fa9c Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 17:33:36 +0400 Subject: [PATCH 074/200] test function --- tests/test_quantum_info_entropies.py | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index e7d19a4ef4..4853c2eef1 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -155,6 +155,25 @@ def test_classical_renyi_entropy(backend, alpha, base, kind): prob = backend.cast(prob, dtype=prob.dtype) test = classical_renyi_entropy(prob, alpha, backend=backend) + prob_dist = np.random.rand(10) + prob_dist /= np.sum(prob_dist) + + if alpha == 1: + target = shannon_entropy(prob_dist, base=base, backend=backend) + elif alpha == 2: + target = -1 * np.log2(np.sum(prob_dist**2)) / np.log2(base) + elif alpha == np.inf: + target = -1 * np.log2(max(prob_dist)) / np.log2(base) + else: + target = (1 / (1 - alpha)) * np.log2(np.sum(prob_dist**alpha)) / np.log2(base) + + if kind is not None: + prob_dist = kind(prob_dist) + + renyi_ent = classical_renyi_entropy(prob_dist, alpha, base=base, backend=backend) + + backend.assert_allclose(renyi_ent, target, atol=1e-5) + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) From aa23dbc38d6cd204f78574247f7b48fbfa131429 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 30 Jan 2024 17:48:29 +0400 Subject: [PATCH 075/200] add `alpha = 0` --- src/qibo/quantum_info/entropies.py | 19 +++++++++++-------- tests/test_quantum_info_entropies.py | 6 ++++-- 2 files changed, 15 insertions(+), 10 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index ec869ba9c9..b22246cf5f 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -164,20 +164,20 @@ def classical_renyi_entropy( H_{\\alpha}(\\mathbf{p}) = \\frac{1}{1 - \\alpha} \\, \\log\\left( \\sum_{x} \\, \\mathbf{p}^{\\alpha}(x) \\right) \\, . - For :math:`\\alpha \\in \\{0, 1, \\infty \\}`, it is further defined that - - .. math:: - H_{\\alpha}(\\mathbf{p}) = \\lim_{\\beta \\to \\alpha} \\, H_{\\beta}(\\mathbf{p}) \\, . - A special case is the limit :math:`\\alpha \\to 1`, in which the classical Rényi entropy coincides with the :func:`qibo.quantum_info.entropies.shannon_entropy`. + Another special case is the limit :math:`\\alpha \\to 0`, where the function is + reduced to the :math:`\\log\\left(|\\mathbf{p}|\\right)`, with :math:`|\\mathbf{p}|` + being the support of :math:`\\mathbf{p}`. + + In the limit :math:`\\alpha \\to \\infty`, the function reduces to + :math:`-\\log(\\max_{x}(\\mathbf{p}(x)))`, which is called the + `min-entropy `_. + Args: prob_dist (ndarray): discrete probability distribution. alpha (float or int): order of the Rényi entropy. - If :math:`\\alpha = 1`, defaults to :func:`qibo.quantum_info.entropies.shannon_entropy`. - If :math:`\\alpha = \\infty`, defaults to the - `min-entropy `_. base (float): the base of the log. Defaults to :math:`2`. backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used in the execution. If ``None``, it uses @@ -222,6 +222,9 @@ def classical_renyi_entropy( if np.abs(np.sum(prob_dist) - 1.0) > PRECISION_TOL: raise_error(ValueError, "Probability array must sum to 1.") + if alpha == 0.0: + return np.log2(len(prob_dist)) / np.log2(base) + if alpha == 1.0: return shannon_entropy(prob_dist, base=base, backend=backend) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 4853c2eef1..0153a3b778 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -116,7 +116,7 @@ def test_classical_relative_entropy(backend, base, kind): @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("alpha", [1, 2, 3, np.inf]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) def test_classical_renyi_entropy(backend, alpha, base, kind): with pytest.raises(TypeError): prob = np.array([1.0, 0.0]) @@ -158,7 +158,9 @@ def test_classical_renyi_entropy(backend, alpha, base, kind): prob_dist = np.random.rand(10) prob_dist /= np.sum(prob_dist) - if alpha == 1: + if alpha == 0.0: + target = np.log2(len(prob_dist)) / np.log2(base) + elif alpha == 1: target = shannon_entropy(prob_dist, base=base, backend=backend) elif alpha == 2: target = -1 * np.log2(np.sum(prob_dist**2)) / np.log2(base) From 36f91984803601ff477f215b71b1a3c925547d5a Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 09:07:58 +0400 Subject: [PATCH 076/200] docstring --- src/qibo/quantum_info/entropies.py | 86 ++++++++++++++++++++++++++++-- 1 file changed, 83 insertions(+), 3 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index b22246cf5f..0da8fe2fe2 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -158,7 +158,7 @@ def classical_renyi_entropy( """Calculates the classical Rényi entropy :math:`H_{\\alpha}` of a discrete probability distribution. For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and probability distribution - :math:`\\mathbf{p}`, the Rényi entropy is defined as + :math:`\\mathbf{p}`, the classical Rényi entropy is defined as .. math:: H_{\\alpha}(\\mathbf{p}) = \\frac{1}{1 - \\alpha} \\, \\log\\left( \\sum_{x} @@ -168,8 +168,10 @@ def classical_renyi_entropy( coincides with the :func:`qibo.quantum_info.entropies.shannon_entropy`. Another special case is the limit :math:`\\alpha \\to 0`, where the function is - reduced to the :math:`\\log\\left(|\\mathbf{p}|\\right)`, with :math:`|\\mathbf{p}|` + reduced to :math:`\\log\\left(|\\mathbf{p}|\\right)`, with :math:`|\\mathbf{p}|` being the support of :math:`\\mathbf{p}`. + This is knows as the `Hartley entropy ` + (also known as *Hartley function* or *max-entropy*). In the limit :math:`\\alpha \\to \\infty`, the function reduces to :math:`-\\log(\\max_{x}(\\mathbf{p}(x)))`, which is called the @@ -184,7 +186,7 @@ def classical_renyi_entropy( :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. Returns: - float: Rényi entropy :math:`H_{\\alpha}`. + float: Classical Rényi entropy :math:`H_{\\alpha}`. """ if backend is None: # pragma: no cover backend = GlobalBackend() @@ -423,6 +425,84 @@ def relative_entropy( return float(entropy_state - relative) +def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None): + """Calculates the Rényi entropy :math:`H_{\\alpha}` of a quantum state :math:`\\rho`. + + For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)`, the Rényi entropy is defined as + + .. math:: + H_{\\alpha}(\\rho) = \\frac{1}{1 - \\alpha} \\, \\log\\left( \\rho^{\\alpha} \\right) \\, . + + A special case is the limit :math:`\\alpha \\to 1`, in which the Rényi entropy + coincides with the :func:`qibo.quantum_info.entropies.entropy`. + + Another special case is the limit :math:`\\alpha \\to 0`, where the function is + reduced to :math:`\\log\\left(d\\right)`, with :math:`d = 2^{n}` + being the dimension of the Hilbert space in which ``state`` :math:`\\rho` lives in. + This is knows as the `Hartley entropy _` + (also known as *Hartley function* or *max-entropy*). + + In the limit :math:`\\alpha \\to \\infty`, the function reduces to + :math:`-\\log(\\|\\rho\\|_{\\infty})`, with :math:`\\|\\cdot\\|_{\\infty}` + being the `spectral norm `_. + This is known as the `min-entropy `_. + + Args: + prob_dist (ndarray): discrete probability distribution. + alpha (float or int): order of the Rényi entropy. + base (float): the base of the log. Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Rényi entropy :math:`H_{\\alpha}`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if ( + (len(state.shape) >= 3) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if not isinstance(alpha, (float, int)): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if purity(state) == 1.0: + return 0.0 + + if alpha == 0.0: + return np.log2(len(state)) / np.log2(base) + + if alpha == 1.0: + return entropy(state, base=base, backend=backend) + + if alpha == np.inf: + return ( + -1 + * np.log2(backend.calculate_norm_density_matrix(state, order=2)) + / np.log2(base) + ) + + log = np.log2(np.trace(np.linalg.matrix_power(state, alpha))) + + return (1 / (1 - alpha)) * log / np.log2(base) + + def entanglement_entropy( state, bipartition, From 8e61e250047cf2709a530a5df722bafb64791e13 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 09:28:43 +0400 Subject: [PATCH 077/200] fix bug --- src/qibo/quantum_info/entropies.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 0da8fe2fe2..8c674b37a8 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -482,7 +482,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None if base <= 0.0: raise_error(ValueError, "log base must be non-negative.") - if purity(state) == 1.0: + if abs(purity(state) - 1.0) < PRECISION_TOL: return 0.0 if alpha == 0.0: From 6b7b1af87aec223e97fa68c0981722035641b6a4 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 09:28:48 +0400 Subject: [PATCH 078/200] tests --- tests/test_quantum_info_entropies.py | 42 ++++++++++++++++++++++++++++ 1 file changed, 42 insertions(+) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 0153a3b778..702ce8db2e 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -8,6 +8,7 @@ entanglement_entropy, entropy, relative_entropy, + renyi_entropy, shannon_entropy, ) from qibo.quantum_info.random_ensembles import ( @@ -301,6 +302,47 @@ def test_relative_entropy(backend, base, check_hermitian): ) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +def test_renyi_entropy(backend, alpha, base): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = renyi_entropy(state, alpha=alpha, base=base, backend=backend) + with pytest.raises(TypeError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha="2", base=base, backend=backend) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha=-1, base=base, backend=backend) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha=alpha, base=0, backend=backend) + + state = random_density_matrix(4, backend=backend) + + if alpha == 0.0: + target = np.log2(len(state)) / np.log2(base) + elif alpha == 1.0: + target = entropy(state, base=base, backend=backend) + elif alpha == np.inf: + target = backend.calculate_norm_density_matrix(state, order=2) + target = -1 * np.log2(target) / np.log2(base) + else: + target = np.log2(np.trace(np.linalg.matrix_power(state, alpha))) + target = (1 / (1 - alpha)) * target / np.log2(base) + + backend.assert_allclose( + renyi_entropy(state, alpha=alpha, base=base, backend=backend), target, atol=1e-5 + ) + + # test pure state + state = random_density_matrix(4, pure=True, backend=backend) + backend.assert_allclose( + renyi_entropy(state, alpha=alpha, base=base, backend=backend), 0.0, atol=1e-8 + ) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("bipartition", [[0], [1]]) From 1ed2b39f226a3001f5752979d62e5769fee19b1f Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 10:19:56 +0400 Subject: [PATCH 079/200] api ref --- doc/source/api-reference/qibo.rst | 26 +++++++++++++++++++------- 1 file changed, 19 insertions(+), 7 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 5f80e763c1..9248affd9b 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1271,7 +1271,7 @@ Callbacks Callbacks provide a way to calculate quantities on the state vector as it propagates through the circuit. Example of such quantity is the entanglement entropy, which is currently the only callback implemented in -:class:`qibo.callbacks.EntanglementEntropy`. +:class:`qibo.callbacks.Entanglemententropy`. The user can create custom callbacks by inheriting the :class:`qibo.callbacks.Callback` class. The point each callback is calculated inside the circuit is defined by adding a :class:`qibo.gates.CallbackGate`. @@ -1284,7 +1284,7 @@ This can be added similarly to a standard gate and does not affect the state vec Entanglement entropy ^^^^^^^^^^^^^^^^^^^^ -.. autoclass:: qibo.callbacks.EntanglementEntropy +.. autoclass:: qibo.callbacks.Entanglemententropy :members: :member-order: bysource @@ -1537,18 +1537,24 @@ Shannon entropy .. autofunction:: qibo.quantum_info.shannon_entropy -Classical Relative Entropy +Classical relative entropy """""""""""""""""""""""""" .. autofunction:: qibo.quantum_info.classical_relative_entropy -Classical Rényi Entropy +Classical Rényi entropy """"""""""""""""""""""" .. autofunction:: qibo.quantum_info.classical_renyi_entropy +Classical Rényi relative entropy +"""""""""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.classical_renyi_relative_entropy + + Entropy """"""" @@ -1562,7 +1568,7 @@ Entropy and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. -Relative Entropy +Relative entropy """""""""""""""" .. autofunction:: qibo.quantum_info.relative_entropy @@ -1576,13 +1582,19 @@ Relative Entropy an error will be raised when using `cupy` backend. -Rényi Entropy +Rényi entropy """"""""""""" .. autofunction:: qibo.quantum_info.renyi_entropy -Entanglement Entropy +Rényi relative entropy +"""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.renyi_relative_entropy + + +Entanglement entropy """""""""""""""""""" .. autofunction:: qibo.quantum_info.entanglement_entropy From 6d2fed8fd5c0c89d0c402890fd5fe8567e3d2cb9 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 10:20:10 +0400 Subject: [PATCH 080/200] calssical renyi relative entropy --- src/qibo/quantum_info/entropies.py | 64 ++++++++++++++++++++++++++++++ 1 file changed, 64 insertions(+) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 8c674b37a8..99b04e62a2 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -238,6 +238,70 @@ def classical_renyi_entropy( return renyi_ent +def classical_renyi_relative_entropy( + prob_dist_p, prob_dist_q, alpha: Union[float, int], base: float = 2, backend=None +): + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(prob_dist_p, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) + if isinstance(prob_dist_q, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist_q = backend.cast(prob_dist_q, dtype=np.float64) + + if (len(prob_dist_p.shape) != 1) or (len(prob_dist_q.shape) != 1): + raise_error( + TypeError, + "Probability arrays must have dims (k,) but have " + + f"dims {prob_dist_p.shape} and {prob_dist_q.shape}.", + ) + + if (len(prob_dist_p) == 0) or (len(prob_dist_q) == 0): + raise_error(TypeError, "At least one of the arrays is empty.") + + if not isinstance(alpha, (float, int)): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if (any(prob_dist_p < 0) or any(prob_dist_p > 1.0)) or ( + any(prob_dist_q < 0) or any(prob_dist_q > 1.0) + ): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + if np.abs(np.sum(prob_dist_p) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "First probability array must sum to 1.") + + if np.abs(np.sum(prob_dist_q) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Second probability array must sum to 1.") + + if alpha == 0.5: + return -2 * np.log2(np.sum(np.sqrt(prob_dist_p * prob_dist_q))) / np.log2(base) + + if alpha == 1.0: + return classical_relative_entropy( + prob_dist_p, prob_dist_q, base=base, backend=backend + ) + + if alpha == np.inf: + return np.log2(max(prob_dist_p / prob_dist_q)) / np.log2(base) + + prob_p = prob_dist_p**alpha + prob_q = prob_dist_q ** (1 - alpha) + + return (1 / (alpha - 1)) * np.log2(np.sum(prob_p * prob_q)) / np.log2(base) + + def entropy( state, base: float = 2, From dac736e9589e5f35529a9ac1c72db82536eaf452 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 10:20:23 +0400 Subject: [PATCH 081/200] tests --- tests/test_quantum_info_entropies.py | 98 ++++++++++++++++++++++++++++ 1 file changed, 98 insertions(+) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 702ce8db2e..c12532424c 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -5,6 +5,7 @@ from qibo.quantum_info.entropies import ( classical_relative_entropy, classical_renyi_entropy, + classical_renyi_relative_entropy, entanglement_entropy, entropy, relative_entropy, @@ -115,6 +116,103 @@ def test_classical_relative_entropy(backend, base, kind): backend.assert_allclose(divergence, target, atol=1e-5) +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [0, 1 / 2, 1, 2, 3, np.inf]) +def test_classical_renyi_relative_entropy(backend, alpha, base, kind): + with pytest.raises(TypeError): + prob = np.random.rand(1, 2) + prob_q = np.random.rand(1, 5) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base, backend=backend + ) + with pytest.raises(TypeError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base, backend=backend + ) + with pytest.raises(ValueError): + prob = np.array([-1, 2.0]) + prob_q = np.random.rand(1, 5)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base, backend=backend + ) + with pytest.raises(ValueError): + prob = np.random.rand(1, 2)[0] + prob_q = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base, backend=backend + ) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.random.rand(1, 2)[0] + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base, backend=backend + ) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.array([0.0, 1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha, base=-2, backend=backend + ) + with pytest.raises(TypeError): + prob = np.array([1.0, 0.0]) + prob_q = np.array([0.0, 1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha="1", base=base, backend=backend + ) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob_q = np.array([0.0, 1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + prob_q = backend.cast(prob_q, dtype=prob_q.dtype) + test = classical_renyi_relative_entropy( + prob, prob_q, alpha=-2, base=base, backend=backend + ) + + prob_p = np.random.rand(10) + prob_q = np.random.rand(10) + prob_p /= np.sum(prob_p) + prob_q /= np.sum(prob_q) + + if alpha == 0.5: + target = -2 * np.log2(np.sum(np.sqrt(prob_p * prob_q))) / np.log2(base) + elif alpha == 1.0: + target = classical_relative_entropy(prob_p, prob_q, base=base, backend=backend) + elif alpha == np.inf: + target = np.log2(max(prob_p / prob_q)) / np.log2(base) + else: + target = ( + (1 / (alpha - 1)) + * np.log2(np.sum(prob_p**alpha * prob_q ** (1 - alpha))) + / np.log2(base) + ) + + if kind is not None: + prob_p, prob_q = kind(prob_p), kind(prob_q) + + divergence = classical_renyi_relative_entropy( + prob_p, prob_q, alpha=alpha, base=base, backend=backend + ) + + backend.assert_allclose(divergence, target, atol=1e-5) + + @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) From 5af2fe69948ee3ec925df29a782690b93ad28251 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 10:33:49 +0400 Subject: [PATCH 082/200] docstring --- src/qibo/quantum_info/entropies.py | 38 +++++++++++++++++++++++++++++- 1 file changed, 37 insertions(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 99b04e62a2..94e7c07cd3 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -170,7 +170,7 @@ def classical_renyi_entropy( Another special case is the limit :math:`\\alpha \\to 0`, where the function is reduced to :math:`\\log\\left(|\\mathbf{p}|\\right)`, with :math:`|\\mathbf{p}|` being the support of :math:`\\mathbf{p}`. - This is knows as the `Hartley entropy ` + This is knows as the `Hartley entropy `_ (also known as *Hartley function* or *max-entropy*). In the limit :math:`\\alpha \\to \\infty`, the function reduces to @@ -241,6 +241,42 @@ def classical_renyi_entropy( def classical_renyi_relative_entropy( prob_dist_p, prob_dist_q, alpha: Union[float, int], base: float = 2, backend=None ): + """Calculates the classical Rényi relative entropy between two discrete probability distributions. + + This function is also known as + `Rényi divergence `_. + + For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and probability distributions + :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, the classical Rényi relative entropy is defined as + + .. math:: + H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q}) = \\frac{1}{\\alpha - 1} \\, + \\log\\left( \\sum_{x} \\, \\frac{\\mathbf{p}^{\\alpha}(x)} + {\\mathbf{q}^{\\alpha - 1}(x)} \\right) \\, . + + A special case is the limit :math:`\\alpha \\to 1`, in which the classical Rényi divergence + coincides with the :func:`qibo.quantum_info.entropies.classical_relative_entropy`. + + Another special case is the limit :math:`\\alpha \\to 1/2`, where the function is + reduced to :math:`-2 \\log\\left(\\sum_{x} \\, \\sqrt{\\mathbf{p}(x) \\, \\mathbf{q}(x)} \\right)`. + The sum inside the :math:`\\log` is known as the + `Bhattacharyya coefficient `_. + + In the limit :math:`\\alpha \\to \\infty`, the function reduces to + :math:`\\log(\\max_{x}(\\mathbf{p}(x) \\, \\mathbf{q}(x))`. + + Args: + prob_dist_p (ndarray or list): discrete probability distribution :math:`p`. + prob_dist_q (ndarray or list): discrete probability distribution :math:`q`. + alpha (float or int): order of the Rényi entropy. + base (float): the base of the log. Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Classical Rényi relative entropy :math:`H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q})`. + """ if backend is None: # pragma: no cover backend = GlobalBackend() From d9e95c743d49522e45bf62bc712d39044fe8a841 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 12:26:37 +0400 Subject: [PATCH 083/200] rename function --- doc/source/api-reference/qibo.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 9248affd9b..0018faa93a 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1552,7 +1552,7 @@ Classical Rényi entropy Classical Rényi relative entropy """""""""""""""""""""""""""""""" -.. autofunction:: qibo.quantum_info.classical_renyi_relative_entropy +.. autofunction:: qibo.quantum_info.classical_relative_renyi_entropy Entropy From 39aadcd62e23253964aa26e2ce0bf7e759abc12a Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 12:26:55 +0400 Subject: [PATCH 084/200] relative renyi entropy --- src/qibo/quantum_info/entropies.py | 103 +++++++++++++++++++++++++++-- 1 file changed, 99 insertions(+), 4 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 94e7c07cd3..606be7d221 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -238,16 +238,16 @@ def classical_renyi_entropy( return renyi_ent -def classical_renyi_relative_entropy( +def classical_relative_renyi_entropy( prob_dist_p, prob_dist_q, alpha: Union[float, int], base: float = 2, backend=None ): - """Calculates the classical Rényi relative entropy between two discrete probability distributions. + """Calculates the classical relative Rényi entropy between two discrete probability distributions. This function is also known as `Rényi divergence `_. For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and probability distributions - :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, the classical Rényi relative entropy is defined as + :math:`\\mathbf{p}` and :math:`\\mathbf{q}`, the classical relative Rényi entropy is defined as .. math:: H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q}) = \\frac{1}{\\alpha - 1} \\, @@ -275,7 +275,7 @@ def classical_renyi_relative_entropy( :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. Returns: - float: Classical Rényi relative entropy :math:`H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q})`. + float: Classical relative Rényi entropy :math:`H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q})`. """ if backend is None: # pragma: no cover backend = GlobalBackend() @@ -603,6 +603,101 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None return (1 / (1 - alpha)) * log / np.log2(base) +def relative_renyi_entropy( + state, target, alpha: Union[float, int], base: float = 2, backend=None +): + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if ( + (len(state.shape) >= 3) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if ( + (len(target.shape) >= 3) + or (len(target) == 0) + or (len(target.shape) == 2 and target.shape[0] != target.shape[1]) + ): + raise_error( + TypeError, + f"target must have dims either (k,) or (k,k), but have dims {target.shape}.", + ) + + if not isinstance(alpha, (float, int)): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if ( + abs(purity(state) - 1.0) < PRECISION_TOL + and abs(purity(target) - 1) < PRECISION_TOL + ): + return 0.0 + + if alpha == 1.0: + return relative_entropy(state, target, base, backend=backend) + + if alpha == np.inf: + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + eigenvalues_state, eigenvectors_state = np.linalg.eigh(state) + new_state = np.zeros_like(state, dtype=complex) + new_state = backend.cast(new_state, dtype=new_state.dtype) + for eigenvalue, eigenstate in zip( + eigenvalues_state, np.transpose(eigenvectors_state) + ): + new_state += np.sqrt(eigenvalue) * np.outer( + eigenstate, np.conj(eigenstate) + ) + + eigenvalues_target, eigenvectors_target = np.linalg.eigh(target) + new_target = np.zeros_like(target, dtype=complex) + new_target = backend.cast(new_target, dtype=new_target.dtype) + for eigenvalue, eigenstate in zip( + eigenvalues_target, np.transpose(eigenvectors_target) + ): + new_target += np.sqrt(eigenstate) * np.outer( + eigenstate, np.conj(eigenstate) + ) + else: + from scipy.linalg import sqrtm # pylint: disable=C0415 + + # astype method needed because of tensorflow + new_state = sqrtm(state).astype("complex128") + new_target = sqrtm(target).astype("complex128") + new_state = backend.cast(new_state, dtype=new_state.dtype) + new_target = backend.cast(new_target, dtype=new_target.dtype) + + log = np.log2( + backend.calculate_norm_density_matrix(new_state @ new_target, order=1) + ) + + return -2 * log / np.log2(base) + + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) + + log = np.linalg.matrix_power(state, alpha) + log = log @ np.linalg.matrix_power(target, 1 - alpha) + log = np.log2(np.trace(log)) + + return (1 / (alpha - 1)) * log / np.log2(base) + + def entanglement_entropy( state, bipartition, From 0c4b75a91e37aea94fec2647a6f0156424b99ed7 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 12:26:59 +0400 Subject: [PATCH 085/200] tests --- tests/test_quantum_info_entropies.py | 122 ++++++++++++++++++++++++--- 1 file changed, 111 insertions(+), 11 deletions(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index c12532424c..c7e7ebdf9b 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -1,14 +1,16 @@ import numpy as np import pytest +from scipy.linalg import sqrtm from qibo.config import PRECISION_TOL from qibo.quantum_info.entropies import ( classical_relative_entropy, + classical_relative_renyi_entropy, classical_renyi_entropy, - classical_renyi_relative_entropy, entanglement_entropy, entropy, relative_entropy, + relative_renyi_entropy, renyi_entropy, shannon_entropy, ) @@ -119,13 +121,13 @@ def test_classical_relative_entropy(backend, base, kind): @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("alpha", [0, 1 / 2, 1, 2, 3, np.inf]) -def test_classical_renyi_relative_entropy(backend, alpha, base, kind): +def test_classical_relative_renyi_entropy(backend, alpha, base, kind): with pytest.raises(TypeError): prob = np.random.rand(1, 2) prob_q = np.random.rand(1, 5) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base, backend=backend ) with pytest.raises(TypeError): @@ -133,7 +135,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.array([]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base, backend=backend ) with pytest.raises(ValueError): @@ -141,7 +143,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.random.rand(1, 5)[0] prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base, backend=backend ) with pytest.raises(ValueError): @@ -149,7 +151,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base, backend=backend ) with pytest.raises(ValueError): @@ -157,7 +159,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.random.rand(1, 2)[0] prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base, backend=backend ) with pytest.raises(ValueError): @@ -165,7 +167,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.array([0.0, 1.0]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha, base=-2, backend=backend ) with pytest.raises(TypeError): @@ -173,7 +175,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.array([0.0, 1.0]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha="1", base=base, backend=backend ) with pytest.raises(ValueError): @@ -181,7 +183,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): prob_q = np.array([0.0, 1.0]) prob = backend.cast(prob, dtype=prob.dtype) prob_q = backend.cast(prob_q, dtype=prob_q.dtype) - test = classical_renyi_relative_entropy( + test = classical_relative_renyi_entropy( prob, prob_q, alpha=-2, base=base, backend=backend ) @@ -206,7 +208,7 @@ def test_classical_renyi_relative_entropy(backend, alpha, base, kind): if kind is not None: prob_p, prob_q = kind(prob_p), kind(prob_q) - divergence = classical_renyi_relative_entropy( + divergence = classical_relative_renyi_entropy( prob_p, prob_q, alpha=alpha, base=base, backend=backend ) @@ -441,6 +443,104 @@ def test_renyi_entropy(backend, alpha, base): ) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +def test_relative_renyi_entropy(backend, alpha, base): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + target = random_density_matrix(4, backend=backend) + test = relative_renyi_entropy( + state, target, alpha=alpha, base=base, backend=backend + ) + with pytest.raises(TypeError): + target = np.random.rand(2, 3) + target = backend.cast(target, dtype=target.dtype) + state = random_density_matrix(4, backend=backend) + test = relative_renyi_entropy( + state, target, alpha=alpha, base=base, backend=backend + ) + with pytest.raises(TypeError): + state = random_statevector(4, backend=backend) + target = random_statevector(4, backend=backend) + test = relative_renyi_entropy( + state, target, alpha="2", base=base, backend=backend + ) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + target = random_statevector(4, backend=backend) + test = relative_renyi_entropy( + state, target, alpha=-1, base=base, backend=backend + ) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + target = random_statevector(4, backend=backend) + test = relative_renyi_entropy( + state, target, alpha=alpha, base=0, backend=backend + ) + + state = random_density_matrix(4, backend=backend) + target = random_density_matrix(4, backend=backend) + + if alpha == 1.0: + log = relative_entropy(state, target, base, backend=backend) + elif alpha == np.inf: + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + eigenvalues_state, eigenvectors_state = np.linalg.eigh(state) + new_state = np.zeros_like(state, dtype=complex) + new_state = backend.cast(new_state, dtype=new_state.dtype) + for eigenvalue, eigenstate in zip( + eigenvalues_state, np.transpose(eigenvectors_state) + ): + new_state += np.sqrt(eigenvalue) * np.outer( + eigenstate, np.conj(eigenstate) + ) + + eigenvalues_target, eigenvectors_target = np.linalg.eigh(target) + new_target = np.zeros_like(target, dtype=complex) + new_target = backend.cast(new_target, dtype=new_target.dtype) + for eigenvalue, eigenstate in zip( + eigenvalues_target, np.transpose(eigenvectors_target) + ): + new_target += np.sqrt(eigenstate) * np.outer( + eigenstate, np.conj(eigenstate) + ) + else: + new_state, new_target = sqrtm(state).astype("complex128"), sqrtm( + target + ).astype("complex128") + new_state = backend.cast(new_state, dtype=new_state.dtype) + new_target = backend.cast(new_target, dtype=new_target.dtype) + + log = np.log2( + backend.calculate_norm_density_matrix(new_state @ new_target, order=1) + ) + + log = -2 * log / np.log2(base) + + else: + log = np.linalg.matrix_power(state, alpha) + log = log @ np.linalg.matrix_power(target, 1 - alpha) + log = np.log2(np.trace(log)) + + log = (1 / (alpha - 1)) * log / np.log2(base) + + backend.assert_allclose( + relative_renyi_entropy(state, target, alpha=alpha, base=base, backend=backend), + log, + atol=1e-5, + ) + + # test pure states + state = random_density_matrix(4, pure=True, backend=backend) + target = random_density_matrix(4, pure=True, backend=backend) + backend.assert_allclose( + relative_renyi_entropy(state, target, alpha=alpha, base=base, backend=backend), + 0.0, + atol=1e-8, + ) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("bipartition", [[0], [1]]) From 5fea3d1d9bb8d83eaea0d517947ae8930f27bc86 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 12:48:43 +0400 Subject: [PATCH 086/200] docstring --- src/qibo/quantum_info/entropies.py | 33 +++++++++++++++++++++++++++++- 1 file changed, 32 insertions(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 606be7d221..3abdb3755b 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -548,7 +548,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None This is known as the `min-entropy `_. Args: - prob_dist (ndarray): discrete probability distribution. + state (ndarray): statevector or density matrix. alpha (float or int): order of the Rényi entropy. base (float): the base of the log. Defaults to :math:`2`. backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be @@ -606,6 +606,37 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None def relative_renyi_entropy( state, target, alpha: Union[float, int], base: float = 2, backend=None ): + """Calculates the relative Rényi entropy between two quantum states. + + For :math:`\\alpha \\in (0, \\, 1) \\cup (1, \\, \\infty)` and quantum states + :math:`\\rho` and :math:`\\sigma`, the relative Rényi entropy is defined as + + .. math:: + H_{\\alpha}(\\rho \\, \\| \\, \\sigma) = \\frac{1}{\\alpha - 1} \\, + \\log\\left( \\textup{tr}\\left( \\rho^{\\alpha} \\, + \\sigma^{1 - \\alpha} \\right) \\right) \\, . + + A special case is the limit :math:`\\alpha \\to 1`, in which the Rényi entropy + coincides with the :func:`qibo.quantum_info.entropies.relative_entropy`. + + In the limit :math:`\\alpha \\to \\infty`, the function reduces to + :math:`-2 \\, \\log(\\|\\sqrt{\\rho} \\, \\sqrt{\\sigma}\\|_{1})`, + with :math:`\\|\\cdot\\|_{1}` being the + `Schatten 1-norm `_. + This is known as the `min-relative entropy `_. + + Args: + state (ndarray): statevector or density matrix :math:`\\rho`. + target (ndarray): statevector or density matrix :math:`\\sigma`. + alpha (float or int): order of the Rényi entropy. + base (float): the base of the log. Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Relative Rényi entropy :math:`H_{\\alpha}(\\rho \\, \\| \\, \\sigma)`. + """ if backend is None: # pragma: no cover backend = GlobalBackend() From bd994ecaebf33322c70447ad20a973401754a31b Mon Sep 17 00:00:00 2001 From: Rahul Arvind Date: Wed, 31 Jan 2024 17:24:26 +0800 Subject: [PATCH 087/200] Explicitly add the fixture --- pyproject.toml | 6 +++++- src/qibo/models/qcnn.py | 2 +- tests/test_models_qcnn.py | 9 +++------ 3 files changed, 9 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 61641cc190..fd67a76f28 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "qibo" -version = "0.2.4" +version = "0.2.5" description = "A framework for quantum computing with hardware acceleration." authors = ["The Qibo team"] license = "Apache License 2.0" @@ -95,3 +95,7 @@ output-format = "colorized" [tool.pytest.ini_options] testpaths = ['tests/'] filterwarnings = ['ignore::RuntimeWarning'] + +addopts = [ + '--durations=60', +] \ No newline at end of file diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 640904e6ee..48d4104e05 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -51,7 +51,7 @@ def __init__( nlayers, nclasses=2, params=None, - twoqubitansatz=None, + twoqubitansatz = None, copy_init_state=None, ): self.nclasses = nclasses diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 1f8d853c72..34f92da826 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -11,13 +11,8 @@ angles0 = [i * math.pi / num_angles for i in range(num_angles)] -def test_classifier_circuit2(backend, capsys): +def test_classifier_circuit2(backend): """ """ - - with capsys.disabled(): - backender = get_backend() - print(str(backender)) - nqubits = 2 nlayers = int(nqubits / 2) init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # @@ -373,6 +368,7 @@ def test_two_qubit_ansatz(backend): c.add(gates.CNOT(1, 0)) test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_qcnn_training(backend): import random @@ -403,6 +399,7 @@ def test_qcnn_training(backend): predictions.append(1) labels = np.array([[1], [-1], [1]]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_two_qubit_ansatz_training(backend): c = Circuit(2) From fd5c1ea7bffbf62c6b50ccdb9cbc5b89aa998005 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 13:49:27 +0400 Subject: [PATCH 088/200] fix test and coverage --- src/qibo/quantum_info/entropies.py | 23 ++++++++++++++++------- tests/test_quantum_info_entropies.py | 25 ++++++++++++++++++++++--- 2 files changed, 38 insertions(+), 10 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 3abdb3755b..a2ef64899a 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -483,6 +483,12 @@ def relative_entropy( if purity(state) == 1.0 and purity(target) == 1.0: return 0.0 + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) + if not check_hermitian or _check_hermitian_or_not_gpu(state, backend=backend): eigenvalues_state = np.linalg.eigvalsh(state) else: @@ -677,11 +683,20 @@ def relative_renyi_entropy( ): return 0.0 + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) + if alpha == 1.0: return relative_entropy(state, target, base, backend=backend) if alpha == np.inf: - if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + if backend.__class__.__name__ in [ + "CupyBackend", + "CuQuantumBackend", + ]: # pragma: no cover eigenvalues_state, eigenvectors_state = np.linalg.eigh(state) new_state = np.zeros_like(state, dtype=complex) new_state = backend.cast(new_state, dtype=new_state.dtype) @@ -716,12 +731,6 @@ def relative_renyi_entropy( return -2 * log / np.log2(base) - if len(state.shape) == 1: - state = np.outer(state, np.conj(state)) - - if len(target.shape) == 1: - target = np.outer(target, np.conj(target)) - log = np.linalg.matrix_power(state, alpha) log = log @ np.linalg.matrix_power(target, 1 - alpha) log = np.log2(np.trace(log)) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index c7e7ebdf9b..bc2ec4abab 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -443,9 +443,12 @@ def test_renyi_entropy(backend, alpha, base): ) +@pytest.mark.parametrize( + ["state_flag", "target_flag"], [[True, True], [False, True], [True, False]] +) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) -def test_relative_renyi_entropy(backend, alpha, base): +def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): with pytest.raises(TypeError): state = np.random.rand(2, 3) state = backend.cast(state, dtype=state.dtype) @@ -479,8 +482,12 @@ def test_relative_renyi_entropy(backend, alpha, base): state, target, alpha=alpha, base=0, backend=backend ) - state = random_density_matrix(4, backend=backend) - target = random_density_matrix(4, backend=backend) + state = ( + random_statevector(4, backend=backend) + if state_flag + else random_density_matrix(4, backend=backend) + ) + target = backend.identity_density_matrix(2, normalize=True) if alpha == 1.0: log = relative_entropy(state, target, base, backend=backend) @@ -506,6 +513,12 @@ def test_relative_renyi_entropy(backend, alpha, base): eigenstate, np.conj(eigenstate) ) else: + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) + new_state, new_target = sqrtm(state).astype("complex128"), sqrtm( target ).astype("complex128") @@ -519,6 +532,12 @@ def test_relative_renyi_entropy(backend, alpha, base): log = -2 * log / np.log2(base) else: + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) + + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) + log = np.linalg.matrix_power(state, alpha) log = log @ np.linalg.matrix_power(target, 1 - alpha) log = np.log2(np.trace(log)) From 40e39d195149292dce4d8f2ef3dc354c26152b97 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 31 Jan 2024 09:56:10 +0000 Subject: [PATCH 089/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- pyproject.toml | 2 +- src/qibo/models/qcnn.py | 2 +- tests/test_models_qcnn.py | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 0e40057c74..bb2b539695 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -101,4 +101,4 @@ addopts = [ '--cov-report=xml', '--cov-report=html', '--durations=60', -] \ No newline at end of file +] diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 48d4104e05..640904e6ee 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -51,7 +51,7 @@ def __init__( nlayers, nclasses=2, params=None, - twoqubitansatz = None, + twoqubitansatz=None, copy_init_state=None, ): self.nclasses = nclasses diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 34f92da826..9e5d262871 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -368,8 +368,8 @@ def test_two_qubit_ansatz(backend): c.add(gates.CNOT(1, 0)) test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_qcnn_training(backend): import random @@ -399,8 +399,8 @@ def test_qcnn_training(backend): predictions.append(1) labels = np.array([[1], [-1], [1]]) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_two_qubit_ansatz_training(backend): c = Circuit(2) c.add(gates.H(0)) From 37e9d6da1013ee3468a6fdd489cb791c4b1c7522 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 14:45:12 +0400 Subject: [PATCH 090/200] entropies and tests --- src/qibo/quantum_info/entropies.py | 121 ++++++++++++++++++++++ tests/test_quantum_info_entropies.py | 144 ++++++++++++++++++++++----- 2 files changed, 242 insertions(+), 23 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index a2ef64899a..fcc20fff8c 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -338,6 +338,72 @@ def classical_relative_renyi_entropy( return (1 / (alpha - 1)) * np.log2(np.sum(prob_p * prob_q)) / np.log2(base) +def classical_tsallis_entropy(prob_dist, alpha: float, base: float = 2, backend=None): + """Calculates the classical Tsallis entropy for a discrete probability distribution. + + This is defined as + + .. math:: + S_{\\alpha}(\\mathbf{p}) = \\frac{1}{\\alpha - 1} \\, + \\left(1 - \\sum_{x} \\, \\mathbf{p}^{\\alpha}(x) \\right) + + Args: + prob_dist (ndarray): discrete probability distribution. + alpha (float or int): entropic index. + base (float): the base of the log. Used when ``alpha=1.0``. + Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be + used in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Classical Tsallis entropy :math:`S_{\\alpha}(\\mathbf{p})`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if isinstance(prob_dist, list): + # np.float64 is necessary instead of native float because of tensorflow + prob_dist = backend.cast(prob_dist, dtype=np.float64) + + if not isinstance(alpha, (float, int)): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0: + raise_error(ValueError, "log base must be non-negative.") + + if len(prob_dist.shape) != 1: + raise_error( + TypeError, + f"Probability array must have dims (k,) but it has {prob_dist.shape}.", + ) + + if len(prob_dist) == 0: + raise_error(TypeError, "Empty array.") + + if any(prob_dist < 0) or any(prob_dist > 1.0): + raise_error( + ValueError, + "All elements of the probability array must be between 0. and 1..", + ) + + if np.abs(np.sum(prob_dist) - 1.0) > PRECISION_TOL: + raise_error(ValueError, "Probability array must sum to 1.") + + if alpha == 1.0: + return shannon_entropy(prob_dist, base=base, backend=backend) + + if isinstance(prob_dist, list): + prob_dist = backend.cast(prob_dist, dtype=np.float64) + + return (1 / (1 - alpha)) * (np.sum(prob_dist**alpha) - 1) + + def entropy( state, base: float = 2, @@ -738,6 +804,61 @@ def relative_renyi_entropy( return (1 / (alpha - 1)) * log / np.log2(base) +def tsallis_entropy(state, alpha: float, base: float = 2, backend=None): + """Calculates the Tsallis entropy of a quantum state. + + .. math:: + S_{\\alpha}(\\rho) = \\frac{1}{1 - \\alpha} \\, + \\left( \\text{tr}(\\rho^{\\alpha}) - 1 \\right) + + When :math:`\\alpha = 1`, the functions defaults to + :func:`qibo.quantum_info.entropies.entropy`. + + Args: + state (ndarray): statevector or density matrix. + alpha (float or int): entropic index. + base (float, optional): the base of the log. Used when ``alpha=1.0``. + Defaults to :math:`2`. + backend (:class:`qibo.backends.abstract.Backend`, optional): backend to be used + in the execution. If ``None``, it uses + :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + Returns: + float: Tsallis entropy :math:`S_{\\alpha}(\\rho)`. + """ + if backend is None: # pragma: no cover + backend = GlobalBackend() + + if ( + (len(state.shape) >= 3) + or (len(state) == 0) + or (len(state.shape) == 2 and state.shape[0] != state.shape[1]) + ): + raise_error( + TypeError, + f"state must have dims either (k,) or (k,k), but have dims {state.shape}.", + ) + + if not isinstance(alpha, (float, int)): + raise_error( + TypeError, f"alpha must be type float, but it is type {type(alpha)}." + ) + + if alpha < 0.0: + raise_error(ValueError, "alpha must a non-negative float.") + + if base <= 0.0: + raise_error(ValueError, "log base must be non-negative.") + + if abs(purity(state) - 1.0) < PRECISION_TOL: + return 0.0 + + if alpha == 1.0: + return entropy(state, base=base, backend=backend) + + return (1 / (1 - alpha)) * (np.trace(np.linalg.matrix_power(state, alpha)) - 1) + + def entanglement_entropy( state, bipartition, diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index bc2ec4abab..0bcca2e087 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -7,12 +7,14 @@ classical_relative_entropy, classical_relative_renyi_entropy, classical_renyi_entropy, + classical_tsallis_entropy, entanglement_entropy, entropy, relative_entropy, relative_renyi_entropy, renyi_entropy, shannon_entropy, + tsallis_entropy, ) from qibo.quantum_info.random_ensembles import ( random_density_matrix, @@ -118,6 +120,69 @@ def test_classical_relative_entropy(backend, base, kind): backend.assert_allclose(divergence, target, atol=1e-5) +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +def test_classical_renyi_entropy(backend, alpha, base, kind): + with pytest.raises(TypeError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha="2", backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha=-2, backend=backend) + with pytest.raises(TypeError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, base="2", backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, base=-2, backend=backend) + with pytest.raises(TypeError): + prob = np.array([[1.0], [0.0]]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(TypeError): + prob = np.array([]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.0, -1.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([1.1, 0.0]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + with pytest.raises(ValueError): + prob = np.array([0.5, 0.4999999]) + prob = backend.cast(prob, dtype=prob.dtype) + test = classical_renyi_entropy(prob, alpha, backend=backend) + + prob_dist = np.random.rand(10) + prob_dist /= np.sum(prob_dist) + + if alpha == 0.0: + target = np.log2(len(prob_dist)) / np.log2(base) + elif alpha == 1: + target = shannon_entropy(prob_dist, base=base, backend=backend) + elif alpha == 2: + target = -1 * np.log2(np.sum(prob_dist**2)) / np.log2(base) + elif alpha == np.inf: + target = -1 * np.log2(max(prob_dist)) / np.log2(base) + else: + target = (1 / (1 - alpha)) * np.log2(np.sum(prob_dist**alpha)) / np.log2(base) + + if kind is not None: + prob_dist = kind(prob_dist) + + renyi_ent = classical_renyi_entropy(prob_dist, alpha, base=base, backend=backend) + + backend.assert_allclose(renyi_ent, target, atol=1e-5) + + @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("alpha", [0, 1 / 2, 1, 2, 3, np.inf]) @@ -217,65 +282,61 @@ def test_classical_relative_renyi_entropy(backend, alpha, base, kind): @pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) -def test_classical_renyi_entropy(backend, alpha, base, kind): +@pytest.mark.parametrize("alpha", [0, 1, 2, 3]) +def test_classical_tsallis_entropy(backend, alpha, base, kind): with pytest.raises(TypeError): prob = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha="2", backend=backend) + test = classical_tsallis_entropy(prob, alpha="2", backend=backend) with pytest.raises(ValueError): prob = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha=-2, backend=backend) + test = classical_tsallis_entropy(prob, alpha=-2, backend=backend) with pytest.raises(TypeError): prob = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, base="2", backend=backend) + test = classical_tsallis_entropy(prob, alpha, base="2", backend=backend) with pytest.raises(ValueError): prob = np.array([1.0, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, base=-2, backend=backend) + test = classical_tsallis_entropy(prob, alpha, base=-2, backend=backend) with pytest.raises(TypeError): prob = np.array([[1.0], [0.0]]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, backend=backend) + test = classical_tsallis_entropy(prob, alpha, backend=backend) with pytest.raises(TypeError): prob = np.array([]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, backend=backend) + test = classical_tsallis_entropy(prob, alpha, backend=backend) with pytest.raises(ValueError): prob = np.array([1.0, -1.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, backend=backend) + test = classical_tsallis_entropy(prob, alpha, backend=backend) with pytest.raises(ValueError): prob = np.array([1.1, 0.0]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, backend=backend) + test = classical_tsallis_entropy(prob, alpha, backend=backend) with pytest.raises(ValueError): prob = np.array([0.5, 0.4999999]) prob = backend.cast(prob, dtype=prob.dtype) - test = classical_renyi_entropy(prob, alpha, backend=backend) + test = classical_tsallis_entropy(prob, alpha, backend=backend) prob_dist = np.random.rand(10) prob_dist /= np.sum(prob_dist) - if alpha == 0.0: - target = np.log2(len(prob_dist)) / np.log2(base) - elif alpha == 1: + if alpha == 1.0: target = shannon_entropy(prob_dist, base=base, backend=backend) - elif alpha == 2: - target = -1 * np.log2(np.sum(prob_dist**2)) / np.log2(base) - elif alpha == np.inf: - target = -1 * np.log2(max(prob_dist)) / np.log2(base) else: - target = (1 / (1 - alpha)) * np.log2(np.sum(prob_dist**alpha)) / np.log2(base) + target = (1 / (1 - alpha)) * (np.sum(prob_dist**alpha) - 1) if kind is not None: prob_dist = kind(prob_dist) - renyi_ent = classical_renyi_entropy(prob_dist, alpha, base=base, backend=backend) - - backend.assert_allclose(renyi_ent, target, atol=1e-5) + backend.assert_allclose( + classical_tsallis_entropy(prob_dist, alpha=alpha, base=base, backend=backend), + target, + atol=1e-5, + ) @pytest.mark.parametrize("check_hermitian", [False, True]) @@ -487,7 +548,11 @@ def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): if state_flag else random_density_matrix(4, backend=backend) ) - target = backend.identity_density_matrix(2, normalize=True) + target = ( + random_statevector(4, backend=backend) + if target_flag + else random_density_matrix(4, backend=backend) + ) if alpha == 1.0: log = relative_entropy(state, target, base, backend=backend) @@ -560,6 +625,39 @@ def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): ) +@pytest.mark.parametrize("base", [2, 10, np.e, 5]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +def test_tsallis_entropy(backend, alpha, base): + with pytest.raises(TypeError): + state = np.random.rand(2, 3) + state = backend.cast(state, dtype=state.dtype) + test = renyi_entropy(state, alpha=alpha, base=base, backend=backend) + with pytest.raises(TypeError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha="2", base=base, backend=backend) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha=-1, base=base, backend=backend) + with pytest.raises(ValueError): + state = random_statevector(4, backend=backend) + test = renyi_entropy(state, alpha=alpha, base=0, backend=backend) + + state = random_density_matrix(4, backend=backend) + + if alpha == 1.0: + target = entropy(state, base=base, backend=backend) + else: + target = (1 / (1 - alpha)) * ( + np.trace(np.linalg.matrix_power(state, alpha)) - 1 + ) + + backend.assert_allclose( + tsallis_entropy(state, alpha=alpha, base=base, backend=backend), + target, + atol=1e-5, + ) + + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) @pytest.mark.parametrize("bipartition", [[0], [1]]) From c4a6bf1086fb311491bb38cf9f8217e95a2aa9fd Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 14:47:15 +0400 Subject: [PATCH 091/200] api ref --- doc/source/api-reference/qibo.rst | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 964267ce4c..8dbf57a43d 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1555,6 +1555,12 @@ Classical Rényi relative entropy .. autofunction:: qibo.quantum_info.classical_relative_renyi_entropy +Classical Tsallis entropy +""""""""""""""""""""""""" + +.. autofunction:: qibo.quantum_info.classical_tsallis_entropy + + Entropy """"""" @@ -1594,6 +1600,12 @@ Rényi relative entropy .. autofunction:: qibo.quantum_info.renyi_relative_entropy +Tsallis entropy +""""""""""""""" + +.. autofunction:: qibo.quantum_info.tsallis_entropy + + Entanglement entropy """""""""""""""""""" From 9a0b3156915b8514df483fd1b5cb07d9b58547d3 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 14:48:45 +0400 Subject: [PATCH 092/200] fix doc bug --- doc/source/api-reference/qibo.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 8dbf57a43d..936ff6ba90 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1271,7 +1271,7 @@ Callbacks Callbacks provide a way to calculate quantities on the state vector as it propagates through the circuit. Example of such quantity is the entanglement entropy, which is currently the only callback implemented in -:class:`qibo.callbacks.Entanglemententropy`. +:class:`qibo.callbacks.EntanglementEntropy`. The user can create custom callbacks by inheriting the :class:`qibo.callbacks.Callback` class. The point each callback is calculated inside the circuit is defined by adding a :class:`qibo.gates.CallbackGate`. @@ -1284,7 +1284,7 @@ This can be added similarly to a standard gate and does not affect the state vec Entanglement entropy ^^^^^^^^^^^^^^^^^^^^ -.. autoclass:: qibo.callbacks.Entanglemententropy +.. autoclass:: qibo.callbacks.EntanglementEntropy :members: :member-order: bysource From 7eab0724727ecbbc8789718a604c33bfa3326f1b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 31 Jan 2024 10:52:45 +0000 Subject: [PATCH 093/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/quantum_info/entropies.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index fcc20fff8c..73b89df413 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -1,4 +1,5 @@ """Submodule with entropy measures.""" + from typing import Union import numpy as np From 03b7d6d103d461a2de7039bf825ceac143151317 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 31 Jan 2024 15:53:23 +0400 Subject: [PATCH 094/200] fix multiple issues --- src/qibo/quantum_info/entropies.py | 75 +++++++++++---------- tests/test_quantum_info_entropies.py | 97 ++++++++++++---------------- 2 files changed, 76 insertions(+), 96 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 73b89df413..f1b3e08a68 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -3,6 +3,7 @@ from typing import Union import numpy as np +from scipy.linalg import fractional_matrix_power from qibo.backends import GlobalBackend from qibo.config import PRECISION_TOL, raise_error @@ -671,7 +672,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None / np.log2(base) ) - log = np.log2(np.trace(np.linalg.matrix_power(state, alpha))) + log = np.log2(np.trace(_matrix_power(state, alpha, backend))) return (1 / (1 - alpha)) * log / np.log2(base) @@ -698,6 +699,12 @@ def relative_renyi_entropy( `Schatten 1-norm `_. This is known as the `min-relative entropy `_. + .. note:: + Function raises ``NotImplementedError`` when ``target`` :math:`sigma` + is a pure state and :math:`\\alpha > 1`. This is due to the fact that + it is not possible to calculate :math:`\\sigma^{1 - \\alpha}` when + :math:`\\alpha > 1` and :math:`\\sigma` is a projector, i.e. a singular matrix. + Args: state (ndarray): statevector or density matrix :math:`\\rho`. target (ndarray): statevector or density matrix :math:`\\sigma`. @@ -744,53 +751,28 @@ def relative_renyi_entropy( if base <= 0.0: raise_error(ValueError, "log base must be non-negative.") + purity_target = purity(target) if ( abs(purity(state) - 1.0) < PRECISION_TOL - and abs(purity(target) - 1) < PRECISION_TOL + and abs(purity_target - 1) < PRECISION_TOL ): return 0.0 + if alpha > 1.0 and abs(purity_target - 1) < PRECISION_TOL: + raise_error( + NotImplementedError, + "It is not possible to invert a singular matrix. ``target`` is a pure state and alpha > 1.", + ) + if len(state.shape) == 1: state = np.outer(state, np.conj(state)) - if len(target.shape) == 1: - target = np.outer(target, np.conj(target)) - if alpha == 1.0: return relative_entropy(state, target, base, backend=backend) if alpha == np.inf: - if backend.__class__.__name__ in [ - "CupyBackend", - "CuQuantumBackend", - ]: # pragma: no cover - eigenvalues_state, eigenvectors_state = np.linalg.eigh(state) - new_state = np.zeros_like(state, dtype=complex) - new_state = backend.cast(new_state, dtype=new_state.dtype) - for eigenvalue, eigenstate in zip( - eigenvalues_state, np.transpose(eigenvectors_state) - ): - new_state += np.sqrt(eigenvalue) * np.outer( - eigenstate, np.conj(eigenstate) - ) - - eigenvalues_target, eigenvectors_target = np.linalg.eigh(target) - new_target = np.zeros_like(target, dtype=complex) - new_target = backend.cast(new_target, dtype=new_target.dtype) - for eigenvalue, eigenstate in zip( - eigenvalues_target, np.transpose(eigenvectors_target) - ): - new_target += np.sqrt(eigenstate) * np.outer( - eigenstate, np.conj(eigenstate) - ) - else: - from scipy.linalg import sqrtm # pylint: disable=C0415 - - # astype method needed because of tensorflow - new_state = sqrtm(state).astype("complex128") - new_target = sqrtm(target).astype("complex128") - new_state = backend.cast(new_state, dtype=new_state.dtype) - new_target = backend.cast(new_target, dtype=new_target.dtype) + new_state = _matrix_power(state, 0.5, backend) + new_target = _matrix_power(target, 0.5, backend) log = np.log2( backend.calculate_norm_density_matrix(new_state @ new_target, order=1) @@ -798,8 +780,8 @@ def relative_renyi_entropy( return -2 * log / np.log2(base) - log = np.linalg.matrix_power(state, alpha) - log = log @ np.linalg.matrix_power(target, 1 - alpha) + log = _matrix_power(state, alpha, backend) + log = log @ _matrix_power(target, 1 - alpha, backend) log = np.log2(np.trace(log)) return (1 / (alpha - 1)) * log / np.log2(base) @@ -857,7 +839,7 @@ def tsallis_entropy(state, alpha: float, base: float = 2, backend=None): if alpha == 1.0: return entropy(state, base=base, backend=backend) - return (1 / (1 - alpha)) * (np.trace(np.linalg.matrix_power(state, alpha)) - 1) + return (1 / (1 - alpha)) * (np.trace(_matrix_power(state, alpha, backend)) - 1) def entanglement_entropy( @@ -925,3 +907,18 @@ def entanglement_entropy( ) return entropy_entanglement + + +def _matrix_power(matrix, alpha, backend): + """Calculates ``matrix ** alpha`` according to backend.""" + if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + new_matrix = backend.to_numpy(matrix) + else: + new_matrix = np.copy(matrix) + + if len(new_matrix.shape) == 1: + new_matrix = np.outer(new_matrix, np.conj(new_matrix)) + + new_matrix = fractional_matrix_power(new_matrix, alpha) + + return backend.cast(new_matrix, dtype=new_matrix.dtype) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index 0bcca2e087..d709f76056 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -4,6 +4,7 @@ from qibo.config import PRECISION_TOL from qibo.quantum_info.entropies import ( + _matrix_power, classical_relative_entropy, classical_relative_renyi_entropy, classical_renyi_entropy, @@ -508,7 +509,7 @@ def test_renyi_entropy(backend, alpha, base): ["state_flag", "target_flag"], [[True, True], [False, True], [True, False]] ) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, 5.4, np.inf]) def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): with pytest.raises(TypeError): state = np.random.rand(2, 3) @@ -554,66 +555,48 @@ def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): else random_density_matrix(4, backend=backend) ) - if alpha == 1.0: - log = relative_entropy(state, target, base, backend=backend) - elif alpha == np.inf: - if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: - eigenvalues_state, eigenvectors_state = np.linalg.eigh(state) - new_state = np.zeros_like(state, dtype=complex) - new_state = backend.cast(new_state, dtype=new_state.dtype) - for eigenvalue, eigenstate in zip( - eigenvalues_state, np.transpose(eigenvectors_state) - ): - new_state += np.sqrt(eigenvalue) * np.outer( - eigenstate, np.conj(eigenstate) - ) - - eigenvalues_target, eigenvectors_target = np.linalg.eigh(target) - new_target = np.zeros_like(target, dtype=complex) - new_target = backend.cast(new_target, dtype=new_target.dtype) - for eigenvalue, eigenstate in zip( - eigenvalues_target, np.transpose(eigenvectors_target) - ): - new_target += np.sqrt(eigenstate) * np.outer( - eigenstate, np.conj(eigenstate) - ) - else: - if len(state.shape) == 1: - state = np.outer(state, np.conj(state)) - - if len(target.shape) == 1: - target = np.outer(target, np.conj(target)) - - new_state, new_target = sqrtm(state).astype("complex128"), sqrtm( - target - ).astype("complex128") - new_state = backend.cast(new_state, dtype=new_state.dtype) - new_target = backend.cast(new_target, dtype=new_target.dtype) - - log = np.log2( - backend.calculate_norm_density_matrix(new_state @ new_target, order=1) + if state_flag and target_flag: + backend.assert_allclose( + relative_renyi_entropy(state, target, alpha, base, backend), 0.0, atol=1e-5 ) - - log = -2 * log / np.log2(base) - else: - if len(state.shape) == 1: - state = np.outer(state, np.conj(state)) + if target_flag and alpha > 1: + with pytest.raises(NotImplementedError): + relative_renyi_entropy(state, target, alpha, base, backend) + else: + if alpha == 1.0: + log = relative_entropy(state, target, base, backend=backend) + elif alpha == np.inf: + new_state = _matrix_power(state, 0.5, backend) + new_target = _matrix_power(target, 0.5, backend) + + log = np.log2( + backend.calculate_norm_density_matrix( + new_state @ new_target, order=1 + ) + ) - if len(target.shape) == 1: - target = np.outer(target, np.conj(target)) + log = -2 * log / np.log2(base) + else: + if len(state.shape) == 1: + state = np.outer(state, np.conj(state)) - log = np.linalg.matrix_power(state, alpha) - log = log @ np.linalg.matrix_power(target, 1 - alpha) - log = np.log2(np.trace(log)) + if len(target.shape) == 1: + target = np.outer(target, np.conj(target)) - log = (1 / (alpha - 1)) * log / np.log2(base) + log = _matrix_power(state, alpha, backend) + log = log @ _matrix_power(target, 1 - alpha, backend) + log = np.log2(np.trace(log)) - backend.assert_allclose( - relative_renyi_entropy(state, target, alpha=alpha, base=base, backend=backend), - log, - atol=1e-5, - ) + log = (1 / (alpha - 1)) * log / np.log2(base) + + backend.assert_allclose( + relative_renyi_entropy( + state, target, alpha=alpha, base=base, backend=backend + ), + log, + atol=1e-5, + ) # test pure states state = random_density_matrix(4, pure=True, backend=backend) @@ -626,7 +609,7 @@ def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -@pytest.mark.parametrize("alpha", [0, 1, 2, 3, np.inf]) +@pytest.mark.parametrize("alpha", [0, 1, 2, 3, 5.4]) def test_tsallis_entropy(backend, alpha, base): with pytest.raises(TypeError): state = np.random.rand(2, 3) @@ -648,7 +631,7 @@ def test_tsallis_entropy(backend, alpha, base): target = entropy(state, base=base, backend=backend) else: target = (1 / (1 - alpha)) * ( - np.trace(np.linalg.matrix_power(state, alpha)) - 1 + np.trace(_matrix_power(state, alpha, backend)) - 1 ) backend.assert_allclose( From d50888dd14f93ea0e05b3e53eba8ba8e91360975 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Thu, 1 Feb 2024 08:46:45 +0400 Subject: [PATCH 095/200] fix coverage --- tests/test_quantum_info_entropies.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index d709f76056..bb091196fb 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -614,16 +614,16 @@ def test_tsallis_entropy(backend, alpha, base): with pytest.raises(TypeError): state = np.random.rand(2, 3) state = backend.cast(state, dtype=state.dtype) - test = renyi_entropy(state, alpha=alpha, base=base, backend=backend) + test = tsallis_entropy(state, alpha=alpha, base=base, backend=backend) with pytest.raises(TypeError): state = random_statevector(4, backend=backend) - test = renyi_entropy(state, alpha="2", base=base, backend=backend) + test = tsallis_entropy(state, alpha="2", base=base, backend=backend) with pytest.raises(ValueError): state = random_statevector(4, backend=backend) - test = renyi_entropy(state, alpha=-1, base=base, backend=backend) + test = tsallis_entropy(state, alpha=-1, base=base, backend=backend) with pytest.raises(ValueError): state = random_statevector(4, backend=backend) - test = renyi_entropy(state, alpha=alpha, base=0, backend=backend) + test = tsallis_entropy(state, alpha=alpha, base=0, backend=backend) state = random_density_matrix(4, backend=backend) @@ -640,6 +640,12 @@ def test_tsallis_entropy(backend, alpha, base): atol=1e-5, ) + # test pure state + state = random_density_matrix(4, pure=True, backend=backend) + backend.assert_allclose( + tsallis_entropy(state, alpha=alpha, base=base, backend=backend), 0.0, atol=1e-5 + ) + @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) From bd8f5215b1444224ebd97aedebd06b4b284a0910 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Thu, 1 Feb 2024 09:25:21 +0400 Subject: [PATCH 096/200] fix coverage --- src/qibo/quantum_info/entropies.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index f1b3e08a68..0174df02b1 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -400,9 +400,6 @@ def classical_tsallis_entropy(prob_dist, alpha: float, base: float = 2, backend= if alpha == 1.0: return shannon_entropy(prob_dist, base=base, backend=backend) - if isinstance(prob_dist, list): - prob_dist = backend.cast(prob_dist, dtype=np.float64) - return (1 / (1 - alpha)) * (np.sum(prob_dist**alpha) - 1) @@ -911,7 +908,10 @@ def entanglement_entropy( def _matrix_power(matrix, alpha, backend): """Calculates ``matrix ** alpha`` according to backend.""" - if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: + if backend.__class__.__name__ in [ + "CupyBackend", + "CuQuantumBackend", + ]: # pragma: no cover new_matrix = backend.to_numpy(matrix) else: new_matrix = np.copy(matrix) From 6decd8cef13786ac2c853351463214849a52c122 Mon Sep 17 00:00:00 2001 From: Alejandro Sopena Date: Fri, 2 Feb 2024 21:57:33 +0100 Subject: [PATCH 097/200] fix backend --- src/qibo/models/error_mitigation.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/src/qibo/models/error_mitigation.py b/src/qibo/models/error_mitigation.py index 2e2d577d2e..1f69c07a10 100644 --- a/src/qibo/models/error_mitigation.py +++ b/src/qibo/models/error_mitigation.py @@ -314,7 +314,8 @@ def CDR( train_val = {"noise-free": [], "noisy": []} for circ in training_circuits: - val = circ(nshots=nshots).expectation_from_samples(observable) + result = backend.execute_circuit(circ, nshots=nshots) + val = result.expectation_from_samples(observable) train_val["noise-free"].append(val) val = get_expectation_val_with_readout_mitigation( circ, observable, noise_model, nshots, readout, qubit_map, backend=backend @@ -400,7 +401,8 @@ def vnCDR( train_val = {"noise-free": [], "noisy": []} for circ in training_circuits: - val = circ(nshots=nshots).expectation_from_samples(observable) + result = backend.execute_circuit(circ, nshots=nshots) + val = result.expectation_from_samples(observable) train_val["noise-free"].append(val) for level in noise_levels: noisy_c = get_noisy_circuit(circ, level, insertion_gate=insertion_gate) @@ -897,7 +899,7 @@ def ICS( lambda_list = [] for training_circuit in training_circuits: - circuit_result = training_circuit(nshots=nshots) + circuit_result = backend.execute_circuit(training_circuit, nshots=nshots) expectation = observable.expectation_from_samples(circuit_result.frequencies()) noisy_expectation = get_expectation_val_with_readout_mitigation( From 9168a8784e5df469d2acce30a32fbbd4a9e8e563 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 04:17:21 +0000 Subject: [PATCH 098/200] Update src/qibo/quantum_info/entropies.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/entropies.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 0174df02b1..30d2e746c7 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -610,7 +610,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None Another special case is the limit :math:`\\alpha \\to 0`, where the function is reduced to :math:`\\log\\left(d\\right)`, with :math:`d = 2^{n}` being the dimension of the Hilbert space in which ``state`` :math:`\\rho` lives in. - This is knows as the `Hartley entropy _` + This is knows as the `Hartley entropy `_ (also known as *Hartley function* or *max-entropy*). In the limit :math:`\\alpha \\to \\infty`, the function reduces to From ce78900e5c68900de952e70577b9a6a0ac24863f Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 12:21:05 +0400 Subject: [PATCH 099/200] Alejandro suggestion --- doc/source/api-reference/qibo.rst | 14 +++---- src/qibo/quantum_info/entropies.py | 12 +++--- tests/test_quantum_info_entropies.py | 61 +++++++++++++++++----------- 3 files changed, 51 insertions(+), 36 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index e4f691487d..a91e1a9ee8 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1587,10 +1587,10 @@ Classical Tsallis entropy .. autofunction:: qibo.quantum_info.classical_tsallis_entropy -Entropy -""""""" +von Neumann entropy +""""""""""""""""""" -.. autofunction:: qibo.quantum_info.entropy +.. autofunction:: qibo.quantum_info.von_neumann_entropy .. note:: ``validate`` flag allows the user to choose if the function will check if input @@ -1600,10 +1600,10 @@ Entropy and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. -Relative entropy -"""""""""""""""" +Relative von Neumann entropy +"""""""""""""""""""""""""""" -.. autofunction:: qibo.quantum_info.relative_entropy +.. autofunction:: qibo.quantum_info.relative_von_neumann_entropy .. note:: ``validate`` flag allows the user to choose if the function will check if input @@ -1620,7 +1620,7 @@ Rényi entropy .. autofunction:: qibo.quantum_info.renyi_entropy -Rényi relative entropy +Relative Rényi entropy """""""""""""""""""""" .. autofunction:: qibo.quantum_info.renyi_relative_entropy diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 30d2e746c7..a577263039 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -403,7 +403,7 @@ def classical_tsallis_entropy(prob_dist, alpha: float, base: float = 2, backend= return (1 / (1 - alpha)) * (np.sum(prob_dist**alpha) - 1) -def entropy( +def von_neumann_entropy( state, base: float = 2, check_hermitian: bool = False, @@ -488,7 +488,7 @@ def entropy( return ent -def relative_entropy( +def relative_von_neumann_entropy( state, target, base: float = 2, check_hermitian: bool = False, backend=None ): """Calculates the relative entropy :math:`S(\\rho \\, \\| \\, \\sigma)` between ``state`` :math:`\\rho` and ``target`` :math:`\\sigma`. @@ -660,7 +660,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None return np.log2(len(state)) / np.log2(base) if alpha == 1.0: - return entropy(state, base=base, backend=backend) + return von_neumann_entropy(state, base=base, backend=backend) if alpha == np.inf: return ( @@ -765,7 +765,7 @@ def relative_renyi_entropy( state = np.outer(state, np.conj(state)) if alpha == 1.0: - return relative_entropy(state, target, base, backend=backend) + return relative_von_neumann_entropy(state, target, base, backend=backend) if alpha == np.inf: new_state = _matrix_power(state, 0.5, backend) @@ -834,7 +834,7 @@ def tsallis_entropy(state, alpha: float, base: float = 2, backend=None): return 0.0 if alpha == 1.0: - return entropy(state, base=base, backend=backend) + return von_neumann_entropy(state, base=base, backend=backend) return (1 / (1 - alpha)) * (np.trace(_matrix_power(state, alpha, backend)) - 1) @@ -895,7 +895,7 @@ def entanglement_entropy( else backend.partial_trace_density_matrix(state, bipartition, nqubits) ) - entropy_entanglement = entropy( + entropy_entanglement = von_neumann_entropy( reduced_density_matrix, base=base, check_hermitian=check_hermitian, diff --git a/tests/test_quantum_info_entropies.py b/tests/test_quantum_info_entropies.py index bb091196fb..3cf8b2d721 100644 --- a/tests/test_quantum_info_entropies.py +++ b/tests/test_quantum_info_entropies.py @@ -10,12 +10,12 @@ classical_renyi_entropy, classical_tsallis_entropy, entanglement_entropy, - entropy, - relative_entropy, relative_renyi_entropy, + relative_von_neumann_entropy, renyi_entropy, shannon_entropy, tsallis_entropy, + von_neumann_entropy, ) from qibo.quantum_info.random_ensembles import ( random_density_matrix, @@ -342,33 +342,43 @@ def test_classical_tsallis_entropy(backend, alpha, base, kind): @pytest.mark.parametrize("check_hermitian", [False, True]) @pytest.mark.parametrize("base", [2, 10, np.e, 5]) -def test_entropy(backend, base, check_hermitian): +def test_von_neumann_entropy(backend, base, check_hermitian): with pytest.raises(TypeError): state = np.random.rand(2, 3) state = backend.cast(state, dtype=state.dtype) - test = entropy( + test = von_neumann_entropy( state, base=base, check_hermitian=check_hermitian, backend=backend ) with pytest.raises(ValueError): state = np.array([1.0, 0.0]) state = backend.cast(state, dtype=state.dtype) - test = entropy(state, base=0, check_hermitian=check_hermitian, backend=backend) + test = von_neumann_entropy( + state, base=0, check_hermitian=check_hermitian, backend=backend + ) with pytest.raises(TypeError): state = np.array([1.0, 0.0]) state = backend.cast(state, dtype=state.dtype) - test = entropy(state, base=base, check_hermitian="False", backend=backend) + test = von_neumann_entropy( + state, base=base, check_hermitian="False", backend=backend + ) if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: with pytest.raises(NotImplementedError): state = random_unitary(4, backend=backend) - test = entropy(state, base=base, check_hermitian=True, backend=backend) + test = von_neumann_entropy( + state, base=base, check_hermitian=True, backend=backend + ) else: state = random_unitary(4, backend=backend) - test = entropy(state, base=base, check_hermitian=True, backend=backend) + test = von_neumann_entropy( + state, base=base, check_hermitian=True, backend=backend + ) state = np.array([1.0, 0.0]) state = backend.cast(state, dtype=state.dtype) - backend.assert_allclose(entropy(state, backend=backend), 0.0, atol=PRECISION_TOL) + backend.assert_allclose( + von_neumann_entropy(state, backend=backend), 0.0, atol=PRECISION_TOL + ) state = np.array([1.0, 0.0, 0.0, 0.0]) state = np.outer(state, state) @@ -386,7 +396,10 @@ def test_entropy(backend, base, check_hermitian): test = 0.8613531161467861 backend.assert_allclose( - entropy(state, base, check_hermitian=check_hermitian, backend=backend), test + von_neumann_entropy( + state, base, check_hermitian=check_hermitian, backend=backend + ), + test, ) @@ -397,14 +410,14 @@ def test_relative_entropy(backend, base, check_hermitian): state = np.random.rand(2, 3) state = backend.cast(state, dtype=state.dtype) target = random_density_matrix(2, pure=True, backend=backend) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian=check_hermitian, backend=backend ) with pytest.raises(TypeError): target = np.random.rand(2, 3) target = backend.cast(target, dtype=target.dtype) state = random_density_matrix(2, pure=True, backend=backend) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian=check_hermitian, backend=backend ) with pytest.raises(ValueError): @@ -412,7 +425,7 @@ def test_relative_entropy(backend, base, check_hermitian): state = backend.cast(state, dtype=state.dtype) target = np.array([0.0, 1.0]) target = backend.cast(target, dtype=target.dtype) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=0, check_hermitian=check_hermitian, backend=backend ) with pytest.raises(TypeError): @@ -420,7 +433,7 @@ def test_relative_entropy(backend, base, check_hermitian): state = backend.cast(state, dtype=state.dtype) target = np.array([0.0, 1.0]) target = backend.cast(target, dtype=target.dtype) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian="False", backend=backend ) @@ -431,35 +444,37 @@ def test_relative_entropy(backend, base, check_hermitian): target = backend.identity_density_matrix(nqubits, normalize=True) backend.assert_allclose( - relative_entropy(state, target, base, check_hermitian, backend), + relative_von_neumann_entropy(state, target, base, check_hermitian, backend), np.log(dims) / np.log(base) - - entropy(state, base=base, check_hermitian=check_hermitian, backend=backend), + - von_neumann_entropy( + state, base=base, check_hermitian=check_hermitian, backend=backend + ), atol=1e-5, ) state = backend.cast([1.0, 0.0], dtype=np.float64) target = backend.cast([0.0, 1.0], dtype=np.float64) - assert relative_entropy(state, target, backend=backend) == 0.0 + assert relative_von_neumann_entropy(state, target, backend=backend) == 0.0 # for coverage when GPUs are present if backend.__class__.__name__ in ["CupyBackend", "CuQuantumBackend"]: with pytest.raises(NotImplementedError): state = random_unitary(4, backend=backend) target = random_density_matrix(4, backend=backend) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian=True, backend=backend ) with pytest.raises(NotImplementedError): target = random_unitary(4, backend=backend) state = random_density_matrix(4, backend=backend) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian=True, backend=backend ) else: state = random_unitary(4, backend=backend) target = random_unitary(4, backend=backend) - test = relative_entropy( + test = relative_von_neumann_entropy( state, target, base=base, check_hermitian=True, backend=backend ) @@ -486,7 +501,7 @@ def test_renyi_entropy(backend, alpha, base): if alpha == 0.0: target = np.log2(len(state)) / np.log2(base) elif alpha == 1.0: - target = entropy(state, base=base, backend=backend) + target = von_neumann_entropy(state, base=base, backend=backend) elif alpha == np.inf: target = backend.calculate_norm_density_matrix(state, order=2) target = -1 * np.log2(target) / np.log2(base) @@ -565,7 +580,7 @@ def test_relative_renyi_entropy(backend, alpha, base, state_flag, target_flag): relative_renyi_entropy(state, target, alpha, base, backend) else: if alpha == 1.0: - log = relative_entropy(state, target, base, backend=backend) + log = relative_von_neumann_entropy(state, target, base, backend=backend) elif alpha == np.inf: new_state = _matrix_power(state, 0.5, backend) new_target = _matrix_power(target, 0.5, backend) @@ -628,7 +643,7 @@ def test_tsallis_entropy(backend, alpha, base): state = random_density_matrix(4, backend=backend) if alpha == 1.0: - target = entropy(state, base=base, backend=backend) + target = von_neumann_entropy(state, base=base, backend=backend) else: target = (1 / (1 - alpha)) * ( np.trace(_matrix_power(state, alpha, backend)) - 1 From 8ac8c6ef67818686d658049d6df751b941583fde Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 12:25:26 +0400 Subject: [PATCH 100/200] Alejandro suggestion --- doc/source/api-reference/qibo.rst | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index a91e1a9ee8..4f1fea5f24 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1593,10 +1593,10 @@ von Neumann entropy .. autofunction:: qibo.quantum_info.von_neumann_entropy .. note:: - ``validate`` flag allows the user to choose if the function will check if input - ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + ``check_hermitian`` flag allows the user to choose if the function will check if input + ``state`` is Hermitian or not. Default option is ``check_hermitian=False``, i.e. the assumption of Hermiticity. This is faster and, more importantly, - this function are intended to be used on Hermitian inputs. When ``validate=True`` + this function are intended to be used on Hermitian inputs. When ``check_hermitian=True`` and ``state`` is non-Hermitian, an error will be raised when using `cupy` backend. @@ -1606,10 +1606,10 @@ Relative von Neumann entropy .. autofunction:: qibo.quantum_info.relative_von_neumann_entropy .. note:: - ``validate`` flag allows the user to choose if the function will check if input - ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + ``check_hermitian`` flag allows the user to choose if the function will check if input + ``state`` is Hermitian or not. Default option is ``check_hermitian=False``, i.e. the assumption of Hermiticity. This is faster and, more importantly, - this function are intended to be used on Hermitian inputs. When ``validate=True`` + this function are intended to be used on Hermitian inputs. When ``check_hermitian=True`` and either ``state`` or ``target`` is non-Hermitian, an error will be raised when using `cupy` backend. @@ -1638,11 +1638,11 @@ Entanglement entropy .. autofunction:: qibo.quantum_info.entanglement_entropy .. note:: - ``validate`` flag allows the user to choose if the function will check if + ``check_hermitian`` flag allows the user to choose if the function will check if the reduced density matrix resulting from tracing out ``bipartition`` from input - ``state`` is Hermitian or not. Default option is ``validate=False``, i.e. the + ``state`` is Hermitian or not. Default option is ``check_hermitian=False``, i.e. the assumption of Hermiticity. This is faster and, more importantly, - this function are intended to be used on Hermitian inputs. When ``validate=True`` + this function are intended to be used on Hermitian inputs. When ``check_hermitian=True`` and the reduced density matrix is non-Hermitian, an error will be raised when using `cupy` backend. @@ -1671,11 +1671,11 @@ Trace distance .. autofunction:: qibo.quantum_info.trace_distance .. note:: - ``validate`` flag allows the user to choose if the function will check if difference + ``check_hermitian`` flag allows the user to choose if the function will check if difference between inputs, ``state - target``, is Hermitian or not. Default option is - ``validate=False``, i.e. the assumption of Hermiticity, because it is faster and, + ``check_hermitian=False``, i.e. the assumption of Hermiticity, because it is faster and, more importantly, the functions are intended to be used on Hermitian inputs. - When ``validate=True`` and ``state - target`` is non-Hermitian, an error will be + When ``check_hermitian=True`` and ``state - target`` is non-Hermitian, an error will be raised when using `cupy` backend. From dd6e31ac4011bb39030b5dc440cfbbb1a3c71d16 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 13:10:18 +0400 Subject: [PATCH 101/200] initial commit --- src/qibo/transpiler/decompositions.py | 50 ++++++++++++++++++--------- 1 file changed, 34 insertions(+), 16 deletions(-) diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index cb106d423b..cbefc02dc9 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -116,7 +116,7 @@ def _u3_to_gpi2(t, p, l): # Decompose single qubit gates using U3 u3_dec = GateDecompositions() -u3_dec.add(gates.H, [gates.U3(0, 7 * np.pi / 2, np.pi, 0)]) +u3_dec.add(gates.H, [gates.U3(0, -np.pi / 2, np.pi, 0)]) u3_dec.add(gates.X, [gates.U3(0, np.pi, 0, np.pi)]) u3_dec.add(gates.Y, [gates.U3(0, np.pi, 0, 0)]) u3_dec.add(gates.Z, [gates.Z(0)]) @@ -159,28 +159,28 @@ def _u3_to_gpi2(t, p, l): gates.CNOT, [ gates.U3(0, 3 * np.pi / 2, np.pi, 0), - gates.U3(1, np.pi / 2, -np.pi, -np.pi), + gates.U3(1, np.pi / 2, np.pi, np.pi), gates.iSWAP(0, 1), gates.U3(0, np.pi, 0, np.pi), - gates.U3(1, np.pi / 2, -np.pi, -np.pi), + gates.U3(1, np.pi / 2, np.pi, np.pi), gates.iSWAP(0, 1), - gates.U3(0, np.pi / 2, np.pi / 2, -np.pi), - gates.U3(1, np.pi / 2, -np.pi, -np.pi / 2), + gates.U3(0, np.pi / 2, np.pi / 2, np.pi), + gates.U3(1, np.pi / 2, np.pi, -np.pi / 2), ], ) iswap_dec.add( gates.CZ, [ - gates.U3(0, 7 * np.pi / 2, np.pi, 0), - gates.U3(1, 7 * np.pi / 2, np.pi, 0), - gates.U3(1, np.pi / 2, -np.pi, -np.pi), + gates.U3(0, -np.pi / 2, np.pi, 0), + gates.U3(1, -np.pi / 2, np.pi, 0), + gates.U3(1, np.pi / 2, np.pi, np.pi), gates.iSWAP(0, 1), gates.U3(0, np.pi, 0, np.pi), - gates.U3(1, np.pi / 2, -np.pi, -np.pi), + gates.U3(1, np.pi / 2, np.pi, np.pi), gates.iSWAP(0, 1), - gates.U3(0, np.pi / 2, np.pi / 2, -np.pi), - gates.U3(1, np.pi / 2, -np.pi, -np.pi / 2), - gates.U3(1, 7 * np.pi / 2, np.pi, 0), + gates.U3(0, np.pi / 2, np.pi / 2, np.pi), + gates.U3(1, np.pi / 2, np.pi, -np.pi / 2), + gates.U3(1, -np.pi / 2, np.pi, 0), ], ) iswap_dec.add( @@ -304,14 +304,14 @@ def _u3_to_gpi2(t, p, l): cz_dec.add( gates.FSWAP, [ - gates.U3(0, np.pi / 2, -np.pi / 2, -np.pi), + gates.U3(0, np.pi / 2, -np.pi / 2, np.pi), gates.U3(1, np.pi / 2, np.pi / 2, np.pi / 2), gates.CZ(0, 1), gates.U3(0, np.pi / 2, 0, -np.pi / 2), gates.U3(1, np.pi / 2, 0, np.pi / 2), gates.CZ(0, 1), - gates.U3(0, np.pi / 2, np.pi / 2, -np.pi), - gates.U3(1, np.pi / 2, 0, -np.pi), + gates.U3(0, np.pi / 2, np.pi / 2, np.pi), + gates.U3(1, np.pi / 2, 0, np.pi), ], ) cz_dec.add( @@ -328,7 +328,7 @@ def _u3_to_gpi2(t, p, l): gates.RYY, lambda gate: [ gates.RX(0, np.pi / 2), - gates.U3(1, np.pi / 2, np.pi / 2, -np.pi), + gates.U3(1, np.pi / 2, np.pi / 2, np.pi), gates.CZ(0, 1), gates.RX(1, gate.parameters[0]), gates.CZ(0, 1), @@ -392,3 +392,21 @@ def _u3_to_gpi2(t, p, l): gates.H(1), ], ) + + +# standard gate decompositions used by :meth:`qibo.gates.gates.Gate.decompose` +standard = GateDecompositions() +standard.add(gates.SX, [gates.RX(0, np.pi / 2, trainable=False)]) +standard.add(gates.SXDG, [gates.RX(0, -np.pi / 2, trainable=False)]) +standard.add(gates.U3, [gates.RZ, gates.SX, gates.RZ, gates.SX, gates.RZ]) +standard.add(gates.CY, [gates.SDG, gates.CNOT, gates.S]) +standard.add(gates.CZ, [gates.H, gates.CNOT, gates.H]) +standard.add(gates.CSX, []) +standard.add(gates.CSXDG, []) +standard.add(gates.FSWAP, []) +standard.add(gates.RZX, []) +standard.add(gates.RXXYY, []) +standard.add(gates.GIVENS, []) +standard.add(gates.RBS, []) +standard.add(gates.ECR, []) +standard.add(gates.TOFFOLI, []) From b8b95813a31e575dd1ae2e73938ffbaf8c68ea41 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 14:13:04 +0000 Subject: [PATCH 102/200] Update doc/source/api-reference/qibo.rst Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- doc/source/api-reference/qibo.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 4f1fea5f24..b2405a01c0 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1623,7 +1623,7 @@ Rényi entropy Relative Rényi entropy """""""""""""""""""""" -.. autofunction:: qibo.quantum_info.renyi_relative_entropy +.. autofunction:: qibo.quantum_info.relative_renyi_entropy Tsallis entropy From ba3de9c3173018d21791bb86afc11b45cb501e3a Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 18:40:02 +0400 Subject: [PATCH 103/200] fix local state and backend --- src/qibo/quantum_info/random_ensembles.py | 14 +------------- 1 file changed, 1 insertion(+), 13 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index ddccc3b6f0..8c61aa38b7 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -419,19 +419,7 @@ def random_statevector(dims: int, seed=None, backend=None): TypeError, "seed must be either type int or numpy.random.Generator." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() - - if seed is None or isinstance(seed, int): - if backend.__class__.__name__ in [ - "CupyBackend", - "CuQuantumBackend", - ]: # pragma: no cover - local_state = backend.np.random.default_rng(seed) - else: - local_state = np.random.default_rng(seed) - else: - local_state = seed + backend, local_state = _set_backend_and_local_state(seed, backend) state = local_state.standard_normal(dims).astype(complex) state += 1.0j * local_state.standard_normal(dims) From 230f5853a34e0eea122c0bac4fe8ea6166029cf0 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 15:01:58 +0000 Subject: [PATCH 104/200] Update src/qibo/quantum_info/entropies.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/entropies.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index a577263039..c303c37f0a 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -172,7 +172,7 @@ def classical_renyi_entropy( Another special case is the limit :math:`\\alpha \\to 0`, where the function is reduced to :math:`\\log\\left(|\\mathbf{p}|\\right)`, with :math:`|\\mathbf{p}|` being the support of :math:`\\mathbf{p}`. - This is knows as the `Hartley entropy `_ + This is known as the `Hartley entropy `_ (also known as *Hartley function* or *max-entropy*). In the limit :math:`\\alpha \\to \\infty`, the function reduces to From 9e761fb9617fe18c471436391246b6521c35c369 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 3 Feb 2024 15:02:06 +0000 Subject: [PATCH 105/200] Update src/qibo/quantum_info/entropies.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/entropies.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index c303c37f0a..0108bcddbc 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -610,7 +610,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None Another special case is the limit :math:`\\alpha \\to 0`, where the function is reduced to :math:`\\log\\left(d\\right)`, with :math:`d = 2^{n}` being the dimension of the Hilbert space in which ``state`` :math:`\\rho` lives in. - This is knows as the `Hartley entropy `_ + This is known as the `Hartley entropy `_ (also known as *Hartley function* or *max-entropy*). In the limit :math:`\\alpha \\to \\infty`, the function reduces to From 287528256b3cdbb15489a63e1873e1fe6a0050d6 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 04:08:28 +0000 Subject: [PATCH 106/200] Update src/qibo/quantum_info/random_ensembles.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/random_ensembles.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 8c61aa38b7..dd66a7e0a6 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -424,6 +424,7 @@ def random_statevector(dims: int, seed=None, backend=None): state = local_state.standard_normal(dims).astype(complex) state += 1.0j * local_state.standard_normal(dims) state /= np.linalg.norm(state) + state = backend.cast(state, dtype=state.dtype) return backend.cast(state, dtype=state.dtype) From 5192b14599a79b95ec684ab9f0296ea863dd2f82 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 04:08:34 +0000 Subject: [PATCH 107/200] Update src/qibo/quantum_info/random_ensembles.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/random_ensembles.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index dd66a7e0a6..3d11c0d1ce 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -426,7 +426,7 @@ def random_statevector(dims: int, seed=None, backend=None): state /= np.linalg.norm(state) state = backend.cast(state, dtype=state.dtype) - return backend.cast(state, dtype=state.dtype) + return state def random_density_matrix( From 2bfd6ecbad2b348a7f4b47bbb033e25160aea742 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sun, 4 Feb 2024 04:08:54 +0000 Subject: [PATCH 108/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/quantum_info/random_ensembles.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 3d11c0d1ce..18e2eedaa1 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -424,7 +424,7 @@ def random_statevector(dims: int, seed=None, backend=None): state = local_state.standard_normal(dims).astype(complex) state += 1.0j * local_state.standard_normal(dims) state /= np.linalg.norm(state) - state = backend.cast(state, dtype=state.dtype) + state = backend.cast(state, dtype=state.dtype) return state From 645e6f1eec20cc8f5c59db6d7a1309334019dc6b Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 08:36:46 +0400 Subject: [PATCH 109/200] testing function --- src/qibo/transpiler/decompositions.py | 34 +++++++++++++++------------ 1 file changed, 19 insertions(+), 15 deletions(-) diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index cbefc02dc9..56901c8920 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -1,3 +1,4 @@ +#%% import numpy as np from qibo import gates @@ -395,18 +396,21 @@ def _u3_to_gpi2(t, p, l): # standard gate decompositions used by :meth:`qibo.gates.gates.Gate.decompose` -standard = GateDecompositions() -standard.add(gates.SX, [gates.RX(0, np.pi / 2, trainable=False)]) -standard.add(gates.SXDG, [gates.RX(0, -np.pi / 2, trainable=False)]) -standard.add(gates.U3, [gates.RZ, gates.SX, gates.RZ, gates.SX, gates.RZ]) -standard.add(gates.CY, [gates.SDG, gates.CNOT, gates.S]) -standard.add(gates.CZ, [gates.H, gates.CNOT, gates.H]) -standard.add(gates.CSX, []) -standard.add(gates.CSXDG, []) -standard.add(gates.FSWAP, []) -standard.add(gates.RZX, []) -standard.add(gates.RXXYY, []) -standard.add(gates.GIVENS, []) -standard.add(gates.RBS, []) -standard.add(gates.ECR, []) -standard.add(gates.TOFFOLI, []) +standard_decompositions = GateDecompositions() +standard_decompositions.add(gates.SX, [gates.RX(0, np.pi / 2, trainable=False)]) +standard_decompositions.add(gates.SXDG, [gates.RX(0, -np.pi / 2, trainable=False)]) +standard_decompositions.add( + gates.U3, + lambda gate: [gates.RZ(0, gate.parameters[2]), gates.SX(0), gates.RZ(0, gate.parameters[0] + np.pi), gates.SX(0), gates.RZ(0, gate.parameters[1] + np.pi)], +) +standard_decompositions.add(gates.CY, [gates.SDG, gates.CNOT, gates.S]) +standard_decompositions.add(gates.CZ, [gates.H, gates.CNOT, gates.H]) +standard_decompositions.add(gates.CSX, []) +standard_decompositions.add(gates.CSXDG, []) +standard_decompositions.add(gates.FSWAP, []) +standard_decompositions.add(gates.RZX, []) +standard_decompositions.add(gates.RXXYY, []) +standard_decompositions.add(gates.GIVENS, []) +standard_decompositions.add(gates.RBS, []) +standard_decompositions.add(gates.ECR, []) +standard_decompositions.add(gates.TOFFOLI, []) From 62971ea411e7f29cbcc3a79a2b03d7b4899d5554 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sun, 4 Feb 2024 04:37:13 +0000 Subject: [PATCH 110/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/transpiler/decompositions.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index 56901c8920..72e49154fd 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -1,4 +1,4 @@ -#%% +# %% import numpy as np from qibo import gates @@ -400,8 +400,14 @@ def _u3_to_gpi2(t, p, l): standard_decompositions.add(gates.SX, [gates.RX(0, np.pi / 2, trainable=False)]) standard_decompositions.add(gates.SXDG, [gates.RX(0, -np.pi / 2, trainable=False)]) standard_decompositions.add( - gates.U3, - lambda gate: [gates.RZ(0, gate.parameters[2]), gates.SX(0), gates.RZ(0, gate.parameters[0] + np.pi), gates.SX(0), gates.RZ(0, gate.parameters[1] + np.pi)], + gates.U3, + lambda gate: [ + gates.RZ(0, gate.parameters[2]), + gates.SX(0), + gates.RZ(0, gate.parameters[0] + np.pi), + gates.SX(0), + gates.RZ(0, gate.parameters[1] + np.pi), + ], ) standard_decompositions.add(gates.CY, [gates.SDG, gates.CNOT, gates.S]) standard_decompositions.add(gates.CZ, [gates.H, gates.CNOT, gates.H]) From a7ac562498f5678679659944dc18303ae46066d2 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 09:43:36 +0400 Subject: [PATCH 111/200] implement refactoring --- src/qibo/gates/gates.py | 124 +++++++++++++------------- src/qibo/transpiler/decompositions.py | 69 +++++++++++--- 2 files changed, 118 insertions(+), 75 deletions(-) diff --git a/src/qibo/gates/gates.py b/src/qibo/gates/gates.py index aa0e0d5ede..588145a5dc 100644 --- a/src/qibo/gates/gates.py +++ b/src/qibo/gates/gates.py @@ -271,7 +271,11 @@ def decompose(self): being the :class:`qibo.gates.RX` gate. More precisely, :math:`\\sqrt{X} = e^{i \\pi / 4} \\, \\text{RX}(\\pi / 2)`. """ - return [RX(self.init_args[0], np.pi / 2, trainable=False)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) def _dagger(self): """""" @@ -314,7 +318,11 @@ def decompose(self): being the :class:`qibo.gates.RX` gate. More precisely, :math:`(\\sqrt{X})^{\\dagger} = e^{-i \\pi / 4} \\, \\text{RX}(-\\pi / 2)`. """ - return [RX(self.init_args[0], -np.pi / 2, trainable=False)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) def _dagger(self): """""" @@ -892,14 +900,11 @@ def decompose(self) -> List[Gate]: where :math:`\\text{RZ}` and :math:`\\sqrt{X}` are, respectively, :class:`qibo.gates.RZ` and :class`qibo.gates.SX`. """ - q = self.init_args[0] - return [ - RZ(q, self.init_kwargs["lam"]), - SX(q), - RZ(q, self.init_kwargs["theta"] + math.pi), - SX(q), - RZ(q, self.init_kwargs["phi"] + math.pi), - ] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class U1q(_Un_): @@ -1020,8 +1025,11 @@ def decompose(self) -> List[Gate]: the target qubit, followed by :class:`qibo.gates.CNOT`, followed by a :class:`qibo.gates.S` in the target qubit. """ - q0, q1 = self.init_args - return [SDG(q1), CNOT(q0, q1), S(q1)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class CZ(Gate): @@ -1063,8 +1071,11 @@ def decompose(self) -> List[Gate]: the target qubit, followed by :class:`qibo.gates.CNOT`, followed by another :class:`qibo.gates.H` in the target qubit """ - q0, q1 = self.init_args - return [H(q1), CNOT(q0, q1), H(q1)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class CSX(Gate): @@ -1100,8 +1111,11 @@ def qasm_label(self): def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: """""" - q0, q1 = self.init_args - return [H(q1), CU1(q0, q1, np.pi / 2), H(q1)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) def _dagger(self): """""" @@ -1141,8 +1155,11 @@ def qasm_label(self): def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: """""" - q0, q1 = self.init_args - return [H(q1), CU1(q0, q1, -np.pi / 2), H(q1)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) def _dagger(self): """""" @@ -1868,9 +1885,11 @@ def __init__(self, q0, q1, theta, trainable=True): def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: """""" - q0, q1 = self.target_qubits - theta = self.init_kwargs["theta"] - return [H(q1), CNOT(q0, q1), RZ(q1, theta), CNOT(q0, q1), H(q1)] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class RXXYY(_Rnn_): @@ -1909,22 +1928,11 @@ def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: the original gate due to a phase difference in :math:`\\left(\\sqrt{X}\\right)^{\\dagger}`. """ - q0, q1 = self.target_qubits - theta = self.init_kwargs["theta"] - return [ - RZ(q1, -np.pi / 2), - S(q0), - SX(q1), - RZ(q1, np.pi / 2), - CNOT(q1, q0), - RY(q0, -theta / 2), - RY(q1, -theta / 2), - CNOT(q1, q0), - SDG(q0), - RZ(q1, -np.pi / 2), - SX(q1).dagger(), - RZ(q1, np.pi / 2), - ] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class MS(ParametrizedGate): @@ -2029,18 +2037,13 @@ def _dagger(self) -> "Gate": return self.__class__(*self.target_qubits, -self.parameters[0]) def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: - """Decomposition of Givens gate according to `ArXiv:2106.13839 - `_.""" - q0, q1 = self.target_qubits - theta = self.init_kwargs["theta"] - return [ - CNOT(q0, q1), - RY(q0, theta), - CNOT(q1, q0), - RY(q0, -theta), - CNOT(q1, q0), - CNOT(q0, q1), - ] + """Decomposition of RBS gate according to `ArXiv:2109.09685 + `_.""" + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class RBS(ParametrizedGate): @@ -2090,18 +2093,11 @@ def _dagger(self) -> "Gate": def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: """Decomposition of RBS gate according to `ArXiv:2109.09685 `_.""" - q0, q1 = self.target_qubits - theta = self.init_kwargs["theta"] - return [ - H(q0), - CNOT(q0, q1), - H(q1), - RY(q0, theta), - RY(q1, -theta), - H(q1), - CNOT(q0, q1), - H(q0), - ] + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) + + return standard_decompositions(self) class ECR(Gate): @@ -2142,9 +2138,11 @@ def decompose(self, *free, use_toffolis: bool = True) -> List[Gate]: \\textup{ECR} = e^{i 7 \\pi / 4} \\, S(q_{0}) \\, \\sqrt{X}(q_{1}) \\, \\textup{CNOT}(q_{0}, q_{1}) \\, X(q_{0}) """ + from qibo.transpiler.decompositions import ( # pylint: disable=C0415 + standard_decompositions, + ) - q0, q1 = self.target_qubits - return [S(q0), SX(q1), CNOT(q0, q1), X(q0)] + return standard_decompositions(self) class TOFFOLI(Gate): diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index 72e49154fd..813549e046 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -1,4 +1,3 @@ -# %% import numpy as np from qibo import gates @@ -409,14 +408,60 @@ def _u3_to_gpi2(t, p, l): gates.RZ(0, gate.parameters[1] + np.pi), ], ) -standard_decompositions.add(gates.CY, [gates.SDG, gates.CNOT, gates.S]) -standard_decompositions.add(gates.CZ, [gates.H, gates.CNOT, gates.H]) -standard_decompositions.add(gates.CSX, []) -standard_decompositions.add(gates.CSXDG, []) -standard_decompositions.add(gates.FSWAP, []) -standard_decompositions.add(gates.RZX, []) -standard_decompositions.add(gates.RXXYY, []) -standard_decompositions.add(gates.GIVENS, []) -standard_decompositions.add(gates.RBS, []) -standard_decompositions.add(gates.ECR, []) -standard_decompositions.add(gates.TOFFOLI, []) +standard_decompositions.add(gates.CY, [gates.SDG(1), gates.CNOT(0, 1), gates.S(1)]) +standard_decompositions.add(gates.CZ, [gates.H(1), gates.CNOT(0, 1), gates.H(1)]) +standard_decompositions.add( + gates.CSX, [gates.H(1), gates.CU1(0, 1, np.pi / 2), gates.H(1)] +) +standard_decompositions.add( + gates.CSXDG, [gates.H(1), gates.CU1(0, 1, -np.pi / 2), gates.H(1)] +) +standard_decompositions.add( + gates.FSWAP, [gates.X(1)] + gates.GIVENS(0, 1, np.pi / 2).decompose() + [gates.X(0)] +) +standard_decompositions.add( + gates.RZX, + lambda gate: [ + gates.H(1), + gates.CNOT(0, 1), + gates.RZ(1, gate.parameters[0]), + gates.CNOT(0, 1), + gates.H(1), + ], +) +standard_decompositions.add( + gates.RXXYY, + lambda gate: [ + gates.RZ(1, -np.pi / 2), + gates.S(0), + gates.SX(1), + gates.RZ(1, np.pi / 2), + gates.CNOT(1, 0), + gates.RY(0, -gate.parameters[0] / 2), + gates.RY(1, -gate.parameters[0] / 2), + gates.CNOT(1, 0), + gates.SDG(0), + gates.RZ(1, -np.pi / 2), + gates.SX(1).dagger(), + gates.RZ(1, np.pi / 2), + ], +) +standard_decompositions.add( + gates.GIVENS, lambda gate: gates.RBS(0, 1, -gate.parameters[1]).decompose() +) +standard_decompositions.add( + gates.RBS, + lambda gate: [ + gates.H(0), + gates.CNOT(0, 1), + gates.H(1), + gates.RY(0, gate.parameters[0]), + gates.RY(1, -gate.parameters[0]), + gates.H(1), + gates.CNOT(0, 1), + gates.H(0), + ], +) +standard_decompositions.add( + gates.ECR, [gates.S(0), gates.SX(1), gates.CNOT(0, 1), gates.X(0)] +) From a86e2acab1488fcadd254a5ca059c8f481cfd71e Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 10:17:53 +0400 Subject: [PATCH 112/200] fix order --- src/qibo/transpiler/decompositions.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index 813549e046..b36ff1c139 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -416,9 +416,6 @@ def _u3_to_gpi2(t, p, l): standard_decompositions.add( gates.CSXDG, [gates.H(1), gates.CU1(0, 1, -np.pi / 2), gates.H(1)] ) -standard_decompositions.add( - gates.FSWAP, [gates.X(1)] + gates.GIVENS(0, 1, np.pi / 2).decompose() + [gates.X(0)] -) standard_decompositions.add( gates.RZX, lambda gate: [ @@ -446,9 +443,6 @@ def _u3_to_gpi2(t, p, l): gates.RZ(1, np.pi / 2), ], ) -standard_decompositions.add( - gates.GIVENS, lambda gate: gates.RBS(0, 1, -gate.parameters[1]).decompose() -) standard_decompositions.add( gates.RBS, lambda gate: [ @@ -462,6 +456,12 @@ def _u3_to_gpi2(t, p, l): gates.H(0), ], ) +standard_decompositions.add( + gates.GIVENS, lambda gate: gates.RBS(0, 1, -gate.parameters[1]).decompose() +) +standard_decompositions.add( + gates.FSWAP, [gates.X(1)] + gates.GIVENS(0, 1, np.pi / 2).decompose() + [gates.X(0)] +) standard_decompositions.add( gates.ECR, [gates.S(0), gates.SX(1), gates.CNOT(0, 1), gates.X(0)] ) From 2a7b55b479c6fb7a98fa9521017752424df04052 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 4 Feb 2024 10:31:46 +0400 Subject: [PATCH 113/200] fix bug --- src/qibo/transpiler/decompositions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/transpiler/decompositions.py b/src/qibo/transpiler/decompositions.py index b36ff1c139..f559f0088a 100644 --- a/src/qibo/transpiler/decompositions.py +++ b/src/qibo/transpiler/decompositions.py @@ -457,7 +457,7 @@ def _u3_to_gpi2(t, p, l): ], ) standard_decompositions.add( - gates.GIVENS, lambda gate: gates.RBS(0, 1, -gate.parameters[1]).decompose() + gates.GIVENS, lambda gate: gates.RBS(0, 1, -gate.parameters[0]).decompose() ) standard_decompositions.add( gates.FSWAP, [gates.X(1)] + gates.GIVENS(0, 1, np.pi / 2).decompose() + [gates.X(0)] From 330200828ac5dc3d41244e4fa0c698b2a94fceb9 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 10:29:08 +0400 Subject: [PATCH 114/200] functions --- src/qibo/models/encodings.py | 46 +++++++++++++++++++++++++++++++++++- 1 file changed, 45 insertions(+), 1 deletion(-) diff --git a/src/qibo/models/encodings.py b/src/qibo/models/encodings.py index a85024ad3c..ba0e5a4352 100644 --- a/src/qibo/models/encodings.py +++ b/src/qibo/models/encodings.py @@ -70,6 +70,47 @@ def comp_basis_encoder( return circuit +def phase_encoder(data, rotation: str = "RY"): + """Creates circuit that performs the phase encoding of ``data``. + + Args: + data (ndarray or list): :math:`1`-dimensional array of phases to be loaded. + rotation (str, optional): If ``"RX"``, uses :class:`qibo.gates.gates.RX` as rotation. + If ``"RY"``, uses :class:`qibo.gates.gates.RY` as rotation. + If ``"RZ"``, uses :class:`qibo.gates.gates.RZ` as rotation. + Defaults to ``"RY"``. + + Returns: + :class:`qibo.models.circuit.Circuit`: circuit that loads ``data`` in phase encoding. + """ + if isinstance(data, list): + data = np.array(data) + + if len(data.shape) != 1: + raise_error( + TypeError, + f"``data`` must be a 1-dimensional array, but it has dimensions {data.shape}.", + ) + + if not isinstance(rotation, str): + raise_error( + TypeError, + f"``rotation`` must be type str, but it is type {type(rotation)}.", + ) + + if rotation not in ["RX", "RY", "RZ"]: + raise_error(ValueError, f"``rotation`` {rotation} not found.") + + nqubits = len(data) + gate = getattr(gates, rotation.upper()) + + circuit = Circuit(nqubits) + circuit.add(gate(qubit, 0.0) for qubit in range(nqubits)) + circuit.set_parameters(data) + + return circuit + + def unary_encoder(data, architecture: str = "tree"): """Creates circuit that performs the unary encoding of ``data``. @@ -91,7 +132,7 @@ def unary_encoder(data, architecture: str = "tree"): :math:`d`. Args: - data (ndarray, optional): :math:`1`-dimensional array of data to be loaded. + data (ndarray): :math:`1`-dimensional array of data to be loaded. architecture(str, optional): circuit architecture used for the unary loader. If ``diagonal``, uses a ladder-like structure. If ``tree``, uses a binary-tree-based structure. @@ -104,6 +145,9 @@ def unary_encoder(data, architecture: str = "tree"): 1. S. Johri *et al.*, *Nearest Centroid Classification on a Trapped Ion Quantum Computer*. `arXiv:2012.04145v2 [quant-ph] `_. """ + if isinstance(data, list): + data = np.array(data) + if len(data.shape) != 1: raise_error( TypeError, From 743e3acc7c7844f81363903b0e694560b07e86e7 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 10:29:16 +0400 Subject: [PATCH 115/200] tests --- tests/test_models_encodings.py | 50 ++++++++++++++++++++++++++++++++++ 1 file changed, 50 insertions(+) diff --git a/tests/test_models_encodings.py b/tests/test_models_encodings.py index b71faa5c97..ac997460c2 100644 --- a/tests/test_models_encodings.py +++ b/tests/test_models_encodings.py @@ -1,6 +1,7 @@ """Tests for qibo.models.encodings""" import math +from itertools import product import numpy as np import pytest @@ -8,6 +9,7 @@ from qibo.models.encodings import ( comp_basis_encoder, + phase_encoder, unary_encoder, unary_encoder_random_gaussian, ) @@ -48,6 +50,54 @@ def test_comp_basis_encoder(backend, basis_element): backend.assert_allclose(state, target) +@pytest.mark.parametrize("kind", [None, list]) +@pytest.mark.parametrize("rotation", ["RX", "RY", "RZ"]) +def test_phase_encoder(backend, rotation, kind): + sampler = np.random.default_rng(1) + + nqubits = 3 + dims = 2**nqubits + + with pytest.raises(TypeError): + data = sampler.random((nqubits, nqubits)) + data = backend.cast(data, dtype=data.dtype) + phase_encoder(data, rotation=rotation) + with pytest.raises(TypeError): + data = sampler.random(nqubits) + data = backend.cast(data, dtype=data.dtype) + phase_encoder(data, rotation=True) + with pytest.raises(ValueError): + data = sampler.random(nqubits) + data = backend.cast(data, dtype=data.dtype) + phase_encoder(data, rotation="rzz") + + phases = np.random.rand(nqubits) + + if rotation in ["RX", "RY"]: + functions = list(product([np.cos, np.sin], repeat=nqubits)) + target = [] + for row in functions: + elem = 1.0 + for phase, func in zip(phases, row): + elem *= func(phase / 2) + if rotation == "RX" and func.__name__ == "sin": + elem *= -1.0j + target.append(elem) + else: + target = [np.exp(-0.5j * sum(phases))] + [0.0] * (dims - 1) + + target = np.array(target, dtype=complex) + target = backend.cast(target, dtype=target.dtype) + + if kind is not None: + phases = kind(phases) + + state = phase_encoder(phases, rotation=rotation) + state = backend.execute_circuit(state).state() + + backend.assert_allclose(state, target) + + @pytest.mark.parametrize("architecture", ["tree", "diagonal"]) @pytest.mark.parametrize("nqubits", [8]) def test_unary_encoder(backend, nqubits, architecture): From a8994b09f39ec4c51d98a4bce51baa0105060960 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 10:57:57 +0400 Subject: [PATCH 116/200] add image to doc --- doc/source/_static/phase_encoder.png | Bin 0 -> 199388 bytes doc/source/api-reference/qibo.rst | 36 +++++++++++++++++++++++++++ 2 files changed, 36 insertions(+) create mode 100644 doc/source/_static/phase_encoder.png diff --git a/doc/source/_static/phase_encoder.png b/doc/source/_static/phase_encoder.png new file 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!LPr1tSZ>L++57EKf?Zp`oBE^|J)zP`xdF)Um-DgP}~K|3H)#O!$S9i zRM(Vn`0l!=3)#=`!tLweqi7x(JzC5Q(~lqIu7g~Ees+ADOex@6%syqO$*0Bh;rUm~ zZ`*~1H*#;>cFj}mJH}(|&;-TcV$cM%KVW+Q8z)i%tjR=MON4n~un*1Fvi^C;aS2fGtNn;epw*m_a}Q zKIZ-xO5PQ3oUP2dSn=mIG)9)^ox{B&H%D1NpIH Date: Mon, 5 Feb 2024 11:07:44 +0400 Subject: [PATCH 117/200] iamge proportions --- doc/source/api-reference/qibo.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 688e94d73b..2058f41b26 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -300,8 +300,8 @@ For instance, the following two circuit generations are equivalent: .. image:: ../_static/phase_encoder.png - :width: 1164px - :height: 670px + :width: 2000px + :height: 2329px :scale: 30 % :align: center From b14b1cc594c5893cbbd74ab8feae263e0c966971 Mon Sep 17 00:00:00 2001 From: Canoming Date: Mon, 5 Feb 2024 16:06:39 +0800 Subject: [PATCH 118/200] minor fix: [@BrunoLiegiBastonLiegi](https://github.com/qiboteam/qibo/pull/1137#discussion_r1475722863) --- src/qibo/quantum_info/quantum_networks.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index af549a46fa..89c9a6a8e2 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -42,7 +42,7 @@ def __init__( self.partition = partition self.system_output = system_output self._pure = pure - self._backend = backend + self._backend = backend if backend is not None else GlobalBackend() self.dims = reduce(mul, self.partition) self._set_tensor_and_parameters() @@ -211,7 +211,7 @@ def causal( return float(norm) <= precision_tol def positive_semidefinite(self, precision_tol: float = 1e-8): - """Returns bool indicating if Choi operator :math:`\\mathcal{E}` of the networn is positive-semidefinite. + """Returns bool indicating if Choi operator :math:`\\mathcal{E}` of the network is positive-semidefinite. Args: precision_tol (float, optional): threshold value used to check if eigenvalues of @@ -478,20 +478,12 @@ def __truediv__(self, number: Union[float, int]): "It is not possible to divide a ``QuantumNetwork`` by a non-scalar.", ) - if self.pure() and number > 0.0: - return QuantumNetwork( - self.matrix(backend=self._backend) / np.sqrt(number), - partition=self.partition, - system_output=self.system_output, - pure=True, - backend=self._backend, - ) - + number = np.sqrt(number) if self.pure() and number > 0.0 else number return QuantumNetwork( self.matrix(backend=self._backend) / number, partition=self.partition, system_output=self.system_output, - pure=False, + pure=self.pure(), backend=self._backend, ) From 9b1634e400d3c7c47afa1bba19531bef45739f13 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 12:12:27 +0400 Subject: [PATCH 119/200] image for `comp_basis_encoder` --- doc/source/_static/comp_basis_encoder.png | Bin 0 -> 272260 bytes doc/source/api-reference/qibo.rst 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z9!23q)Ozp3a&PJev7#EXPsNd=S&?x;xa?D??j$X<&J_K)Qn}{Ns%;ud9fx}m2$2OK zBPoC8Tw@mdZY$U=45<3h_OOLq-xIFxi8MJ0JlNEI2~*j~@kyD7tZ$`=#o%BlL6CfS zbvv&;7>_eoQlhAT6&0S`Y&`9)-qpG0^8OO{xlBu9zLX{%{t2-RShO5#!0u2|a{m5n zF5fuDp6rUL`j78(16|u~`&UeDASIofUvuyVa#s28H+~&*<2CamUn|266l?o6XKtX8 zn_mqR8|d}-U&+`8`rm+mskR%F@#LFdd;|S&O8?%M|JyWwISw~A#{c&?TnB8weQa|5 T3!#5wHtf$i|AMjo?fSm}4>7;x literal 0 HcmV?d00001 diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 2058f41b26..0390a1a1c6 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -270,6 +270,13 @@ For instance, the following two circuit generations are equivalent: circuit_2.add(gates.X(2)) +.. image:: ../_static/comp_basis_encoder.png + :width: 3400px + :height: 2000px + :scale: 25 % + :align: center + + .. autofunction:: qibo.models.encodings.comp_basis_encoder From 8e719a395d5ad48ea2b4df99a697f68e047680e9 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 12:30:54 +0400 Subject: [PATCH 120/200] add `SiSWAPDG` gate --- src/qibo/backends/__init__.py | 1 + src/qibo/backends/npmatrices.py | 12 ++++++++++++ src/qibo/gates/gates.py | 33 +++++++++++++++++++++++++++++++++ tests/test_gates_gates.py | 2 ++ 4 files changed, 48 insertions(+) diff --git a/src/qibo/backends/__init__.py b/src/qibo/backends/__init__.py index 09e1fe1a54..9c99947881 100644 --- a/src/qibo/backends/__init__.py +++ b/src/qibo/backends/__init__.py @@ -115,6 +115,7 @@ def create(self, dtype): self.SWAP = self.matrices.SWAP self.iSWAP = self.matrices.iSWAP self.SiSWAP = self.matrices.SiSWAP + self.SiSWAPDG = self.matrices.SiSWAPDG self.FSWAP = self.matrices.FSWAP self.ECR = self.matrices.ECR self.SYC = self.matrices.SYC diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index 364845c514..ee65e90275 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -206,6 +206,18 @@ def SiSWAP(self): dtype=self.dtype, ) + @cached_property + def SiSWAPDG(self): + return self.np.array( + [ + [1, 0, 0, 0], + [0, 1 / self.np.sqrt(2), -1j / self.np.sqrt(2), 0], + [0, -1j / self.np.sqrt(2), 1 / self.np.sqrt(2), 0], + [0, 0, 0, 1], + ], + dtype=self.dtype, + ) + @cached_property def FSWAP(self): return self.np.array( diff --git a/src/qibo/gates/gates.py b/src/qibo/gates/gates.py index aa0e0d5ede..128518a89e 100644 --- a/src/qibo/gates/gates.py +++ b/src/qibo/gates/gates.py @@ -1533,6 +1533,39 @@ def __init__(self, q0, q1): self.init_args = [q0, q1] self.unitary = True + def _dagger(self) -> "Gate": + return SiSWAPDG(*self.qubits) + + +class SiSWAPDG(Gate): + """The :math:`\\sqrt{\\text{iSWAP}}}^{\\dagger}` gate. + + Corresponds to the following unitary matrix + + .. math:: + \\begin{pmatrix} + 1 & 0 & 0 & 0 \\\\ + 0 & 1/\\sqrt{2} & -i/\\sqrt{2} & 0 \\\\ + 0 & -i/\\sqrt{2} & 1/\\sqrt{2} & 0 \\\\ + 0 & 0 & 0 & 1 \\\\ + \\end{pmatrix} + + Args: + q0 (int): the first qubit to be swapped id number. + q1 (int): the second qubit to be swapped id number. + """ + + def __init__(self, q0, q1): + super().__init__() + self.name = "siswapdg" + self.draw_label = "sidg" + self.target_qubits = (q0, q1) + self.init_args = [q0, q1] + self.unitary = True + + def _dagger(self) -> "Gate": + return SiSWAP(*self.qubits) + class FSWAP(Gate): """The fermionic swap gate. diff --git a/tests/test_gates_gates.py b/tests/test_gates_gates.py index e014031eac..caabc73e57 100644 --- a/tests/test_gates_gates.py +++ b/tests/test_gates_gates.py @@ -1546,6 +1546,8 @@ def test_controlled_unitary_matrix(backend): ("GIVENS", (0, 1, 0.1)), ("RBS", (0, 1, 0.2)), ("ECR", (0, 1)), + ("SiSWAP", (0, 1)), + ("SiSWAPDG", (0, 1)), ] From a72a265b64e550e77ea642269d993b9ff809aa08 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Mon, 5 Feb 2024 12:49:12 +0400 Subject: [PATCH 121/200] concise test --- tests/test_quantum_info_random.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/test_quantum_info_random.py b/tests/test_quantum_info_random.py index b91ad4862a..0749723637 100644 --- a/tests/test_quantum_info_random.py +++ b/tests/test_quantum_info_random.py @@ -238,8 +238,7 @@ def test_random_statevector(backend, seed): # tests if random statevector is a pure state dims = 4 state = random_statevector(dims, seed=seed, backend=backend) - backend.assert_allclose(purity(state) <= 1.0 + PRECISION_TOL, True) - backend.assert_allclose(purity(state) >= 1.0 - PRECISION_TOL, True) + backend.assert_allclose(abs(purity(state) - 1.0) < PRECISION_TOL, True) @pytest.mark.parametrize("normalize", [False, True]) From e7afae18fbdaf69b41f2dad19c479deaaa3e732e Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Mon, 5 Feb 2024 15:41:37 +0400 Subject: [PATCH 122/200] added warning if connectivity is passed to star transpiler --- src/qibo/transpiler/placer.py | 10 +++++++--- src/qibo/transpiler/router.py | 10 +++++++--- 2 files changed, 14 insertions(+), 6 deletions(-) diff --git a/src/qibo/transpiler/placer.py b/src/qibo/transpiler/placer.py index c6b1f8f5fb..d57cc95428 100644 --- a/src/qibo/transpiler/placer.py +++ b/src/qibo/transpiler/placer.py @@ -4,7 +4,7 @@ import networkx as nx from qibo import gates -from qibo.config import raise_error +from qibo.config import log, raise_error from qibo.models import Circuit from qibo.transpiler._exceptions import PlacementError from qibo.transpiler.abstract import Placer, Router @@ -101,14 +101,18 @@ class StarConnectivityPlacer(Placer): def __init__(self, connectivity=None, middle_qubit: int = 2): self.middle_qubit = middle_qubit - self.connectivity = connectivity + if connectivity is not None: # pragma: no cover + log.warning( + "StarConnectivityRouter does not use the connectivity graph." + "The connectivity graph will be ignored." + ) def __call__(self, circuit: Circuit): """Apply the transpiler transformation on a given circuit. Args: circuit (:class:`qibo.models.circuit.Circuit`): The original Qibo circuit to transform. - This circuit must contain up to two-qubit gates. + Only single qubit gates and two qubits gates are supported by the router. Returns: (dict): physical to logical qubit mapping. diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 82f6ac1b7e..8a3bf54180 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -5,7 +5,7 @@ import networkx as nx from qibo import gates -from qibo.config import raise_error +from qibo.config import log, raise_error from qibo.models import Circuit from qibo.transpiler._exceptions import ConnectivityError from qibo.transpiler.abstract import Router @@ -60,14 +60,18 @@ class StarConnectivityRouter(Router): def __init__(self, connectivity=None, middle_qubit: int = 2): self.middle_qubit = middle_qubit - self.connectivity = connectivity + if connectivity is not None: # pragma: no cover + log.warning( + "StarConnectivityRouter does not use the connectivity graph." + "The connectivity graph will be ignored." + ) def __call__(self, circuit: Circuit, initial_layout: dict): """Apply the transpiler transformation on a given circuit. Args: circuit (:class:`qibo.models.circuit.Circuit`): The original Qibo circuit to transform. - This circuit must contain up to two-qubit gates. + Only single qubit gates and two qubits gates are supported by the router. initial_layout (dict): initial physical-to-logical qubit mapping, use `qibo.transpiler.placer.StarConnectivityPlacer` for better performance. From 73d8ba6ffff57cc19fe0be5413d7014836039e9c Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Mon, 5 Feb 2024 15:48:46 +0400 Subject: [PATCH 123/200] avoid log raise in default trasnpiler pipeline --- src/qibo/transpiler/pipeline.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/qibo/transpiler/pipeline.py b/src/qibo/transpiler/pipeline.py index 4452a90eca..06b047d773 100644 --- a/src/qibo/transpiler/pipeline.py +++ b/src/qibo/transpiler/pipeline.py @@ -206,9 +206,9 @@ def default(self): # preprocessing default_passes.append(Preprocessing(connectivity=self.connectivity)) # default placer pass - default_passes.append(StarConnectivityPlacer(connectivity=self.connectivity)) + default_passes.append(StarConnectivityPlacer()) # default router pass - default_passes.append(StarConnectivityRouter(connectivity=self.connectivity)) + default_passes.append(StarConnectivityRouter()) # default unroller pass default_passes.append(Unroller(native_gates=self.native_gates)) From f0ba5adfa670cb61d145aff353b5f04a3f4d179a Mon Sep 17 00:00:00 2001 From: Canoming Date: Mon, 5 Feb 2024 22:16:48 +0800 Subject: [PATCH 124/200] update doc strings for `QuantumNetwork` --- src/qibo/quantum_info/quantum_networks.py | 34 ++++++++++++++++++++--- 1 file changed, 30 insertions(+), 4 deletions(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 89c9a6a8e2..f7ea285373 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -1,4 +1,4 @@ -"""Module defining the QuantumNetwork class and adjacent functions.""" +"""Module defining the `QuantumNetwork` class and adjacent functions.""" import re from functools import reduce @@ -12,7 +12,19 @@ class QuantumNetwork: - """Quantum network object that holds a Choi operator as a tensor. + """ Quantum network that unifies the representation of quantum states, channels, + observables, and higher-order quantum operators [1]_. The class stores the Choi operator of + the quantum network as a tensor, which is an unique representation of the quantum network. + + A minimum quantum network is a quantum channel, which is a quantum network of the form + `J[n -> m]`, where `n` is the dimension of the input system and `m` is the dimension of the + output system. A quantum state is a quantum network of the form `J[1 -> n]`, such that the + input system is trivial. An observable is a quantum network of the form `J[n -> 1]`, such that + the output system is trivial. + + A quantum network may contain multipy input systems and output systems. For example, a + "quantum comb" is a quantum network of the form `J[n', n -> m, m']`, which convert a quantum + channel of the form `J[n -> m]` to a quantum channel of the form `J[n' -> m']`. Args: matrix (ndarray): input Choi operator. @@ -21,11 +33,15 @@ class QuantumNetwork: Choi operator. If ``None``, defaults to ``(False,True,False,True,...)``, where ``len(system_output)=len(partition)``. Defaults to ``None``. - pure (bool, optional): ``True`` when ``matrix`` is a rank-:math:`1` operator, - ``False`` otherwise. Defaults to ``False``. + pure (bool, optional): ``True`` when ``matrix`` is a "pure" representation (e.g. a pure + state, a unitary operator, etc.), ``False`` otherwise. Defaults to ``False``. backend (:class:`qibo.backends.abstract.Backend`, optional): Backend to be used in calculations. If ``None``, defaults to :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. + + References: + 1. G. Chiribella *et al.*, *Theoretical framework for quantum networks.* + `Physical Review A 80.2 (2009): 022339 `. """ def __init__( @@ -426,6 +442,11 @@ def __add__(self, second_network): def __mul__(self, number: Union[float, int]): """Returns quantum network with its Choi operator multiplied by a scalar. + If the quantum network is pure and ``number > 0.0``, the method returns a pure quantum + network with its Choi operator multiplied by the square root of ``number``. + This is equivelant to multiplying `self.to_full()` by the ``number``. + Otherwise, this method will return a full quantum network. + Args: number (float or int): scalar to multiply the Choi operator of the network with. @@ -465,6 +486,11 @@ def __rmul__(self, number: Union[float, int]): def __truediv__(self, number: Union[float, int]): """Returns quantum network with its Choi operator divided by a scalar. + If the quantum network is pure and ``number > 0.0``, the method returns a pure quantum + network with its Choi operator divided by the square root of ``number``. + This is equivelant to dividing `self.to_full()` by the ``number``. + Otherwise, this method will return a full quantum network. + Args: number (float or int): scalar to divide the Choi operator of the network with. From 09256fcc71c09037cf23ac93c18e4d049e5fda65 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 5 Feb 2024 14:42:32 +0000 Subject: [PATCH 125/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/quantum_info/quantum_networks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index f7ea285373..41c4c4acd4 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -12,7 +12,7 @@ class QuantumNetwork: - """ Quantum network that unifies the representation of quantum states, channels, + """Quantum network that unifies the representation of quantum states, channels, observables, and higher-order quantum operators [1]_. The class stores the Choi operator of the quantum network as a tensor, which is an unique representation of the quantum network. From a0a4c5321e63ee81e150215801fec8c5e36fbaaf Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 08:33:24 +0400 Subject: [PATCH 126/200] small fixes --- src/qibo/quantum_info/quantum_networks.py | 64 +++++++++++---------- tests/test_quantum_info_quantum_networks.py | 28 ++++----- 2 files changed, 49 insertions(+), 43 deletions(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 41c4c4acd4..5ae8902d43 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -12,19 +12,24 @@ class QuantumNetwork: - """Quantum network that unifies the representation of quantum states, channels, - observables, and higher-order quantum operators [1]_. The class stores the Choi operator of - the quantum network as a tensor, which is an unique representation of the quantum network. + """Quantum network is an object that unifies the representation of quantum states, channels, + observables, and higher-order quantum operators [1]. - A minimum quantum network is a quantum channel, which is a quantum network of the form - `J[n -> m]`, where `n` is the dimension of the input system and `m` is the dimension of the - output system. A quantum state is a quantum network of the form `J[1 -> n]`, such that the - input system is trivial. An observable is a quantum network of the form `J[n -> 1]`, such that - the output system is trivial. + This class stores the Choi operator of the quantum network as a tensor, + which is an unique representation of the quantum network. - A quantum network may contain multipy input systems and output systems. For example, a - "quantum comb" is a quantum network of the form `J[n', n -> m, m']`, which convert a quantum - channel of the form `J[n -> m]` to a quantum channel of the form `J[n' -> m']`. + A minimum quantum network is a quantum channel, which is a quantum network of the form + :math:`J[n \\to m]`, where :math:`n` is the dimension of the input system , + and :math:`m` is the dimension of the output system. + A quantum state is a quantum network of the form :math:`J[1 \\to n]`, + such that the input system is trivial. + An observable is a quantum network of the form :math:`J[n \\to 1]`, + such that the output system is trivial. + + A quantum network may contain multiple input and output systems. + For example, a "quantum comb" is a quantum network of the form :math:`J[n', n \\to m, m']`, + which convert a quantum channel of the form :math:`J[n \\to m]` + to a quantum channel of the form :math:`J[n' \\to m']`. Args: matrix (ndarray): input Choi operator. @@ -41,7 +46,7 @@ class QuantumNetwork: References: 1. G. Chiribella *et al.*, *Theoretical framework for quantum networks.* - `Physical Review A 80.2 (2009): 022339 `. + `Physical Review A 80.2 (2009): 022339 `_. """ def __init__( @@ -58,7 +63,7 @@ def __init__( self.partition = partition self.system_output = system_output self._pure = pure - self._backend = backend if backend is not None else GlobalBackend() + self._backend = backend self.dims = reduce(mul, self.partition) self._set_tensor_and_parameters() @@ -80,11 +85,11 @@ def matrix(self, backend=None): return backend.cast(self._matrix, dtype=self._matrix.dtype) - def pure(self): + def is_pure(self): """Returns bool indicading if the Choi operator of the network is pure.""" return self._pure - def hermitian( + def is_hermitian( self, order: Optional[Union[int, str]] = None, precision_tol: float = 1e-8 ): """Returns bool indicating if the Choi operator :math:`\\mathcal{E}` of the network is Hermitian. @@ -130,7 +135,7 @@ def hermitian( return float(norm) <= precision_tol - def unital( + def is_unital( self, order: Optional[Union[int, str]] = None, precision_tol: float = 1e-8 ): """Returns bool indicating if the Choi operator :math:`\\mathcal{E}` of the network is unital. @@ -178,7 +183,7 @@ def unital( return float(norm) <= precision_tol - def causal( + def is_causal( self, order: Optional[Union[int, str]] = None, precision_tol: float = 1e-8 ): """Returns bool indicating if the Choi operator :math:`\\mathcal{E}` of the network satisfies the causal order condition. @@ -226,7 +231,7 @@ def causal( return float(norm) <= precision_tol - def positive_semidefinite(self, precision_tol: float = 1e-8): + def is_positive_semidefinite(self, precision_tol: float = 1e-8): """Returns bool indicating if Choi operator :math:`\\mathcal{E}` of the network is positive-semidefinite. Args: @@ -244,7 +249,7 @@ def positive_semidefinite(self, precision_tol: float = 1e-8): reshaped = np.reshape(self._matrix, (self.dims, self.dims)) - if self.hermitian(): + if self.is_hermitian(): eigenvalues = np.linalg.eigvalsh(reshaped) else: if self._backend.__class__.__name__ in [ @@ -256,7 +261,7 @@ def positive_semidefinite(self, precision_tol: float = 1e-8): return all(eigenvalue >= -precision_tol for eigenvalue in eigenvalues) - def channel( + def is_channel( self, order: Optional[Union[int, str]] = None, precision_tol_causal: float = 1e-8, @@ -279,9 +284,9 @@ def channel( Returns: bool: Channel condition. """ - return self.causal(order, precision_tol_causal) and self.positive_semidefinite( - precision_tol_psd - ) + return self.is_causal( + order, precision_tol_causal + ) and self.is_positive_semidefinite(precision_tol_psd) def apply(self, state): """Apply the Choi operator :math:`\\mathcal{E}` to ``state`` :math:`\\varrho`. @@ -296,7 +301,7 @@ def apply(self, state): """ matrix = np.copy(self._matrix) - if self.pure(): + if self.is_pure(): return np.einsum("kj,ml,jl -> km", matrix, np.conj(matrix), state) return np.einsum("jklm,km -> jl", matrix, state) @@ -392,7 +397,7 @@ def to_full(self, backend=None): if backend is None: # pragma: no cover backend = self._backend - if self.pure(): + if self.is_pure(): self._matrix = self._full() self._pure = False @@ -460,7 +465,7 @@ def __mul__(self, number: Union[float, int]): "It is not possible to multiply a ``QuantumNetwork`` by a non-scalar.", ) - if self.pure() and number > 0.0: + if self.is_pure() and number > 0.0: return QuantumNetwork( np.sqrt(number) * self.matrix(backend=self._backend), partition=self.partition, @@ -504,12 +509,13 @@ def __truediv__(self, number: Union[float, int]): "It is not possible to divide a ``QuantumNetwork`` by a non-scalar.", ) - number = np.sqrt(number) if self.pure() and number > 0.0 else number + number = np.sqrt(number) if self.is_pure() and number > 0.0 else number + return QuantumNetwork( self.matrix(backend=self._backend) / number, partition=self.partition, system_output=self.system_output, - pure=self.pure(), + pure=self.is_pure(), backend=self._backend, ) @@ -643,7 +649,7 @@ def _set_tensor_and_parameters(self): def _full(self): """Reshapes input matrix based on purity.""" matrix = np.copy(self._matrix) - if self.pure(): + if self.is_pure(): matrix = np.einsum("jk,lm -> kjml", matrix, np.conj(matrix)) return matrix diff --git a/tests/test_quantum_info_quantum_networks.py b/tests/test_quantum_info_quantum_networks.py index a84103ece5..e02537eae1 100644 --- a/tests/test_quantum_info_quantum_networks.py +++ b/tests/test_quantum_info_quantum_networks.py @@ -46,13 +46,13 @@ def test_errors(backend): QuantumNetwork(channel.to_choi(backend=backend), partition=(1, 2), pure="True") with pytest.raises(ValueError): - network.hermitian(precision_tol=-1e-8) + network.is_hermitian(precision_tol=-1e-8) with pytest.raises(ValueError): - network.unital(precision_tol=-1e-8) + network.is_unital(precision_tol=-1e-8) with pytest.raises(ValueError): - network.causal(precision_tol=-1e-8) + network.is_causal(precision_tol=-1e-8) with pytest.raises(TypeError): network + 1 @@ -155,11 +155,11 @@ def test_parameters(backend): backend.assert_allclose(network.partition, partition) backend.assert_allclose(network.system_output, (False, True)) - assert network.causal() - assert network.unital() - assert network.hermitian() - assert network.positive_semidefinite() - assert network.channel() + assert network.is_causal() + assert network.is_unital() + assert network.is_hermitian() + assert network.is_positive_semidefinite() + assert network.is_channel() def test_with_states(backend): @@ -186,8 +186,8 @@ def test_with_states(backend): state_output_link.matrix(backend=backend).reshape((dims, dims)), state_output ) - assert network_state.hermitian() - assert network_state.positive_semidefinite() + assert network_state.is_hermitian() + assert network_state.is_positive_semidefinite() @pytest.mark.parametrize("subscript", ["jk,kl->jl", "jk,lj->lk"]) @@ -265,9 +265,9 @@ def test_non_hermitian_and_prints(backend): matrix = random_gaussian_matrix(dims**2, backend=backend) network = QuantumNetwork(matrix, (dims, dims), pure=False, backend=backend) - assert not network.hermitian() - assert not network.causal() - assert not network.positive_semidefinite() - assert not network.channel() + assert not network.is_hermitian() + assert not network.is_causal() + assert not network.is_positive_semidefinite() + assert not network.is_channel() assert network.__str__() == "J[4 -> 4]" From f6a794f7b5c11f0ba1e14addb3fa9586a1c18c24 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:06:48 +0400 Subject: [PATCH 127/200] add function --- src/qibo/backends/__init__.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/src/qibo/backends/__init__.py b/src/qibo/backends/__init__.py index 09e1fe1a54..04f26d870b 100644 --- a/src/qibo/backends/__init__.py +++ b/src/qibo/backends/__init__.py @@ -167,3 +167,10 @@ def set_threads(nthreads): if nthreads < 1: raise_error(ValueError, "Number of threads must be positive.") GlobalBackend().set_threads(nthreads) + + +def _check_backend(backend): # pragma: no cover + if backend is None: + return GlobalBackend() + + return backend From 6470632ba271a52676d7f3d2eaab31f75c2b0390 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:06:53 +0400 Subject: [PATCH 128/200] replacements --- src/qibo/gates/abstract.py | 8 +++--- src/qibo/gates/channels.py | 11 +++----- src/qibo/gates/special.py | 5 ++-- src/qibo/hamiltonians/hamiltonians.py | 20 +++++---------- src/qibo/models/circuit.py | 15 +++++------ src/qibo/models/error_mitigation.py | 37 ++++++++++++--------------- src/qibo/models/grover.py | 10 +++----- src/qibo/models/hep.py | 7 ++--- src/qibo/models/iqae.py | 6 ++--- src/qibo/models/tsp.py | 8 +++--- src/qibo/optimizers.py | 12 ++++----- src/qibo/parallel.py | 11 +++----- src/qibo/result.py | 6 ++--- 13 files changed, 62 insertions(+), 94 deletions(-) diff --git a/src/qibo/gates/abstract.py b/src/qibo/gates/abstract.py index d9f49f6a5e..a9b4ef0c2c 100644 --- a/src/qibo/gates/abstract.py +++ b/src/qibo/gates/abstract.py @@ -4,7 +4,7 @@ import sympy -from qibo.backends import CliffordBackend, GlobalBackend +from qibo.backends import _check_backend from qibo.config import raise_error REQUIRED_FIELDS = [ @@ -361,8 +361,7 @@ def matrix(self, backend=None): ``Gate.matrix`` was defined as an atribute in ``qibo`` versions prior to ``0.2.0``. From ``0.2.0`` on, it has been converted into a method and has replaced the ``asmatrix`` method. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) return backend.matrix(self) @@ -481,7 +480,6 @@ def substitute_symbols(self): self.parameters = tuple(params) def matrix(self, backend=None): - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) return backend.matrix_parametrized(self) diff --git a/src/qibo/gates/channels.py b/src/qibo/gates/channels.py index c620738da8..9616c59974 100644 --- a/src/qibo/gates/channels.py +++ b/src/qibo/gates/channels.py @@ -6,7 +6,7 @@ import numpy as np -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error from qibo.gates.abstract import Gate from qibo.gates.gates import I, Unitary, X, Y, Z @@ -80,8 +80,7 @@ def to_choi(self, nqubits: Optional[int] = None, order: str = "row", backend=Non vectorization, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) nqubits = 1 + max(self.target_qubits) if nqubits is None else nqubits @@ -128,8 +127,7 @@ def to_liouville(self, nqubits: int = None, order: str = "row", backend=None): choi_to_liouville, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) super_op = self.to_choi(nqubits=nqubits, order=order, backend=backend) super_op = choi_to_liouville(super_op, order=order, backend=backend) @@ -166,8 +164,7 @@ def to_pauli_liouville( from qibo.quantum_info.basis import comp_basis_to_pauli # pylint: disable=C0415 - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) super_op = self.to_liouville(nqubits=nqubits, backend=backend) diff --git a/src/qibo/gates/special.py b/src/qibo/gates/special.py index 5243b9fa52..3824f3672c 100644 --- a/src/qibo/gates/special.py +++ b/src/qibo/gates/special.py @@ -1,4 +1,4 @@ -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.gates.abstract import SpecialGate from qibo.gates.measurements import M @@ -104,8 +104,7 @@ def matrix(self, backend=None): Returns: ndarray: Matrix representation of special gate. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) return backend.matrix_fused(self) diff --git a/src/qibo/hamiltonians/hamiltonians.py b/src/qibo/hamiltonians/hamiltonians.py index 6354bf316b..10b9419580 100644 --- a/src/qibo/hamiltonians/hamiltonians.py +++ b/src/qibo/hamiltonians/hamiltonians.py @@ -24,14 +24,9 @@ class Hamiltonian(AbstractHamiltonian): """ def __init__(self, nqubits, matrix=None, backend=None): - if backend is None: # pragma: no cover - from qibo.backends import ( # pylint: disable=import-outside-toplevel - GlobalBackend, - ) + from qibo.backends import _check_backend - self.backend = GlobalBackend() - else: - self.backend = backend + self.backend = _check_backend(backend) if not ( isinstance(matrix, self.backend.tensor_types) @@ -355,14 +350,11 @@ def __init__(self, form=None, nqubits=None, symbol_map={}, backend=None): from qibo.symbols import Symbol # pylint: disable=import-outside-toplevel self._qiboSymbol = Symbol # also used in ``self._get_symbol_matrix`` - if backend is None: # pragma: no cover - from qibo.backends import ( # pylint: disable=import-outside-toplevel - GlobalBackend, - ) - self.backend = GlobalBackend() - else: - self.backend = backend + from qibo.backends import _check_backend + + self.backend = _check_backend(backend) + if form is not None: self.form = form if nqubits is not None: diff --git a/src/qibo/models/circuit.py b/src/qibo/models/circuit.py index 419f5635d2..e15223f9ef 100644 --- a/src/qibo/models/circuit.py +++ b/src/qibo/models/circuit.py @@ -1000,14 +1000,13 @@ def fuse(self, max_qubits=2): def unitary(self, backend=None): """Creates the unitary matrix corresponding to all circuit gates. - This is a ``(2 ** nqubits, 2 ** nqubits)`` matrix obtained by - multiplying all circuit gates. + This is a :math:`2^{n} \\times 2^{n}`` matrix obtained by + multiplying all circuit gates, where :math:`n` is ``nqubits``. """ - if backend is None: - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - backend = GlobalBackend() + backend = _check_backend(backend) fgate = gates.FusedGate(*range(self.nqubits)) for gate in self.queue: @@ -1050,10 +1049,10 @@ def compile(self, backend=None): NotImplementedError, "Circuit compilation is not available with callbacks.", ) - if backend is None: - from qibo.backends import GlobalBackend - backend = GlobalBackend() + from qibo.backends import _check_backend + + backend = _check_backend(backend) from qibo.result import CircuitResult, QuantumState diff --git a/src/qibo/models/error_mitigation.py b/src/qibo/models/error_mitigation.py index 1f69c07a10..9af448c564 100644 --- a/src/qibo/models/error_mitigation.py +++ b/src/qibo/models/error_mitigation.py @@ -6,7 +6,7 @@ from scipy.optimize import curve_fit from qibo import gates -from qibo.backends import GlobalBackend +from qibo.backends import GlobalBackend, _check_backend from qibo.config import raise_error @@ -148,8 +148,8 @@ def ZNE( 1. K. Temme, S. Bravyi et al, *Error mitigation for short-depth quantum circuits*. `arXiv:1612.02058 [quant-ph] `_. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + if readout is None: readout = {} @@ -197,8 +197,7 @@ def sample_training_circuit_cdr( Returns: :class:`qibo.models.Circuit`: The sampled circuit. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if replacement_gates is None: replacement_gates = [(gates.RZ, {"theta": n * np.pi / 2}) for n in range(4)] @@ -303,8 +302,8 @@ def CDR( 1. P. Czarnik, A. Arrasmith et al, *Error mitigation with Clifford quantum-circuit data*. `arXiv:2005.10189 [quant-ph] `_. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + if readout is None: readout = {} @@ -390,8 +389,8 @@ def vnCDR( 1. A. Lowe, MH. Gordon et al, *Unified approach to data-driven quantum error mitigation*. `arXiv:2011.01157 [quant-ph] `_. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + if readout is None: readout = {} @@ -495,8 +494,7 @@ def get_response_matrix( """ from qibo import Circuit # pylint: disable=import-outside-toplevel - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) response_matrix = np.zeros((2**nqubits, 2**nqubits)) @@ -599,8 +597,7 @@ def apply_randomized_readout_mitigation( random_pauli, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) meas_qubits = circuit.measurements[0].qubits nshots_r = int(nshots / ncircuits) @@ -672,8 +669,8 @@ def get_expectation_val_with_readout_mitigation( Returns: float: the mitigated expectation value of the observable. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + if readout is None: # pragma: no cover readout = {} @@ -719,8 +716,7 @@ def sample_clifford_training_circuit( random_clifford, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) non_clifford_gates_indices = [ i @@ -783,8 +779,7 @@ def error_sensitive_circuit(circuit, observable, backend=None): vectorization, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) sampled_circuit = sample_clifford_training_circuit(circuit, backend=backend) unitary_matrix = sampled_circuit.unitary(backend=backend) @@ -882,8 +877,8 @@ def ICS( 1. Dayue Qin, Yanzhu Chen et al, *Error statistics and scalability of quantum error mitigation formulas*. `arXiv:2112.06255 [quant-ph] `_. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + if readout is None: readout = {} diff --git a/src/qibo/models/grover.py b/src/qibo/models/grover.py index 2da268aa97..c18fab512e 100644 --- a/src/qibo/models/grover.py +++ b/src/qibo/models/grover.py @@ -188,10 +188,9 @@ def iterative_grover(self, lamda_value=6 / 5, backend=None): measured (str): bitstring measured and checked as a valid solution. total_iterations (int): number of times the oracle has been called. """ - if backend is None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - backend = GlobalBackend() + backend = _check_backend(backend) k = 1 lamda = lamda_value @@ -225,10 +224,9 @@ def execute(self, nshots=100, freq=False, logs=False, backend=None): solution (str): bitstring (or list of bitstrings) measured as solution of the search. iterations (int): number of oracle calls done to reach a solution. """ - if backend is None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - backend = GlobalBackend() + backend = _check_backend(backend) if (self.num_sol or self.targ_a) and not self.iterative: if self.targ_a: diff --git a/src/qibo/models/hep.py b/src/qibo/models/hep.py index 13466cab4e..e03429136e 100644 --- a/src/qibo/models/hep.py +++ b/src/qibo/models/hep.py @@ -41,12 +41,9 @@ def __init__(self, ansatz, layers, nqubits, multi_output=False, backend=None): self.circuit, self.rotation, self.nparams = ansatz_function(layers, nqubits) # load backend - if backend is None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - self.backend = GlobalBackend() - else: - self.backend = backend + self.backend = _check_backend(backend) # load hamiltonian if multi_output: diff --git a/src/qibo/models/iqae.py b/src/qibo/models/iqae.py index 081c787a1a..caf28e72b7 100644 --- a/src/qibo/models/iqae.py +++ b/src/qibo/models/iqae.py @@ -264,10 +264,10 @@ def execute(self, backend=None): Returns: A :class:`qibo.models.iqae.IterativeAmplitudeEstimationResult` results object. """ - if backend is None: - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend + + backend = _check_backend(backend) - backend = GlobalBackend() # Initializing all parameters k = [0] # uppercase_k=4k+2 diff --git a/src/qibo/models/tsp.py b/src/qibo/models/tsp.py index 3db11f818e..250360aa84 100644 --- a/src/qibo/models/tsp.py +++ b/src/qibo/models/tsp.py @@ -135,12 +135,10 @@ def qaoa_function_of_layer(layer, distance_matrix): """ def __init__(self, distance_matrix, backend=None): - if backend is None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend + + self.backend = _check_backend(backend) - self.backend = GlobalBackend() - else: - self.backend = backend self.distance_matrix = distance_matrix self.num_cities = distance_matrix.shape[0] self.two_to_one = calculate_two_to_one(self.num_cities) diff --git a/src/qibo/optimizers.py b/src/qibo/optimizers.py index 92eed2fbeb..0b5c46c778 100644 --- a/src/qibo/optimizers.py +++ b/src/qibo/optimizers.py @@ -86,16 +86,16 @@ def myloss(parameters, circuit): ) return cmaes(loss, initial_parameters, args, options) elif method == "sgd": - if backend is None: - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend + + backend = _check_backend(backend) - backend = GlobalBackend() return sgd(loss, initial_parameters, args, options, compile, backend) else: - if backend is None: - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend + + backend = _check_backend(backend) - backend = GlobalBackend() return newtonian( loss, initial_parameters, diff --git a/src/qibo/parallel.py b/src/qibo/parallel.py index 0bbf84f055..22a65fafe7 100644 --- a/src/qibo/parallel.py +++ b/src/qibo/parallel.py @@ -6,7 +6,7 @@ from joblib import Parallel, delayed -from qibo.backends import GlobalBackend, set_threads +from qibo.backends import _check_backend from qibo.config import raise_error @@ -39,8 +39,7 @@ def parallel_execution(circuit, states, processes=None, backend=None): Returns: Circuit evaluation for input states. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if states is None or not isinstance(states, list): # pragma: no cover raise_error(TypeError, "states must be a list.") @@ -88,8 +87,7 @@ def parallel_circuits_execution( Returns: Circuit evaluation for input states. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if not isinstance(circuits, Iterable): # pragma: no cover raise_error(TypeError, "circuits must be iterable.") @@ -165,8 +163,7 @@ def parallel_parametrized_execution( Returns: Circuit evaluation for input parameters. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if not isinstance(parameters, list): # pragma: no cover raise_error(TypeError, "parameters must be a list.") diff --git a/src/qibo/result.py b/src/qibo/result.py index be095d5bfa..5d74157007 100644 --- a/src/qibo/result.py +++ b/src/qibo/result.py @@ -31,11 +31,9 @@ class QuantumState: """ def __init__(self, state, backend=None): - if backend is None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - backend = GlobalBackend() - self.backend = backend + self.backend = _check_backend(backend) self.density_matrix = len(state.shape) == 2 self.nqubits = int(np.log2(state.shape[0])) self._state = state From aa91b01a81dab9ca00718010fd89c706a4fb5ffb Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:13:34 +0400 Subject: [PATCH 129/200] replacements --- src/qibo/quantum_info/basis.py | 11 ++--- src/qibo/quantum_info/metrics.py | 45 +++++++------------ src/qibo/quantum_info/quantum_networks.py | 5 +-- src/qibo/quantum_info/random_ensembles.py | 5 +-- .../superoperator_transformations.py | 38 ++++++---------- src/qibo/quantum_info/utils.py | 20 +++------ src/qibo/transpiler/unitary_decompositions.py | 14 +++--- 7 files changed, 49 insertions(+), 89 deletions(-) diff --git a/src/qibo/quantum_info/basis.py b/src/qibo/quantum_info/basis.py index 119cf78380..dcb5d7ab84 100644 --- a/src/qibo/quantum_info/basis.py +++ b/src/qibo/quantum_info/basis.py @@ -5,7 +5,7 @@ import numpy as np from qibo import matrices -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import raise_error from qibo.quantum_info.superoperator_transformations import vectorization @@ -89,8 +89,7 @@ def pauli_basis( "sparse representation is not implemented for unvectorized Pauli basis.", ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) pauli_labels = {"I": matrices.I, "X": matrices.X, "Y": matrices.Y, "Z": matrices.Z} basis_single = [pauli_labels[label] for label in pauli_order] @@ -187,8 +186,7 @@ def comp_basis_to_pauli( array with their row-wise indexes. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if sparse: elements, indexes = pauli_basis( @@ -258,8 +256,7 @@ def pauli_to_comp_basis( tuple is composed of array of non-zero elements and an array with their row-wise indexes. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) unitary = pauli_basis( nqubits, diff --git a/src/qibo/quantum_info/metrics.py b/src/qibo/quantum_info/metrics.py index eb29f1b486..41f4740f8f 100644 --- a/src/qibo/quantum_info/metrics.py +++ b/src/qibo/quantum_info/metrics.py @@ -5,7 +5,7 @@ import numpy as np from scipy import sparse -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error @@ -79,8 +79,7 @@ def concurrence(state, bipartition, check_purity: bool = True, backend=None): Returns: float: Concurrence of :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) not in [1, 2]) @@ -157,8 +156,7 @@ def entanglement_of_formation( Returns: float: entanglement of formation of state :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) from qibo.quantum_info.utils import shannon_entropy # pylint: disable=C0415 @@ -202,8 +200,7 @@ def entropy( Returns: float: The von-Neumann entropy :math:`S` of ``state`` :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -289,8 +286,7 @@ def entanglement_entropy( Returns: float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if base <= 0.0: raise_error(ValueError, "log base must be non-negative.") @@ -348,8 +344,7 @@ def trace_distance(state, target, check_hermitian: bool = False, backend=None): Returns: float: Trace distance between ``state`` :math:`\\rho` and ``target`` :math:`\\sigma`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if state.shape != target.shape: raise_error( @@ -470,8 +465,7 @@ def fidelity(state, target, check_hermitian: bool = False, backend=None): Returns: float: Fidelity between ``state`` :math:`\\rho` and ``target`` :math:`\\sigma`. """ - if backend is None: - backend = GlobalBackend() + backend = _check_backend(backend) if state.shape != target.shape: raise_error( @@ -666,8 +660,7 @@ def entanglement_fidelity( Returns: float: Entanglement fidelity :math:`F_{\\mathcal{E}}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(nqubits, int) is False: raise_error( @@ -733,8 +726,7 @@ def process_fidelity(channel, target=None, check_unitary: bool = False, backend= Returns: float: Process fidelity between ``channel`` and ``target``. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if target is not None: if channel.shape != target.shape: @@ -938,8 +930,8 @@ def diamond_norm(channel, target=None, backend=None, **kwargs): # `CVXPY` only works with `numpy`, so this function has to # convert any channel to the `numpy` backend by default - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) + channel = backend.to_numpy(channel) channel = np.transpose(channel) @@ -1025,8 +1017,7 @@ def meyer_wallach_entanglement(circuit, backend=None): float: Meyer-Wallach entanglement. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) circuit.density_matrix = True nqubits = circuit.nqubits @@ -1086,8 +1077,7 @@ def entangling_capability(circuit, samples: int, seed=None, backend=None): TypeError, "seed must be either type int or numpy.random.Generator." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) local_state = ( np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed @@ -1151,8 +1141,7 @@ def expressibility( pqc_integral, ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) deviation = haar_integral( circuit.nqubits, power_t, samples=None, backend=backend @@ -1214,8 +1203,7 @@ def frame_potential( TypeError, f"samples must be type int, but it is type {type(samples)}." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) nqubits = circuit.nqubits dim = 2**nqubits @@ -1259,8 +1247,7 @@ def _check_hermitian_or_not_gpu(matrix, backend=None): `backend` is not :class:`qibojit.backends.CupyBackend` """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) norm = backend.calculate_norm_density_matrix( np.transpose(np.conj(matrix)) - matrix, order=2 diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index af549a46fa..b9d5b01f96 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -7,7 +7,7 @@ import numpy as np -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import raise_error @@ -593,8 +593,7 @@ def _run_checks(self, partition, system_output, pure): def _set_tensor_and_parameters(self): """Sets tensor based on inputs.""" - if self._backend is None: - self._backend = GlobalBackend() + self._backend = _check_backend(self._backend) if isinstance(self.partition, list): self.partition = tuple(self.partition) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 18e2eedaa1..f8da6a6825 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -7,7 +7,7 @@ from scipy.stats import rv_continuous from qibo import Circuit, gates -from qibo.backends import GlobalBackend, NumpyBackend +from qibo.backends import NumpyBackend, _check_backend from qibo.config import MAX_ITERATIONS, PRECISION_TOL, raise_error from qibo.quantum_info.basis import comp_basis_to_pauli from qibo.quantum_info.superoperator_transformations import ( @@ -1201,8 +1201,7 @@ def _set_backend_and_local_state(seed, backend): TypeError, "seed must be either type int or numpy.random.Generator." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if seed is None or isinstance(seed, int): if backend.__class__.__name__ in [ diff --git a/src/qibo/quantum_info/superoperator_transformations.py b/src/qibo/quantum_info/superoperator_transformations.py index b91dadbeb1..c888ed5b18 100644 --- a/src/qibo/quantum_info/superoperator_transformations.py +++ b/src/qibo/quantum_info/superoperator_transformations.py @@ -6,7 +6,7 @@ import numpy as np from scipy.optimize import minimize -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error from qibo.gates.abstract import Gate from qibo.gates.gates import Unitary @@ -61,8 +61,7 @@ def vectorization(state, order: str = "row", backend=None): f"order must be either 'row' or 'column' or 'system', but it is {order}.", ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if len(state.shape) == 1: state = np.outer(state, np.conj(state)) @@ -130,8 +129,7 @@ def unvectorization(state, order: str = "row", backend=None): f"order must be either 'row' or 'column' or 'system', but it is {order}.", ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) dim = int(np.sqrt(len(state))) @@ -449,8 +447,7 @@ def choi_to_kraus( f"validate_cp must be type bool, but it is type {type(validate_cp)}.", ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if validate_cp: norm = float( @@ -652,8 +649,7 @@ def kraus_to_choi(kraus_ops, order: str = "row", backend=None): Returns: ndarray: Choi representation of the Kraus channel. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) gates, target_qubits = _set_gate_and_target_qubits(kraus_ops) nqubits = 1 + max(target_qubits) @@ -782,8 +778,7 @@ def kraus_to_chi( """ from qibo.quantum_info.basis import comp_basis_to_pauli - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) gates, target_qubits = _set_gate_and_target_qubits(kraus_ops) nqubits = 1 + max(target_qubits) @@ -845,8 +840,7 @@ def kraus_to_stinespring( Returns: ndarray: Stinespring representation (restricted unitary) of the Kraus channel. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if initial_state_env is not None: if len(initial_state_env) != len(kraus_ops): @@ -963,8 +957,7 @@ def liouville_to_pauli( """ from qibo.quantum_info.basis import comp_basis_to_pauli - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) dim = int(np.sqrt(len(super_op))) nqubits = int(np.log2(dim)) @@ -1165,8 +1158,7 @@ def pauli_to_liouville( """ from qibo.quantum_info.basis import pauli_to_comp_basis - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) dim = int(np.sqrt(len(pauli_op))) nqubits = int(np.log2(dim)) @@ -1873,8 +1865,7 @@ def stinespring_to_kraus( Returns: ndarray: Kraus operators. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(dim_env, int) is False: raise_error( @@ -2038,8 +2029,7 @@ def kraus_to_unitaries( if precision_tol < 0.0: raise_error(ValueError, "precision_tol must be non-negative.") - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) target_qubits = [q for q, _ in kraus_ops] nqubits = 1 + np.max(target_qubits) @@ -2148,8 +2138,7 @@ def _reshuffling(super_op, order: str = "row", backend=None): NotImplementedError, "reshuffling not implemented for system vectorization." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) dim = np.sqrt(super_op.shape[0]) @@ -2215,8 +2204,7 @@ def _individual_kraus_to_liouville( to be used in :func:`qibo.quantum_info.kraus_to_unitaries`. In principle, this should be not be accessible to users. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) gates, target_qubits = _set_gate_and_target_qubits(kraus_ops) nqubits = 1 + max(target_qubits) diff --git a/src/qibo/quantum_info/utils.py b/src/qibo/quantum_info/utils.py index c1e411360a..e099c96f8e 100644 --- a/src/qibo/quantum_info/utils.py +++ b/src/qibo/quantum_info/utils.py @@ -9,7 +9,7 @@ import numpy as np from qibo import matrices -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error @@ -134,8 +134,7 @@ def hadamard_transform(array, implementation: str = "fast", backend=None): Returns: ndarray: (Fast) Hadamard Transform of ``array``. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( len(array.shape) not in [1, 2] @@ -210,8 +209,7 @@ def shannon_entropy(probability_array, base: float = 2, backend=None): Returns: (float): The Shannon entropy :math:`H(\\mathcal{p})`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(probability_array, list): probability_array = backend.cast(probability_array, dtype=np.float64) @@ -281,8 +279,7 @@ def total_variation_distance( Returns: float: Total variation distance between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist_p, list): prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) @@ -341,8 +338,7 @@ def hellinger_distance(prob_dist_p, prob_dist_q, validate: bool = False, backend Returns: (float): Hellinger distance :math:`H(p, q)`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist_p, list): prob_dist_p = backend.cast(prob_dist_p, dtype=np.float64) @@ -454,8 +450,7 @@ def haar_integral( TypeError, f"samples must be type int, but it is type {type(samples)}." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) dim = 2**nqubits @@ -529,8 +524,7 @@ def pqc_integral(circuit, power_t: int, samples: int, backend=None): TypeError, f"samples must be type int, but it is type {type(samples)}." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) circuit.density_matrix = True dim = 2**circuit.nqubits diff --git a/src/qibo/transpiler/unitary_decompositions.py b/src/qibo/transpiler/unitary_decompositions.py index e737ba649e..472347b0d4 100644 --- a/src/qibo/transpiler/unitary_decompositions.py +++ b/src/qibo/transpiler/unitary_decompositions.py @@ -1,7 +1,7 @@ import numpy as np from qibo import gates, matrices -from qibo.backends import GlobalBackend, NumpyBackend +from qibo.backends import NumpyBackend, _check_backend from qibo.config import raise_error magic_basis = np.array( @@ -50,8 +50,7 @@ def calculate_psi(unitary, magic_basis=magic_basis, backend=None): Returns: (ndarray) Eigenvectors in the computational basis and eigenvalues of :math:`U^{T} U`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if backend.__class__.__name__ in [ "CupyBackend", @@ -154,9 +153,8 @@ def calculate_diagonal(unitary, ua, ub, va, vb): def magic_decomposition(unitary, backend=None): - if backend is None: # pragma: no cover - backend = GlobalBackend() """Decomposes an arbitrary unitary to (A1) from arXiv:quant-ph/0011050.""" + backend = _check_backend(backend) psi, eigvals = calculate_psi(unitary, backend=backend) psi_tilde = np.conj(np.sqrt(eigvals)) * np.dot(unitary, psi) va, vb = calculate_single_qubit_unitaries(psi) @@ -167,8 +165,7 @@ def magic_decomposition(unitary, backend=None): def to_bell_diagonal(ud, bell_basis=bell_basis, backend=None): """Transforms a matrix to the Bell basis and checks if it is diagonal.""" - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) ud = backend.cast(ud) bell_basis = backend.cast(bell_basis, dtype=bell_basis.dtype) @@ -248,8 +245,7 @@ def two_qubit_decomposition(q0, q1, unitary, backend=None): Returns: (list): gates implementing decomposition (24) from arXiv:quant-ph/0307177 """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) ud_diag = to_bell_diagonal(unitary, backend=backend) ud = None From 211b72cd32a8e6439bbf38e3560d79a3174e5185 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:18:29 +0400 Subject: [PATCH 130/200] fix coverage --- tests/test_models_encodings.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/tests/test_models_encodings.py b/tests/test_models_encodings.py index ac997460c2..63cae6836b 100644 --- a/tests/test_models_encodings.py +++ b/tests/test_models_encodings.py @@ -98,9 +98,10 @@ def test_phase_encoder(backend, rotation, kind): backend.assert_allclose(state, target) +@pytest.mark.parametrize("kind", [None, list]) @pytest.mark.parametrize("architecture", ["tree", "diagonal"]) @pytest.mark.parametrize("nqubits", [8]) -def test_unary_encoder(backend, nqubits, architecture): +def test_unary_encoder(backend, nqubits, architecture, kind): sampler = np.random.default_rng(1) with pytest.raises(TypeError): @@ -126,6 +127,9 @@ def test_unary_encoder(backend, nqubits, architecture): data = 2 * sampler.random(nqubits) - 1 data = backend.cast(data, dtype=data.dtype) + if kind is not None: + data = kind(data) + circuit = unary_encoder(data, architecture=architecture) state = backend.execute_circuit(circuit).state() indexes = np.flatnonzero(state) From 63212934298aa5eaa3966b0f7e8d1ac12f5f18c9 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:22:46 +0400 Subject: [PATCH 131/200] more replacements --- src/qibo/backends/clifford.py | 5 ++--- src/qibo/noise_model.py | 5 ++--- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/src/qibo/backends/clifford.py b/src/qibo/backends/clifford.py index 9141ca2fd9..8189287f82 100644 --- a/src/qibo/backends/clifford.py +++ b/src/qibo/backends/clifford.py @@ -538,10 +538,9 @@ class CliffordBackend(NumpyBackend): def __init__(self, engine=None): super().__init__() - if engine is None: - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - engine = GlobalBackend() + engine = _check_backend(engine) if isinstance(engine, TensorflowBackend): raise_error( diff --git a/src/qibo/noise_model.py b/src/qibo/noise_model.py index 892eb48743..44311c2661 100644 --- a/src/qibo/noise_model.py +++ b/src/qibo/noise_model.py @@ -341,10 +341,9 @@ def fit( from scipy.optimize import Bounds, direct - if backend == None: # pragma: no cover - from qibo.backends import GlobalBackend + from qibo.backends import _check_backend - backend = GlobalBackend() + backend = _check_backend(backend) nshots = target_result.nshots target_prob = freq_to_prob(target_result.frequencies()) From a87ef8509220d93a166d76fc779a12eec3d0216a Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 09:43:14 +0400 Subject: [PATCH 132/200] move couple of lines to `qibo.rst` --- doc/source/api-reference/qibo.rst | 7 +++++++ src/qibo/quantum_info/quantum_networks.py | 9 +-------- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 980faf2c70..6d83e5446c 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -1680,6 +1680,13 @@ Frame Potential Quantum Networks ^^^^^^^^^^^^^^^^ +Quantum network is an object that unifies the representation of quantum states, channels, +observables, and higher-order quantum operators. + +For more details, see G. Chiribella *et al.*, *Theoretical framework for quantum networks*, +`Physical Review A 80.2 (2009): 022339 +`_. + .. autoclass:: qibo.quantum_info.quantum_networks.QuantumNetwork :members: :member-order: bysource diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 5ae8902d43..a5ba0a77af 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -12,10 +12,7 @@ class QuantumNetwork: - """Quantum network is an object that unifies the representation of quantum states, channels, - observables, and higher-order quantum operators [1]. - - This class stores the Choi operator of the quantum network as a tensor, + """This class stores the Choi operator of the quantum network as a tensor, which is an unique representation of the quantum network. A minimum quantum network is a quantum channel, which is a quantum network of the form @@ -43,10 +40,6 @@ class QuantumNetwork: backend (:class:`qibo.backends.abstract.Backend`, optional): Backend to be used in calculations. If ``None``, defaults to :class:`qibo.backends.GlobalBackend`. Defaults to ``None``. - - References: - 1. G. Chiribella *et al.*, *Theoretical framework for quantum networks.* - `Physical Review A 80.2 (2009): 022339 `_. """ def __init__( From d8a56d063af5008333bdc58770fdced93ebc26ba Mon Sep 17 00:00:00 2001 From: Andrea Date: Tue, 6 Feb 2024 10:09:45 +0400 Subject: [PATCH 133/200] doc: Add possibility to show source code --- doc/source/conf.py | 1 + 1 file changed, 1 insertion(+) diff --git a/doc/source/conf.py b/doc/source/conf.py index be2efea28d..4937bd5889 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -43,6 +43,7 @@ "sphinx.ext.napoleon", "sphinx.ext.intersphinx", "sphinx_copybutton", + "sphinx.ext.viewcode", "recommonmark", "nbsphinx", ] From 68ad0a24104ebfe5df53bc4cc5a50f8ef663e2a3 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 11:04:37 +0400 Subject: [PATCH 134/200] new figures --- doc/source/_static/unary_encoder_ladder.png | Bin 0 -> 186988 bytes doc/source/_static/unary_encoder_tree.png | Bin 0 -> 177114 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 doc/source/_static/unary_encoder_ladder.png create mode 100644 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zMHd-9vT9*?#>S0+7OSW*DIw)W|hgu95G}Wjmc!;s1#IQ~E{S-FW@ay{?iiQhC z1R~|~fu)wskTVne+lyToHJnKm^(j!|x{FI)_#;YR0c11`u(CiRI{8mVB^knaG&9Uq z2{$AXpJvU5%DLi38b49VW@H}fl4{rxy|qyBV|uJu;bDMU{cZEsUds!xx1VyQ0_{Ho zlhdDD5AhxADrR}hTa?&9Cxmo2X%{=6s!e4LT|^gyBsHwn@+Nk|y|rid+dcVTZRvq` zCXQvUn{~^fnG3WquIr<1lqgwb3X%tw9qzO4_wn{Nvx%xjkI7>q%J7uAEBDtLs(owe z13{Xo5Rhzp{_;2_zwMxVz2fLNtJ55wlWGG*3^-l0&^MUr$OOY_P^peKr*m6ICw+@L z3Ron9Eh26(HLw{IA>p!A>x0{v)yCDP8{2wR7UtSrymxjL>FpL!zd%72dzIPB%^?M(v?=BfX(swx5gy#OTQONd_5`A}un zfZ>!~5O&=ODJDqCp!KM)1-6fRoYg0eE)1Z-X*lAq)3=vjE&!V=h23kFw1_#^uJZ zua?kk2|%LN>rEcBVKS&Z8jYrAiic1aC{;JPylc!($6VeGmH_9@Ke}#{n+z=*yW}+< zi<;>W<|Ejg<}3#E4TsfFeI=q%tG?-R>^p^G1uGaqYG#&`H$xkovxmn&hYpsxskKS9(XEI70VW2C;{X5v literal 0 HcmV?d00001 From 7e4ebb739b9e47011f95b67c7317a92cf5e95e82 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 11:04:58 +0400 Subject: [PATCH 135/200] better doc --- doc/source/api-reference/qibo.rst | 58 +++++++++++++++++++++++++++++++ src/qibo/models/encodings.py | 43 +++-------------------- 2 files changed, 62 insertions(+), 39 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index 0390a1a1c6..c28aee53cf 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -319,12 +319,70 @@ For instance, the following two circuit generations are equivalent: Unary Encoder """"""""""""" +Given a classical ``data`` array :math:`\mathbf{x} \in \mathbb{R}^{d}` such that + +.. math:: + \mathbf{x} = (x_{1}, x_{2}, \dots, x_{d}) \, , + +this function generate the circuit that prepares the following quantum state +:math:`\ket{\psi} \in \mathcal{H}`: + +.. math:: + \ket{\psi} = \frac{1}{\|\mathbf{x}\|_{\textup{HS}}} \, + \sum_{k=1}^{d} \, x_{k} \, \ket{k} \, , + +with :math:`\mathcal{H} \cong \mathbb{C}^{d}` being a :math:`d`-qubit Hilbert space, +and :math:`\|\cdot\|_{\textup{HS}}` being the Hilbert-Schmidt norm. + +Here, :math:`\ket{k}` is a unary representation of the number :math:`k`. +For instance, for :math:`d = 3`, the final state would be + +.. math:: + \ket{\psi} = \frac{1}{\|\mathbf{x}\|_{\textup{HS}}} \, + \left( x_{1} \ket{001} + x_{2} \ket{010} + x_{3} \ket{100} \right) \, . + +There are multiple circuit architechtures that lead to unary encoding of classical data. +For example, to encode a :math:`8`-dimensional data, one could use the so-called +*tree* architechture below: + +.. image:: ../_static/unary_encoder_tree.png + :width: 2000px + :height: 2329px + :scale: 30 % + :align: center + +where the first gate is the :class:`qibo.gates.X` +and the parametrized gates are the :class:`qibo.gates.RBS`. +To know how the angles :math:`\{\theta_{k}\}_{[k]}` are calculated for this architecture, +please refer to S. Johri *et al.*, *Nearest Centroid Classification on a Trapped Ion Quantum Computer*, +`arXiv:2012.04145v2 [quant-ph] `_. + +On the other hand, the same encoding could be performed using the so-called +*diagonal* (also known as *ladder*) architecture below: + +.. image:: ../_static/unary_encoder_ladder.png + :width: 2800px + :height: 2329px + :scale: 30 % + :align: center + +This architecture leads to a choice of angles based on +`spherical coordinates in a d-dimensional hypersphere +`_. + + .. autofunction:: qibo.models.encodings.unary_encoder Unary Encoder for Random Gaussian States """""""""""""""""""""""""""""""""""""""" +Performs the same unary encoder as :class:`qibo.models.encodings.unary_encoder` +using the *tree* architecture , with the difference being that now each entry +of the :math:`d`-dimensional array is sampled from a Gaussian distribution +:math:`\mathcal{N}(0, 1)`. + + .. autofunction:: qibo.models.encodings.unary_encoder_random_gaussian diff --git a/src/qibo/models/encodings.py b/src/qibo/models/encodings.py index ba0e5a4352..8d37bb8922 100644 --- a/src/qibo/models/encodings.py +++ b/src/qibo/models/encodings.py @@ -112,24 +112,7 @@ def phase_encoder(data, rotation: str = "RY"): def unary_encoder(data, architecture: str = "tree"): - """Creates circuit that performs the unary encoding of ``data``. - - Given a classical ``data`` array :math:`\\mathbf{x} \\in \\mathbb{R}^{d}` such that - - .. math:: - \\mathbf{x} = (x_{1}, x_{2}, \\dots, x_{d}) \\, , - - this function generate the circuit that prepares the following quantum state - :math:`\\ket{\\psi} \\in \\mathcal{H}`: - - .. math:: - \\ket{\\psi} = \\frac{1}{\\|\\mathbf{x}\\|_{\\textup{HS}}} \\, - \\sum_{k=1}^{d} \\, x_{k} \\, \\ket{k} \\, , - - with :math:`\\mathcal{H} \\cong \\mathbb{C}^{d}` being a :math:`d`-qubit Hilbert space, - and :math:`\\|\\cdot\\|_{\\textup{HS}}` being the Hilbert-Schmidt norm. - Here, :math:`\\ket{k}` is a unary representation of the number :math:`1` through - :math:`d`. + """Creates circuit that performs the (deterministic) unary encoding of ``data``. Args: data (ndarray): :math:`1`-dimensional array of data to be loaded. @@ -140,10 +123,6 @@ def unary_encoder(data, architecture: str = "tree"): Returns: :class:`qibo.models.circuit.Circuit`: circuit that loads ``data`` in unary representation. - - References: - 1. S. Johri *et al.*, *Nearest Centroid Classification on a Trapped Ion Quantum Computer*. - `arXiv:2012.04145v2 [quant-ph] `_. """ if isinstance(data, list): data = np.array(data) @@ -187,26 +166,12 @@ def unary_encoder(data, architecture: str = "tree"): def unary_encoder_random_gaussian(nqubits: int, architecture: str = "tree", seed=None): """Creates a circuit that performs the unary encoding of a random Gaussian state. - Given :math:`d` qubits, encodes the quantum state - :math:`\\ket{\\psi} \\in \\mathcal{H}` such that - - - .. math:: - \\ket{\\psi} = \\frac{1}{\\|\\mathbf{x}\\|_{\\textup{HS}}} \\, - \\sum_{k=1}^{d} \\, x_{k} \\, \\ket{k} - - where :math:`x_{k}` are independent Gaussian random variables, - :math:`\\mathcal{H} \\cong \\mathbb{C}^{d}` is a :math:`d`-qubit Hilbert space, - and :math:`\\|\\cdot\\|_{\\textup{HS}}` being the Hilbert-Schmidt norm. - Here, :math:`\\ket{k}` is a unary representation of the number :math:`1` through - :math:`d`. - - At depth :math:`h`, the angles :math:`\\theta_{k} \\in [0, 2\\pi]` of the the + At depth :math:`h` of the tree architecture, the angles :math:`\\theta_{k} \\in [0, 2\\pi]` of the the gates :math:`RBS(\\theta_{k})` are sampled from the following probability density function: .. math:: - p_{h}(\\theta) = \\frac{1}{2} \\, \\frac{\\Gamma(2^{h-1})}{\\Gamma^{2}(2^{h-2})} - \\abs{\\sin(\\theta) \\, \\cos(\\theta)}^{2^{h-1} - 1} \\, , + p_{h}(\\theta) = \\frac{1}{2} \\, \\frac{\\Gamma(2^{h-1})}{\\Gamma^{2}(2^{h-2})} \\, + \\left|\\sin(\\theta) \\, \\cos(\\theta)\\right|^{2^{h-1} - 1} \\, , where :math:`\\Gamma(\\cdot)` is the `Gamma function `_. From 1c538eda6624c6732c4321e9c786650197646fe1 Mon Sep 17 00:00:00 2001 From: Rahul Arvind Date: Tue, 6 Feb 2024 16:56:37 +0800 Subject: [PATCH 136/200] Test old test_qcnn --- tests/test_models_qcnn.py | 261 +++++++++++++------------------------- 1 file changed, 89 insertions(+), 172 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 34f92da826..7db8b56d78 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -3,7 +3,8 @@ import numpy as np import pytest -from qibo import gates, get_backend +import qibo +from qibo import gates from qibo.models import Circuit from qibo.models.qcnn import QuantumCNN @@ -11,7 +12,7 @@ angles0 = [i * math.pi / num_angles for i in range(num_angles)] -def test_classifier_circuit2(backend): +def test_classifier_circuit2(): """ """ nqubits = 2 nlayers = int(nqubits / 2) @@ -28,14 +29,14 @@ def test_classifier_circuit2(backend): # circuit = qcnn._circuit statevector = circuit(init_state).state() - real_vector = get_real_vector2(backend) + real_vector = get_real_vector2() # to compare statevector and real_vector np.testing.assert_allclose(statevector.real, real_vector.real, atol=1e-5) np.testing.assert_allclose(statevector.imag, real_vector.imag, atol=1e-5) -def get_real_vector2(backend): +def get_real_vector2(): nqubits = 2 bits = range(nqubits) init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # @@ -44,40 +45,29 @@ def get_real_vector2(backend): # convolution k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), - init_state, + one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), init_state ) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[0], bits[1], angles[k], backend).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[0], bits[1], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) k += 3 # pooling ksink = k - a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) k += 3 + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[0], bits[1]).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a - ) - a = np.dot(CNOT_unitary(nqubits, bits[0], bits[1], backend).unitary(), a) - a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[ksink : ksink + 3], backend) + one_qubit_unitary(nqubits, bits[1], angles[ksink : ksink + 3]) .invert() .unitary(), a, @@ -86,7 +76,7 @@ def get_real_vector2(backend): return a -def test_classifier_circuit4(backend): +def test_classifier_circuit4(): """ """ nqubits = 4 nlayers = int(nqubits / 2) @@ -97,14 +87,14 @@ def test_classifier_circuit4(backend): circuit = qcnn.Classifier_circuit(angles) statevector = circuit(init_state).state() - real_vector = get_real_vector4(backend) + real_vector = get_real_vector4() # to compare statevector and real_vector np.testing.assert_allclose(statevector.real, real_vector.real, atol=1e-5) np.testing.assert_allclose(statevector.imag, real_vector.imag, atol=1e-5) -def get_real_vector4(backend): +def get_real_vector4(): nqubits = 4 init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits) # angles = angles0 @@ -116,140 +106,81 @@ def get_real_vector4(backend): b1 = 1 k = 0 a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), - init_state, + one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), init_state ) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) b0 = 2 b1 = 3 k = 0 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) b0 = 1 b1 = 2 k = 0 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) b0 = 3 b1 = 0 k = 0 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RZZ_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RYY_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RYY_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - RXX_unitary(nqubits, bits[b0], bits[b1], angles[k], backend).unitary(), a - ) + a = np.dot(RXX_unitary(nqubits, bits[b0], bits[b1], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b0], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[b1], angles[k : k + 3]).unitary(), a) # pooling - layer 1 k = 15 # k+=3 ksink = k - a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) k += 3 + a = np.dot(one_qubit_unitary(nqubits, bits[0], angles[k : k + 3]).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[0], bits[2]).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[0], angles[k : k + 3], backend).unitary(), a - ) - a = np.dot(CNOT_unitary(nqubits, bits[0], bits[2], backend).unitary(), a) - a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[ksink : ksink + 3], backend) + one_qubit_unitary(nqubits, bits[2], angles[ksink : ksink + 3]) .invert() .unitary(), a, @@ -257,16 +188,12 @@ def get_real_vector4(backend): k = 15 # k+=3 ksink = k - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) k += 3 + a = np.dot(one_qubit_unitary(nqubits, bits[1], angles[k : k + 3]).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[1], bits[3]).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[1], angles[k : k + 3], backend).unitary(), a - ) - a = np.dot(CNOT_unitary(nqubits, bits[1], bits[3], backend).unitary(), a) - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) + one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3]) .invert() .unitary(), a, @@ -274,41 +201,29 @@ def get_real_vector4(backend): # convolution - layer 2 k = 0 - a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot(RZZ_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) + a = np.dot(RZZ_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) k += 1 - a = np.dot(RYY_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) + a = np.dot(RYY_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) k += 1 - a = np.dot(RXX_unitary(nqubits, bits[2], bits[3], angles[k], backend).unitary(), a) + a = np.dot(RXX_unitary(nqubits, bits[2], bits[3], angles[k]).unitary(), a) k += 1 - a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) k += 3 - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) k += 3 # pooling - layer 2 ksink = k - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[k : k + 3], backend).unitary(), a - ) + a = np.dot(one_qubit_unitary(nqubits, bits[3], angles[k : k + 3]).unitary(), a) k += 3 + a = np.dot(one_qubit_unitary(nqubits, bits[2], angles[k : k + 3]).unitary(), a) + a = np.dot(CNOT_unitary(nqubits, bits[2], bits[3]).unitary(), a) a = np.dot( - one_qubit_unitary(nqubits, bits[2], angles[k : k + 3], backend).unitary(), a - ) - a = np.dot(CNOT_unitary(nqubits, bits[2], bits[3], backend).unitary(), a) - a = np.dot( - one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3], backend) + one_qubit_unitary(nqubits, bits[3], angles[ksink : ksink + 3]) .invert() .unitary(), a, @@ -317,7 +232,7 @@ def get_real_vector4(backend): return a -def one_qubit_unitary(nqubits, bit, symbols, backend): +def one_qubit_unitary(nqubits, bit, symbols): c = Circuit(nqubits) c.add(gates.RX(bit, symbols[0])) c.add(gates.RY(bit, symbols[1])) @@ -326,51 +241,42 @@ def one_qubit_unitary(nqubits, bit, symbols, backend): return c -def RXX_unitary(nqubits, bit0, bit1, angle, backend): +def RXX_unitary(nqubits, bit0, bit1, angle): c = Circuit(nqubits) c.add(gates.RXX(bit0, bit1, angle)) return c -def RYY_unitary(nqubits, bit0, bit1, angle, backend): +def RYY_unitary(nqubits, bit0, bit1, angle): c = Circuit(nqubits) c.add(gates.RYY(bit0, bit1, angle)) return c -def RZZ_unitary(nqubits, bit0, bit1, angle, backend): +def RZZ_unitary(nqubits, bit0, bit1, angle): c = Circuit(nqubits) c.add(gates.RZZ(bit0, bit1, angle)) return c -def CNOT_unitary(nqubits, bit0, bit1, backend): +def CNOT_unitary(nqubits, bit0, bit1): c = Circuit(nqubits) c.add(gates.CNOT(bit0, bit1)) return c -def test_1_qubit_classifier_circuit_error(backend): +def test_1_qubit_classifier_circuit_error(): try: QuantumCNN(nqubits=1, nlayers=1, nclasses=2) except: pass -def test_two_qubit_ansatz(backend): - c = Circuit(2) - c.add(gates.H(0)) - c.add(gates.RX(0, 0)) - c.add(gates.CNOT(1, 0)) - test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) - -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) - -def test_qcnn_training(backend): +def test_qcnn_training(): import random # generate 2 random states and labels for pytest @@ -387,21 +293,32 @@ def test_qcnn_training(backend): test_qcnn = QuantumCNN(nqubits=4, nlayers=1, nclasses=2, params=init_theta) testcircuit = test_qcnn._circuit result = test_qcnn.minimize( - init_theta, data=data, labels=labels, nshots=1000, method="Powell" + init_theta, data=data, labels=labels, nshots=10000, method="Powell" ) # test Predictions function predictions = [] for n in range(len(data)): - predictions.append(test_qcnn.predict(data[n], nshots=1000)[0]) + predictions.append(test_qcnn.predict(data[n], nshots=10000)[0]) # test Accuracy function predictions.append(1) labels = np.array([[1], [-1], [1]]) + test_qcnn.Accuracy(labels, predictions) + + +def test_two_qubit_ansatz(): + c = Circuit(2) + c.add(gates.H(0)) + c.add(gates.RX(0, 0)) + c.add(gates.CNOT(1, 0)) + test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) + -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +def test_two_qubit_ansatz_training(): + # test qibojit case (copy initial state as quick-fix for in-place update) + qibo.set_backend("qibojit") -def test_two_qubit_ansatz_training(backend): c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) @@ -431,4 +348,4 @@ def test_two_qubit_ansatz_training(backend): # test Accuracy function predictions.append(1) labels = np.array([[1], [-1], [1]]) - test_qcnn.Accuracy(labels, predictions) + test_qcnn.Accuracy(labels, predictions) \ No newline at end of file From cdabfea1e10e1d29605967868beeefaa442d08d5 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 6 Feb 2024 08:58:53 +0000 Subject: [PATCH 137/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tests/test_models_qcnn.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index bc99f09d62..dcce3c3697 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -283,8 +283,8 @@ def test_two_qubit_ansatz(backend): c.add(gates.CNOT(1, 0)) test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) def test_qcnn_training(backend): import random @@ -325,7 +325,6 @@ def test_two_qubit_ansatz(): @pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) - def test_two_qubit_ansatz_training(backend): c = Circuit(2) c.add(gates.H(0)) @@ -356,4 +355,4 @@ def test_two_qubit_ansatz_training(backend): # test Accuracy function predictions.append(1) labels = np.array([[1], [-1], [1]]) - test_qcnn.Accuracy(labels, predictions) \ No newline at end of file + test_qcnn.Accuracy(labels, predictions) From 92a8183084ce2e8879dc500d15c3cb6cbd2bf9f3 Mon Sep 17 00:00:00 2001 From: Rahul Arvind Date: Tue, 6 Feb 2024 17:10:01 +0800 Subject: [PATCH 138/200] even older testing --- tests/test_models_qcnn.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index bc99f09d62..7db8b56d78 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -276,16 +276,7 @@ def test_1_qubit_classifier_circuit_error(): pass -def test_two_qubit_ansatz(backend): - c = Circuit(2) - c.add(gates.H(0)) - c.add(gates.RX(0, 0)) - c.add(gates.CNOT(1, 0)) - test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) - -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) - -def test_qcnn_training(backend): +def test_qcnn_training(): import random # generate 2 random states and labels for pytest @@ -324,9 +315,10 @@ def test_two_qubit_ansatz(): test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=c) -@pytest.mark.parametrize("backend", [("numpy"), ("qibojit")]) +def test_two_qubit_ansatz_training(): + # test qibojit case (copy initial state as quick-fix for in-place update) + qibo.set_backend("qibojit") -def test_two_qubit_ansatz_training(backend): c = Circuit(2) c.add(gates.H(0)) c.add(gates.RX(0, 0)) From bdc9571cfc1bfe1a0c0eb30d6acb5ab69a5515db Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 14:20:15 +0400 Subject: [PATCH 139/200] remove `no cover` and add test --- src/qibo/backends/__init__.py | 2 +- tests/test_global_backend.py | 17 +++++++++++++++++ 2 files changed, 18 insertions(+), 1 deletion(-) diff --git a/src/qibo/backends/__init__.py b/src/qibo/backends/__init__.py index 04f26d870b..db25cf04c1 100644 --- a/src/qibo/backends/__init__.py +++ b/src/qibo/backends/__init__.py @@ -169,7 +169,7 @@ def set_threads(nthreads): GlobalBackend().set_threads(nthreads) -def _check_backend(backend): # pragma: no cover +def _check_backend(backend): if backend is None: return GlobalBackend() diff --git a/tests/test_global_backend.py b/tests/test_global_backend.py index 27386ed812..9ad3a4b2f4 100644 --- a/tests/test_global_backend.py +++ b/tests/test_global_backend.py @@ -91,3 +91,20 @@ def test_gate_matrix(): qibo.set_backend("numpy") gate = qibo.gates.H(0) matrix = gate.matrix + + +def test_check_backend(backend): + # testing when backend is not None + test = qibo.backends._check_backend(backend) + + assert test.name == backend.name + assert test.__class__ == backend.__class__ + + # testing when backend is None + test = None + test = qibo.backends._check_backend(test) + + target = qibo.backends.GlobalBackend() + + assert test.name == target.name + assert test.__class__ == target.__class__ From 65914fae1e35302b8e2a33e4a5d0b29c6bf05842 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 11:50:32 +0000 Subject: [PATCH 140/200] Update src/qibo/quantum_info/quantum_networks.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/quantum_networks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 7dd0a7735b..7e2068a77d 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -442,7 +442,7 @@ def __mul__(self, number: Union[float, int]): If the quantum network is pure and ``number > 0.0``, the method returns a pure quantum network with its Choi operator multiplied by the square root of ``number``. - This is equivelant to multiplying `self.to_full()` by the ``number``. + This is equivalent to multiplying `self.to_full()` by the ``number``. Otherwise, this method will return a full quantum network. Args: From 3abdec788d88604ca7dcb5be1e5bb50c6bb3639f Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 11:50:38 +0000 Subject: [PATCH 141/200] Update src/qibo/quantum_info/quantum_networks.py Co-authored-by: Alejandro Sopena <44305203+AlejandroSopena@users.noreply.github.com> --- src/qibo/quantum_info/quantum_networks.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 7e2068a77d..91ba7bce2a 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -486,7 +486,7 @@ def __truediv__(self, number: Union[float, int]): If the quantum network is pure and ``number > 0.0``, the method returns a pure quantum network with its Choi operator divided by the square root of ``number``. - This is equivelant to dividing `self.to_full()` by the ``number``. + This is equivalent to dividing `self.to_full()` by the ``number``. Otherwise, this method will return a full quantum network. Args: From 9c197dd130f958c8079b1ca63ce81f81c197afe0 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 6 Feb 2024 17:59:44 +0400 Subject: [PATCH 142/200] fic docstring --- src/qibo/gates/gates.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/qibo/gates/gates.py b/src/qibo/gates/gates.py index 128518a89e..c0879b10d2 100644 --- a/src/qibo/gates/gates.py +++ b/src/qibo/gates/gates.py @@ -1508,7 +1508,7 @@ def qasm_label(self): class SiSWAP(Gate): - """The :math:`\\sqrt{\\text{iSWAP}}}` gate. + """The :math:`\\sqrt{\\text{iSWAP}}` gate. Corresponds to the following unitary matrix @@ -1538,7 +1538,7 @@ def _dagger(self) -> "Gate": class SiSWAPDG(Gate): - """The :math:`\\sqrt{\\text{iSWAP}}}^{\\dagger}` gate. + """The :math:`\\left(\\sqrt{\\text{iSWAP}}\\right)^{\\dagger}` gate. Corresponds to the following unitary matrix From d9a3baa953263d7008a932851f6006b9fa17ad55 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 6 Feb 2024 23:58:26 +0800 Subject: [PATCH 143/200] Update src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 640904e6ee..1f64e967ef 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -60,12 +60,7 @@ def __init__( self.twoqubitansatz = twoqubitansatz if copy_init_state is None: - if ( - ("qibojit" in get_backend()) - or ("qibojit-numba" in get_backend()) - or ("qibojit-cuquantum" in get_backend()) - or ("qibojit-cupy" in get_backend()) - ): + if "qibojit" in get_backend(): self.copy_init_state = True else: self.copy_init_state = False From 60964247f6b61ea382802e32e12bcd3bc8bb5cd7 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 6 Feb 2024 23:58:37 +0800 Subject: [PATCH 144/200] Update src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 1f64e967ef..8e8fe5227a 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -183,7 +183,7 @@ def two_qubit_unitary(self, bits, symbols): Circuit containing the unitaries added to the specified qubits. """ - if self.twoqubitansatz == None: + if self.twoqubitansatz is None: c = Circuit(self.nqubits) c += self.one_qubit_unitary(bits[0], symbols[0:3]) c += self.one_qubit_unitary(bits[1], symbols[3:6]) From 643752c13a0b81cba41d170087c5355690275880 Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 6 Feb 2024 23:58:45 +0800 Subject: [PATCH 145/200] Update src/qibo/models/qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- src/qibo/models/qcnn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/models/qcnn.py b/src/qibo/models/qcnn.py index 8e8fe5227a..f56ed804cf 100644 --- a/src/qibo/models/qcnn.py +++ b/src/qibo/models/qcnn.py @@ -279,7 +279,7 @@ def Predictions(self, circuit, theta, init_state, nshots=10000): numpy.array() with predictions for each qubit, for the initial state. """ bias = np.array(theta[0 : self.measured_qubits]) - if self.copy_init_state is True: + if self.copy_init_state: init_state_copy = init_state.copy() else: init_state_copy = init_state From 894f6d9c0eef7e4ae474285564780ff39b5b3e8e Mon Sep 17 00:00:00 2001 From: rahul Date: Tue, 6 Feb 2024 23:58:51 +0800 Subject: [PATCH 146/200] Update tests/test_models_qcnn.py Co-authored-by: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> --- tests/test_models_qcnn.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/test_models_qcnn.py b/tests/test_models_qcnn.py index 7e9168b007..ab8d98e2b3 100644 --- a/tests/test_models_qcnn.py +++ b/tests/test_models_qcnn.py @@ -1,7 +1,6 @@ import math import numpy as np -import pytest import qibo from qibo import gates From 8b6ca7794ba6efeaa18ba27d7086ad004c0a7275 Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 00:06:25 +0800 Subject: [PATCH 147/200] correct the behavior of applying a quantum comb to a quantum channel --- src/qibo/quantum_info/quantum_networks.py | 50 +++++++++++++++------ tests/test_quantum_info_quantum_networks.py | 28 ++++++------ 2 files changed, 50 insertions(+), 28 deletions(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index 91ba7bce2a..a688800258 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -337,8 +337,8 @@ def link_product(self, second_network, subscripts: str = "ij,jk -> ik"): inv_subscripts = pattern_two and subscripts[0] == subscripts[4] super_subscripts = ( pattern_four - and subscripts[2] == subscripts[5] - and subscripts[3] == subscripts[6] + and subscripts[1] == subscripts[5] + and subscripts[2] == subscripts[6] ) if not channel_subscripts and not inv_subscripts and not super_subscripts: @@ -351,10 +351,10 @@ def link_product(self, second_network, subscripts: str = "ij,jk -> ik"): second_matrix = second_network._full() # pylint: disable=W0212 if super_subscripts: - cexpr = "jklmnopq,nopqrstu->jklmrstu" + cexpr = "jklmnopq,klop->jmnq" return QuantumNetwork( np.einsum(cexpr, first_matrix, second_matrix), - self.partition[:2] + second_network.partition[2:], + [self.partition[0] + self.partition[-1]], ) cexpr = "jkab,klbc->jlac" @@ -532,17 +532,39 @@ def __matmul__(self, second_network): + "``QuantumNetwork`` by a non-``QuantumNetwork``.", ) - if self.partition != second_network.partition: - raise_error( - ValueError, - "partitions of the networks do not match: " - + f"{self.partition} != {second_network.partition}.", - ) + if len(self.partition) == 2: # `self` is a channel + if len(second_network.partition) != 2: + raise_error( + ValueError, + f"`QuantumNetwork {second_network} is assumed to be a channel, but it is not. " + + "Use `link_product` method to specify the subscript.", + ) + if self.partition[1] != second_network.partition[0]: + raise_error( + ValueError, + "partitions of the networks do not match: " + + f"{self.partition[1]} != {second_network.partition[0]}.", + ) - if len(self.partition) == 2: subscripts = "jk,kl -> jl" - elif len(self.partition) == 4: - subscripts = "jklm,lmno -> jkno" + + + elif len(self.partition) == 4: # `self` is a super-channel + if len(second_network.partition) != 2: + raise_error( + ValueError, + f"`QuantumNetwork {second_network} is assumed to be a channel, but it is not. " + + "Use `link_product` method to specify the subscript.", + ) + if self.partition[1] != second_network.partition[0]: + raise_error( + ValueError, + "Systems of the channel do not match the super-channel: " + + f"{self.partition[1], self.partition[2]} != " + + f"{second_network.partition[0],second_network.partition[1]}.", + ) + + subscripts = "jklm,kl -> jm" else: raise_error( NotImplementedError, @@ -652,7 +674,7 @@ def _check_subscript_pattern(self, subscripts: str): """Checks if input subscript match any implemented pattern.""" braket = "[a-z]" pattern_two = re.compile(braket * 2 + "," + braket * 2 + "->" + braket * 2) - pattern_four = re.compile(braket * 4 + "," + braket * 4 + "->" + braket * 4) + pattern_four = re.compile(braket * 4 + "," + braket * 2 + "->" + braket * 2) return bool(re.match(pattern_two, subscripts)), bool( re.match(pattern_four, subscripts) diff --git a/tests/test_quantum_info_quantum_networks.py b/tests/test_quantum_info_quantum_networks.py index e02537eae1..b9d3b214ed 100644 --- a/tests/test_quantum_info_quantum_networks.py +++ b/tests/test_quantum_info_quantum_networks.py @@ -223,25 +223,25 @@ def test_with_unitaries(backend, subscript): def test_with_comb(backend): - subscript = "jklm,lmno->jkno" - partition = (2,) * 4 - sys_out = (False, True) * 2 + subscript = "jklm,kl->jm" + comb_partition = (2,) * 4 + channel_partition = (2,) * 2 + comb_sys_out = (False, True) * 2 + channel_sys_out = (False, True) * 2 comb = random_density_matrix(2**4, backend=backend) - comb_2 = random_density_matrix(2**4, backend=backend) + channel = random_density_matrix(2**2, backend=backend) - comb_choi = QuantumNetwork(comb, partition, system_output=sys_out, backend=backend) - comb_choi_2 = QuantumNetwork( - comb_2, partition, system_output=sys_out, backend=backend - ) - comb_choi_3 = QuantumNetwork( - comb @ comb_2, partition, system_output=sys_out, backend=backend - ).to_full(backend) + comb_choi = QuantumNetwork(comb, comb_partition, system_output=comb_sys_out, backend=backend) + channel_choi = QuantumNetwork(channel, channel_partition, system_output=channel_sys_out, backend=backend) + # channel_choi_2 = QuantumNetwork( + # comb @ channel, comb_partition, system_output=comb_sys_out, backend=backend + # ).to_full(backend) - test = comb_choi.link_product(comb_choi_2, subscript).to_full(backend) + test = comb_choi.link_product(channel_choi, subscript).to_full(backend) - backend.assert_allclose(test, comb_choi_3, atol=1e-5) - backend.assert_allclose(test, (comb_choi @ comb_choi_2).to_full(backend), atol=1e-5) + # backend.assert_allclose(test, comb_choi_3, atol=1e-5) + # backend.assert_allclose(test, (comb_choi @ comb_choi_2).to_full(backend), atol=1e-5) def test_apply(backend): From 2869d3ed6a08c335e0410d1b85100f8beb52bef1 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 6 Feb 2024 16:09:52 +0000 Subject: [PATCH 148/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/quantum_info/quantum_networks.py | 5 ++--- tests/test_quantum_info_quantum_networks.py | 8 ++++++-- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/src/qibo/quantum_info/quantum_networks.py b/src/qibo/quantum_info/quantum_networks.py index a688800258..8992169ae5 100644 --- a/src/qibo/quantum_info/quantum_networks.py +++ b/src/qibo/quantum_info/quantum_networks.py @@ -532,7 +532,7 @@ def __matmul__(self, second_network): + "``QuantumNetwork`` by a non-``QuantumNetwork``.", ) - if len(self.partition) == 2: # `self` is a channel + if len(self.partition) == 2: # `self` is a channel if len(second_network.partition) != 2: raise_error( ValueError, @@ -548,8 +548,7 @@ def __matmul__(self, second_network): subscripts = "jk,kl -> jl" - - elif len(self.partition) == 4: # `self` is a super-channel + elif len(self.partition) == 4: # `self` is a super-channel if len(second_network.partition) != 2: raise_error( ValueError, diff --git a/tests/test_quantum_info_quantum_networks.py b/tests/test_quantum_info_quantum_networks.py index b9d3b214ed..18f377eabb 100644 --- a/tests/test_quantum_info_quantum_networks.py +++ b/tests/test_quantum_info_quantum_networks.py @@ -232,8 +232,12 @@ def test_with_comb(backend): comb = random_density_matrix(2**4, backend=backend) channel = random_density_matrix(2**2, backend=backend) - comb_choi = QuantumNetwork(comb, comb_partition, system_output=comb_sys_out, backend=backend) - channel_choi = QuantumNetwork(channel, channel_partition, system_output=channel_sys_out, backend=backend) + comb_choi = QuantumNetwork( + comb, comb_partition, system_output=comb_sys_out, backend=backend + ) + channel_choi = QuantumNetwork( + channel, channel_partition, system_output=channel_sys_out, backend=backend + ) # channel_choi_2 = QuantumNetwork( # comb @ channel, comb_partition, system_output=comb_sys_out, backend=backend # ).to_full(backend) From e6c9809b9662009f2af2fc7ddf0c10ecbae32102 Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 14:25:05 +0800 Subject: [PATCH 149/200] update test for combs --- tests/test_quantum_info_quantum_networks.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/tests/test_quantum_info_quantum_networks.py b/tests/test_quantum_info_quantum_networks.py index 18f377eabb..9345ee3ede 100644 --- a/tests/test_quantum_info_quantum_networks.py +++ b/tests/test_quantum_info_quantum_networks.py @@ -88,7 +88,7 @@ def test_errors(backend): with pytest.raises(NotImplementedError): net @ net - with pytest.raises(ValueError): + with pytest.raises(NotImplementedError): net @ network with pytest.raises(ValueError): @@ -227,7 +227,7 @@ def test_with_comb(backend): comb_partition = (2,) * 4 channel_partition = (2,) * 2 comb_sys_out = (False, True) * 2 - channel_sys_out = (False, True) * 2 + channel_sys_out = (False, True) comb = random_density_matrix(2**4, backend=backend) channel = random_density_matrix(2**2, backend=backend) @@ -238,14 +238,11 @@ def test_with_comb(backend): channel_choi = QuantumNetwork( channel, channel_partition, system_output=channel_sys_out, backend=backend ) - # channel_choi_2 = QuantumNetwork( - # comb @ channel, comb_partition, system_output=comb_sys_out, backend=backend - # ).to_full(backend) test = comb_choi.link_product(channel_choi, subscript).to_full(backend) + channel_choi2 = comb_choi @ channel_choi - # backend.assert_allclose(test, comb_choi_3, atol=1e-5) - # backend.assert_allclose(test, (comb_choi @ comb_choi_2).to_full(backend), atol=1e-5) + backend.assert_allclose(test, channel_choi2.to_full(backend), atol=1e-5) def test_apply(backend): From 7df827562d9d9a5f69cb4e3123faa28a493e5fb3 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 7 Feb 2024 10:32:39 +0400 Subject: [PATCH 150/200] use backend helper function --- src/qibo/quantum_info/entanglement.py | 21 ++++++---------- src/qibo/quantum_info/entropies.py | 35 +++++++++------------------ 2 files changed, 20 insertions(+), 36 deletions(-) diff --git a/src/qibo/quantum_info/entanglement.py b/src/qibo/quantum_info/entanglement.py index 7f009e367a..28cbb70305 100644 --- a/src/qibo/quantum_info/entanglement.py +++ b/src/qibo/quantum_info/entanglement.py @@ -2,7 +2,7 @@ import numpy as np -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error from qibo.quantum_info.metrics import fidelity, purity @@ -29,8 +29,7 @@ def concurrence(state, bipartition, check_purity: bool = True, backend=None): Returns: float: Concurrence of :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) not in [1, 2]) @@ -107,11 +106,10 @@ def entanglement_of_formation( Returns: float: entanglement of formation of state :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - from qibo.quantum_info.entropies import shannon_entropy # pylint: disable=C0415 + backend = _check_backend(backend) + concur = concurrence( state, bipartition=bipartition, check_purity=check_purity, backend=backend ) @@ -155,9 +153,6 @@ def entanglement_fidelity( Returns: float: Entanglement fidelity :math:`F_{\\mathcal{E}}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() - if not isinstance(nqubits, int): raise_error( TypeError, f"nqubits must be type int, but it is type {type(nqubits)}." @@ -184,6 +179,8 @@ def entanglement_fidelity( f"check_hermitian must be type bool, but it is type {type(check_hermitian)}.", ) + backend = _check_backend(backend) + if state is None: state = backend.plus_density_matrix(nqubits) @@ -218,8 +215,7 @@ def meyer_wallach_entanglement(circuit, backend=None): float: Meyer-Wallach entanglement. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) circuit.density_matrix = True nqubits = circuit.nqubits @@ -279,8 +275,7 @@ def entangling_capability(circuit, samples: int, seed=None, backend=None): TypeError, "seed must be either type int or numpy.random.Generator." ) - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) local_state = ( np.random.default_rng(seed) if seed is None or isinstance(seed, int) else seed diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 0108bcddbc..4161273082 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -5,7 +5,7 @@ import numpy as np from scipy.linalg import fractional_matrix_power -from qibo.backends import GlobalBackend +from qibo.backends import _check_backend from qibo.config import PRECISION_TOL, raise_error from qibo.quantum_info.metrics import _check_hermitian_or_not_gpu, purity @@ -30,8 +30,7 @@ def shannon_entropy(prob_dist, base: float = 2, backend=None): Returns: (float): Shannon entropy :math:`H(\\mathcal{p})`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist, list): # np.float64 is necessary instead of native float because of tensorflow @@ -98,8 +97,7 @@ def classical_relative_entropy(prob_dist_p, prob_dist_q, base: float = 2, backen Returns: float: Classical relative entropy between :math:`\\mathbf{p}` and :math:`\\mathbf{q}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist_p, list): # np.float64 is necessary instead of native float because of tensorflow @@ -190,8 +188,7 @@ def classical_renyi_entropy( Returns: float: Classical Rényi entropy :math:`H_{\\alpha}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist, list): # np.float64 is necessary instead of native float because of tensorflow @@ -279,8 +276,7 @@ def classical_relative_renyi_entropy( Returns: float: Classical relative Rényi entropy :math:`H_{\\alpha}(\\mathbf{p} \\, \\| \\, \\mathbf{q})`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist_p, list): # np.float64 is necessary instead of native float because of tensorflow @@ -361,8 +357,7 @@ def classical_tsallis_entropy(prob_dist, alpha: float, base: float = 2, backend= Returns: float: Classical Tsallis entropy :math:`S_{\\alpha}(\\mathbf{p})`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if isinstance(prob_dist, list): # np.float64 is necessary instead of native float because of tensorflow @@ -433,8 +428,7 @@ def von_neumann_entropy( Returns: float: The von-Neumann entropy :math:`S` of ``state`` :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -513,8 +507,7 @@ def relative_von_neumann_entropy( Returns: float: Relative (von-Neumann) entropy :math:`S(\\rho \\, \\| \\, \\sigma)`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -629,8 +622,7 @@ def renyi_entropy(state, alpha: Union[float, int], base: float = 2, backend=None Returns: float: Rényi entropy :math:`H_{\\alpha}`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -714,8 +706,7 @@ def relative_renyi_entropy( Returns: float: Relative Rényi entropy :math:`H_{\\alpha}(\\rho \\, \\| \\, \\sigma)`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -806,8 +797,7 @@ def tsallis_entropy(state, alpha: float, base: float = 2, backend=None): Returns: float: Tsallis entropy :math:`S_{\\alpha}(\\rho)`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if ( (len(state.shape) >= 3) @@ -871,8 +861,7 @@ def entanglement_entropy( Returns: float: Entanglement entropy :math:`S` of ``state`` :math:`\\rho`. """ - if backend is None: # pragma: no cover - backend = GlobalBackend() + backend = _check_backend(backend) if base <= 0.0: raise_error(ValueError, "log base must be non-negative.") From 2b63c804d03e6b08a84ad45c446beb351c659545 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 7 Feb 2024 10:39:23 +0400 Subject: [PATCH 151/200] reduce complexity --- src/qibo/quantum_info/entropies.py | 59 ++++++------------------------ 1 file changed, 11 insertions(+), 48 deletions(-) diff --git a/src/qibo/quantum_info/entropies.py b/src/qibo/quantum_info/entropies.py index 4161273082..716bdda3fd 100644 --- a/src/qibo/quantum_info/entropies.py +++ b/src/qibo/quantum_info/entropies.py @@ -57,14 +57,7 @@ def shannon_entropy(prob_dist, base: float = 2, backend=None): if np.abs(np.sum(prob_dist) - 1.0) > PRECISION_TOL: raise_error(ValueError, "Probability array must sum to 1.") - if base == 2: - log_prob = np.where(prob_dist != 0.0, np.log2(prob_dist), 0.0) - elif base == 10: - log_prob = np.where(prob_dist != 0, np.log10(prob_dist), 0.0) - elif base == np.e: - log_prob = np.where(prob_dist != 0, np.log(prob_dist), 0.0) - else: - log_prob = np.where(prob_dist != 0, np.log(prob_dist) / np.log(base), 0.0) + log_prob = np.where(prob_dist != 0, np.log2(prob_dist) / np.log2(base), 0.0) shan_entropy = -np.sum(prob_dist * log_prob) @@ -134,16 +127,9 @@ def classical_relative_entropy(prob_dist_p, prob_dist_q, base: float = 2, backen entropy_p = -1 * shannon_entropy(prob_dist_p, base=base, backend=backend) - if base == 2: - log_prob_q = np.where(prob_dist_q != 0.0, np.log2(prob_dist_q), -np.inf) - elif base == 10: - log_prob_q = np.where(prob_dist_q != 0.0, np.log10(prob_dist_q), -np.inf) - elif base == np.e: - log_prob_q = np.where(prob_dist_q != 0.0, np.log(prob_dist_q), -np.inf) - else: - log_prob_q = np.where( - prob_dist_q != 0.0, np.log(prob_dist_q) / np.log(base), -np.inf - ) + log_prob_q = np.where( + prob_dist_q != 0.0, np.log2(prob_dist_q) / np.log2(base), -np.inf + ) log_prob = np.where(prob_dist_p != 0.0, log_prob_q, 0.0) @@ -460,14 +446,7 @@ def von_neumann_entropy( else: eigenvalues = np.linalg.eigvals(state) - if base == 2: - log_prob = np.where(eigenvalues > 0, np.log2(eigenvalues), 0.0) - elif base == 10: - log_prob = np.where(eigenvalues > 0, np.log10(eigenvalues), 0.0) - elif base == np.e: - log_prob = np.where(eigenvalues > 0, np.log(eigenvalues), 0.0) - else: - log_prob = np.where(eigenvalues > 0, np.log(eigenvalues) / np.log(base), 0.0) + log_prob = np.where(eigenvalues > 0, np.log2(eigenvalues) / np.log2(base), 0.0) ent = -np.sum(eigenvalues * log_prob) # absolute value if entropy == 0.0 to avoid returning -0.0 @@ -557,28 +536,12 @@ def relative_von_neumann_entropy( else: eigenvalues_target = np.linalg.eigvals(target) - if base == 2: - log_state = np.where(eigenvalues_state > 0, np.log2(eigenvalues_state), 0.0) - log_target = np.where( - eigenvalues_target > 0, np.log2(eigenvalues_target), -np.inf - ) - elif base == 10: - log_state = np.where(eigenvalues_state > 0, np.log10(eigenvalues_state), 0.0) - log_target = np.where( - eigenvalues_target > 0, np.log10(eigenvalues_target), -np.inf - ) - elif base == np.e: - log_state = np.where(eigenvalues_state > 0, np.log(eigenvalues_state), 0.0) - log_target = np.where( - eigenvalues_target > 0, np.log(eigenvalues_target), -np.inf - ) - else: - log_state = np.where( - eigenvalues_state > 0, np.log(eigenvalues_state) / np.log(base), 0.0 - ) - log_target = np.where( - eigenvalues_target > 0, np.log(eigenvalues_target) / np.log(base), -np.inf - ) + log_state = np.where( + eigenvalues_state > 0, np.log2(eigenvalues_state) / np.log2(base), 0.0 + ) + log_target = np.where( + eigenvalues_target > 0, np.log2(eigenvalues_target) / np.log2(base), -np.inf + ) log_target = np.where(eigenvalues_state != 0.0, log_target, 0.0) From a876281e39a27b316af9ca98caa2d4b98bbc2db5 Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 15:32:52 +0800 Subject: [PATCH 152/200] add a tutorial for `QuantumNetwork` --- .../tutorials/quantum_networks/README.md | 126 ++++++++++++++++++ 1 file changed, 126 insertions(+) create mode 100644 doc/source/code-examples/tutorials/quantum_networks/README.md diff --git a/doc/source/code-examples/tutorials/quantum_networks/README.md b/doc/source/code-examples/tutorials/quantum_networks/README.md new file mode 100644 index 0000000000..8b9f1197c4 --- /dev/null +++ b/doc/source/code-examples/tutorials/quantum_networks/README.md @@ -0,0 +1,126 @@ +# Quantum Networks + +## The Quantum Network Model + +The quantum network model is a mathematical framework that allows us to uniquely describe quantum information processing that involves multiple points in time and space. +Each distinguished point in time and space is treated as a linear system $\mathcal{H}_i$. +A quantum network involving $n$ points in time and space is a Hermitian operator $\mathcal{N}$ that acts on the tensor product of the linear systems $\mathcal{H}_0 \otimes \mathcal{H}_1 \otimes \cdots \otimes \mathcal{H}_{n-1}$. +Each system $\mathcal{H}_i$ is either an input or an output of the network. + +A physically implementable quantum network is described by a semi-positive definite operator $\mathcal{N}$ that satisfies the causal constraints. + +A simple example is a quantum channel $\Gamma: \mathcal{H}_0 \to \mathcal{H}_1$, where $\mathcal{H}_0$ is the input system and $\mathcal{H}_1$ is the output system. +The quantum channel is a linear map, such that it maps any input quantum state to an output quantum state, which is a sufficient and necessary condition for the map to be physical. +A Hermitian operator $J^\Gamma$ acting on $\mathcal{H}_0\otimes \mathcal{H}_1$ is associated with a quantum channel $\Gamma$, if $J^\Gamma$ satisfies the following conditions: +$$ +J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_{\mathcal{H}_1} J^\Gamma = \mathbb{I}_{\mathcal{H}_0}. +$$ +The first condition is called *complete positivity*, and the second condition is called *trace-preserving*. +In particular, the second condition ensures that the information of the input system is only accessible through the output system. + +In particular, a quantum state $\rho$ may be also considered as a quantum network, where the input system is the trivial system $\mathbb{C}$, and the output system is the quantum system $\mathcal{H}$. +The constraints on the quantum channels are then equivalent to the constraints on the quantum states: +$$ +\rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_\mathbb{C} = 1. +$$ + +> For more details, see G. Chiribella *et al.*, *Theoretical framework for quantum networks*, +> [Physical Review A 80.2 (2009): 022339](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.80.022339). + +## Quantum Network in `qibo` + +The manipulation of quantum networks in `qibo` is done through the `QuantumNetwork` class. + +```python +from qibo.quantum_info.quantum_networks import QuantumNetwork +``` + +A quantum state is a quantum network with a single input system and a single output system, where the input system is the trivial 1-dimensional system. +We need to specify the dimensions of each system in the `partition` argument. + +```python +from qibo.quantum_info import random_density_matrix, random_unitary + +state = random_density_matrix(2) +state_choi = QuantumNetwork(state, (1,2)) +print(f'A quantum state is a quantum netowrk of the form {state_choi}') +``` + +``` +>>> A quantum state is a quantum netowrk of the form J[1 -> 2] +``` + +A general quantum channel can be created in a similar way. + +```python +from qibo.gates import DepolarizingChannel + +test_ch = DepolarizingChannel(0,0.5) +N = len(test_ch.target_qubits) +partition = (2**N, 2**N) + +depolar_choi = QuantumNetwork(test_ch.to_choi(), partition) +print(f'A quantum channel is a quantum netowrk of the form {depolar_choi}') +``` + +``` +>>> A quantum channel is a quantum netowrk of the form J[2 -> 2] +``` + +One may apply a quantum channel to a quantum state, or compose two quantum channels, using the `@` operator. + +```python +new_state = depolar_choi @ depolar_choi @ state_choi +``` + +## Example + +For 3-dimensional systems, an unital channel may not be a mixed unitary channel. + +> Example 4.3 in (Watrous, John. The theory of quantum information. Cambridge university press, 2018.) + +```python +A1 = np.array([ + [0,0,0], + [0,0,1/np.sqrt(2)], + [0,-1/np.sqrt(2),0], +]) +A2 = np.array([ + [0,0,1/np.sqrt(2)], + [0,0,0], + [-1/np.sqrt(2),0,0], +]) +A3 = np.array([ + [0,1/np.sqrt(2),0], + [-1/np.sqrt(2),0,0], + [0,0,0], +]) + +Choi1 = QuantumNetwork(A1, (3,3), pure=True) * 3 +Choi2 = QuantumNetwork(A2, (3,3), pure=True)*3 +Choi3 = QuantumNetwork(A3, (3,3), pure=True)*3 +``` + +The three channels are pure but not unital. Which means they are not unitary. + +```python +print(f"Choi1 is unital: {Choi1.unital()}") +print(f"Choi2 is unital: {Choi2.unital()}") +print(f"Choi3 is unital: {Choi3.unital()}") +``` + +``` +>>> Choi1 is unital: False +Choi2 is unital: False +Choi3 is unital: False +``` + +However, the mixture of the three operators are unital. +As the matrices are orthogonal, they are the extreme points of the convex set of the unital channels. +Therefore, this mixed channel is not a mixed unitary channel. + +```python +Choi = Choi1/3 + Choi2/3 + Choi3/3 +print(f"The mixed channel is unital: {Choi.unital()}") +``` + From ee58ad83b1c8b787c1eb842a4ab0d988ee7e3693 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 7 Feb 2024 07:35:09 +0000 Subject: [PATCH 153/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- doc/source/code-examples/tutorials/quantum_networks/README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/doc/source/code-examples/tutorials/quantum_networks/README.md b/doc/source/code-examples/tutorials/quantum_networks/README.md index 8b9f1197c4..75ca3254f4 100644 --- a/doc/source/code-examples/tutorials/quantum_networks/README.md +++ b/doc/source/code-examples/tutorials/quantum_networks/README.md @@ -123,4 +123,3 @@ Therefore, this mixed channel is not a mixed unitary channel. Choi = Choi1/3 + Choi2/3 + Choi3/3 print(f"The mixed channel is unital: {Choi.unital()}") ``` - From 21c1e1211511307366ca3c179182e3275dcfc3d1 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 7 Feb 2024 12:13:09 +0400 Subject: [PATCH 154/200] cut image sizes by a third --- doc/source/api-reference/qibo.rst | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/doc/source/api-reference/qibo.rst b/doc/source/api-reference/qibo.rst index c28aee53cf..40d3cc91d8 100644 --- a/doc/source/api-reference/qibo.rst +++ b/doc/source/api-reference/qibo.rst @@ -307,8 +307,8 @@ For instance, the following two circuit generations are equivalent: .. image:: ../_static/phase_encoder.png - :width: 2000px - :height: 2329px + :width: 1333px + :height: 1552px :scale: 30 % :align: center @@ -346,8 +346,8 @@ For example, to encode a :math:`8`-dimensional data, one could use the so-called *tree* architechture below: .. image:: ../_static/unary_encoder_tree.png - :width: 2000px - :height: 2329px + :width: 1333px + :height: 1552px :scale: 30 % :align: center @@ -361,8 +361,8 @@ On the other hand, the same encoding could be performed using the so-called *diagonal* (also known as *ladder*) architecture below: .. image:: ../_static/unary_encoder_ladder.png - :width: 2800px - :height: 2329px + :width: 1867px + :height: 1552px :scale: 30 % :align: center From c1cfe94ffc2bd7535905d84c9e050fa562510375 Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 19:16:18 +0800 Subject: [PATCH 155/200] fix math rendering in docs --- .../tutorials/quantum_networks/README.md | 27 ++++++++++--------- 1 file changed, 14 insertions(+), 13 deletions(-) diff --git a/doc/source/code-examples/tutorials/quantum_networks/README.md b/doc/source/code-examples/tutorials/quantum_networks/README.md index 75ca3254f4..26cb7e8752 100644 --- a/doc/source/code-examples/tutorials/quantum_networks/README.md +++ b/doc/source/code-examples/tutorials/quantum_networks/README.md @@ -3,26 +3,27 @@ ## The Quantum Network Model The quantum network model is a mathematical framework that allows us to uniquely describe quantum information processing that involves multiple points in time and space. -Each distinguished point in time and space is treated as a linear system $\mathcal{H}_i$. -A quantum network involving $n$ points in time and space is a Hermitian operator $\mathcal{N}$ that acts on the tensor product of the linear systems $\mathcal{H}_0 \otimes \mathcal{H}_1 \otimes \cdots \otimes \mathcal{H}_{n-1}$. -Each system $\mathcal{H}_i$ is either an input or an output of the network. +Each distinguished point in time and space is treated as a linear system \(\mathcal{H}_ i\). +A quantum network involving $n$ points in time and space is a Hermitian operator \(\mathcal{N}\) that acts on the tensor product of the linear systems \(\mathcal{H}_ 0 \otimes \mathcal{H}_ 1 \otimes \cdots \otimes \mathcal{H}_ {n-1}\). +Each system \(\mathcal{H}_ {i}\) is either an input or an output of the network. -A physically implementable quantum network is described by a semi-positive definite operator $\mathcal{N}$ that satisfies the causal constraints. +A physically implementable quantum network is described by a semi-positive definite operator \(\mathcal{N}\) that satisfies the causal constraints. -A simple example is a quantum channel $\Gamma: \mathcal{H}_0 \to \mathcal{H}_1$, where $\mathcal{H}_0$ is the input system and $\mathcal{H}_1$ is the output system. +A simple example is a quantum channel \(\Gamma: \mathcal{H}_ 0 \to \mathcal{H}_ 1\), where \(\mathcal{H}_ 0\) is the input system and \(\mathcal{H}_ 1\) is the output system. The quantum channel is a linear map, such that it maps any input quantum state to an output quantum state, which is a sufficient and necessary condition for the map to be physical. -A Hermitian operator $J^\Gamma$ acting on $\mathcal{H}_0\otimes \mathcal{H}_1$ is associated with a quantum channel $\Gamma$, if $J^\Gamma$ satisfies the following conditions: -$$ -J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_{\mathcal{H}_1} J^\Gamma = \mathbb{I}_{\mathcal{H}_0}. -$$ +A Hermitian operator \(J^\Gamma\) acting on \(\mathcal{H}_ 0\otimes \mathcal{H}_ 1\) is associated with a quantum channel \(\Gamma\), if \(J^\Gamma\) satisfies the following conditions: +\[ +J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_ {\mathcal{H}_ 1} J^\Gamma = \mathbb{I}_ {\mathcal{H} _0} \ . +\] + The first condition is called *complete positivity*, and the second condition is called *trace-preserving*. In particular, the second condition ensures that the information of the input system is only accessible through the output system. -In particular, a quantum state $\rho$ may be also considered as a quantum network, where the input system is the trivial system $\mathbb{C}$, and the output system is the quantum system $\mathcal{H}$. +In particular, a quantum state \(\rho\) may be also considered as a quantum network, where the input system is the trivial system \(\mathbb{C}\), and the output system is the quantum system \(\mathcal{H}\). The constraints on the quantum channels are then equivalent to the constraints on the quantum states: -$$ -\rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_\mathbb{C} = 1. -$$ +\[ +\rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_ \mathbb{C} = 1\ . +\] > For more details, see G. Chiribella *et al.*, *Theoretical framework for quantum networks*, > [Physical Review A 80.2 (2009): 022339](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.80.022339). From 48e4aa9b732aef71c5f8d68eb8e8210fa245552d Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 19:20:05 +0800 Subject: [PATCH 156/200] fix math rendering in docs --- .../tutorials/quantum_networks/README.md | 22 +++++++++---------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/doc/source/code-examples/tutorials/quantum_networks/README.md b/doc/source/code-examples/tutorials/quantum_networks/README.md index 26cb7e8752..349fc10fa0 100644 --- a/doc/source/code-examples/tutorials/quantum_networks/README.md +++ b/doc/source/code-examples/tutorials/quantum_networks/README.md @@ -3,27 +3,27 @@ ## The Quantum Network Model The quantum network model is a mathematical framework that allows us to uniquely describe quantum information processing that involves multiple points in time and space. -Each distinguished point in time and space is treated as a linear system \(\mathcal{H}_ i\). -A quantum network involving $n$ points in time and space is a Hermitian operator \(\mathcal{N}\) that acts on the tensor product of the linear systems \(\mathcal{H}_ 0 \otimes \mathcal{H}_ 1 \otimes \cdots \otimes \mathcal{H}_ {n-1}\). -Each system \(\mathcal{H}_ {i}\) is either an input or an output of the network. +Each distinguished point in time and space is treated as a linear system $\mathcal{H}_ i$. +A quantum network involving $n$ points in time and space is a Hermitian operator $\mathcal{N}$ that acts on the tensor product of the linear systems $\mathcal{H}_ 0 \otimes \mathcal{H}_ 1 \otimes \cdots \otimes \mathcal{H}_ {n-1}$. +Each system $\mathcal{H}_ {i}$ is either an input or an output of the network. -A physically implementable quantum network is described by a semi-positive definite operator \(\mathcal{N}\) that satisfies the causal constraints. +A physically implementable quantum network is described by a semi-positive definite operator $\mathcal{N}$ that satisfies the causal constraints. -A simple example is a quantum channel \(\Gamma: \mathcal{H}_ 0 \to \mathcal{H}_ 1\), where \(\mathcal{H}_ 0\) is the input system and \(\mathcal{H}_ 1\) is the output system. +A simple example is a quantum channel $\Gamma: \mathcal{H}_ 0 \to \mathcal{H}_ 1$, where $\mathcal{H}_ 0$ is the input system and $\mathcal{H}_ 1$ is the output system. The quantum channel is a linear map, such that it maps any input quantum state to an output quantum state, which is a sufficient and necessary condition for the map to be physical. -A Hermitian operator \(J^\Gamma\) acting on \(\mathcal{H}_ 0\otimes \mathcal{H}_ 1\) is associated with a quantum channel \(\Gamma\), if \(J^\Gamma\) satisfies the following conditions: -\[ +A Hermitian operator $J^\Gamma$ acting on $\mathcal{H}_ 0\otimes \mathcal{H}_ 1$ is associated with a quantum channel $\Gamma$, if $J^\Gamma$ satisfies the following conditions: +$$ J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_ {\mathcal{H}_ 1} J^\Gamma = \mathbb{I}_ {\mathcal{H} _0} \ . -\] +$$ The first condition is called *complete positivity*, and the second condition is called *trace-preserving*. In particular, the second condition ensures that the information of the input system is only accessible through the output system. -In particular, a quantum state \(\rho\) may be also considered as a quantum network, where the input system is the trivial system \(\mathbb{C}\), and the output system is the quantum system \(\mathcal{H}\). +In particular, a quantum state $\rho$ may be also considered as a quantum network, where the input system is the trivial system $\mathbb{C}$, and the output system is the quantum system $\mathcal{H}$. The constraints on the quantum channels are then equivalent to the constraints on the quantum states: -\[ +$$ \rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_ \mathbb{C} = 1\ . -\] +$$ > For more details, see G. Chiribella *et al.*, *Theoretical framework for quantum networks*, > [Physical Review A 80.2 (2009): 022339](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.80.022339). From 7d76ecd1dcab28becb3b7905eb882d326e2046da Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 7 Feb 2024 15:26:36 +0400 Subject: [PATCH 157/200] rename qubits based on connectivity and solved minor bugs --- src/qibo/transpiler/blocks.py | 4 ++-- src/qibo/transpiler/router.py | 8 ++++++-- src/qibo/transpiler/unroller.py | 2 +- tests/test_transpiler_pipeline.py | 1 + tests/test_transpiler_router.py | 1 + 5 files changed, 11 insertions(+), 5 deletions(-) diff --git a/src/qibo/transpiler/blocks.py b/src/qibo/transpiler/blocks.py index 199979767e..5b881d9e06 100644 --- a/src/qibo/transpiler/blocks.py +++ b/src/qibo/transpiler/blocks.py @@ -65,8 +65,8 @@ def fuse(self, block, name: Optional[str] = None): (:class:`qibo.transpiler.blocks.Block`): fusion of the two input blocks. """ if not self.qubits == block.qubits: - raise_error( - BlockingError, "In order to fuse two blocks their qubits must coincide." + raise BlockingError( + "In order to fuse two blocks their qubits must coincide." ) return Block(qubits=self.qubits, gates=self.gates + block.gates, name=name) diff --git a/src/qibo/transpiler/router.py b/src/qibo/transpiler/router.py index 8a3bf54180..6023296d8c 100644 --- a/src/qibo/transpiler/router.py +++ b/src/qibo/transpiler/router.py @@ -379,7 +379,9 @@ def __call__(self, circuit: Circuit, initial_layout: dict): else: self._find_new_mapping() - routed_circuit = self.circuit.routed_circuit(circuit_kwargs=circuit.init_kwargs) + circuit_kwargs = circuit.init_kwargs + circuit_kwargs["wire_names"] = list(initial_layout.keys()) + routed_circuit = self.circuit.routed_circuit(circuit_kwargs=circuit_kwargs) if self._final_measurements is not None: routed_circuit = self._append_final_measurements( routed_circuit=routed_circuit @@ -658,7 +660,9 @@ def __call__(self, circuit: Circuit, initial_layout: dict): else: self._find_new_mapping() - routed_circuit = self.circuit.routed_circuit(circuit_kwargs=circuit.init_kwargs) + circuit_kwargs = circuit.init_kwargs + circuit_kwargs["wire_names"] = list(initial_layout.keys()) + routed_circuit = self.circuit.routed_circuit(circuit_kwargs=circuit_kwargs) if self._final_measurements is not None: routed_circuit = self._append_final_measurements( routed_circuit=routed_circuit diff --git a/src/qibo/transpiler/unroller.py b/src/qibo/transpiler/unroller.py index c62ae4e273..6b8f3e9c60 100644 --- a/src/qibo/transpiler/unroller.py +++ b/src/qibo/transpiler/unroller.py @@ -85,7 +85,7 @@ def __call__(self, circuit: Circuit): Returns: (:class:`qibo.models.circuit.Circuit`): equivalent circuit with native gates. """ - translated_circuit = circuit.__class__(circuit.nqubits) + translated_circuit = Circuit(**circuit.init_kwargs) for gate in circuit.queue: translated_circuit.add( translate_gate( diff --git a/tests/test_transpiler_pipeline.py b/tests/test_transpiler_pipeline.py index ce8afee66d..94d2c4b539 100644 --- a/tests/test_transpiler_pipeline.py +++ b/tests/test_transpiler_pipeline.py @@ -237,6 +237,7 @@ def test_custom_passes_restict(gates, placer, routing): final_layout=final_layout, native_gates=NativeGates.default(), ) + assert transpiled_circ.wire_names == ["q1", "q2", "q3"] def test_custom_passes_multiple_placer(): diff --git a/tests/test_transpiler_router.py b/tests/test_transpiler_router.py index 2cf2364fe9..7a7ef17583 100644 --- a/tests/test_transpiler_router.py +++ b/tests/test_transpiler_router.py @@ -348,6 +348,7 @@ def test_restrict_qubits(router_algorithm): ) assert_connectivity(restricted_connectivity, routed_circ) assert_placement(routed_circ, final_layout, connectivity=restricted_connectivity) + assert routed_circ.wire_names == ["q0", "q2", "q3"] def test_star_error_multi_qubit(): From d5f8ab14a2ede5b39e0117b02550ff8fbc138b3d Mon Sep 17 00:00:00 2001 From: Canoming Date: Wed, 7 Feb 2024 19:32:06 +0800 Subject: [PATCH 158/200] fix math rendering in docs --- .../code-examples/tutorials/quantum_networks/README.md | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/doc/source/code-examples/tutorials/quantum_networks/README.md b/doc/source/code-examples/tutorials/quantum_networks/README.md index 349fc10fa0..e0b074640c 100644 --- a/doc/source/code-examples/tutorials/quantum_networks/README.md +++ b/doc/source/code-examples/tutorials/quantum_networks/README.md @@ -12,18 +12,14 @@ A physically implementable quantum network is described by a semi-positive defin A simple example is a quantum channel $\Gamma: \mathcal{H}_ 0 \to \mathcal{H}_ 1$, where $\mathcal{H}_ 0$ is the input system and $\mathcal{H}_ 1$ is the output system. The quantum channel is a linear map, such that it maps any input quantum state to an output quantum state, which is a sufficient and necessary condition for the map to be physical. A Hermitian operator $J^\Gamma$ acting on $\mathcal{H}_ 0\otimes \mathcal{H}_ 1$ is associated with a quantum channel $\Gamma$, if $J^\Gamma$ satisfies the following conditions: -$$ -J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_ {\mathcal{H}_ 1} J^\Gamma = \mathbb{I}_ {\mathcal{H} _0} \ . -$$ +$$J^\Gamma \geq 0, \quad \text{and} \quad \text{Tr}_ {\mathcal{H}_ 1} J^\Gamma = \mathbb{I}_ {\mathcal{H} _0} .$$ The first condition is called *complete positivity*, and the second condition is called *trace-preserving*. In particular, the second condition ensures that the information of the input system is only accessible through the output system. In particular, a quantum state $\rho$ may be also considered as a quantum network, where the input system is the trivial system $\mathbb{C}$, and the output system is the quantum system $\mathcal{H}$. The constraints on the quantum channels are then equivalent to the constraints on the quantum states: -$$ -\rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_ \mathbb{C} = 1\ . -$$ +$$\rho \geq 0, \quad \text{and} \quad \text{Tr} \rho = \mathbb{I}_ \mathbb{C} = 1\ .$$ > For more details, see G. Chiribella *et al.*, *Theoretical framework for quantum networks*, > [Physical Review A 80.2 (2009): 022339](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.80.022339). @@ -116,7 +112,7 @@ Choi2 is unital: False Choi3 is unital: False ``` -However, the mixture of the three operators are unital. +However, the mixture of the three operators is unital. As the matrices are orthogonal, they are the extreme points of the convex set of the unital channels. Therefore, this mixed channel is not a mixed unitary channel. From 66e82fc809ff0f33138ad7ad695626e133314847 Mon Sep 17 00:00:00 2001 From: Andrea Date: Thu, 8 Feb 2024 08:27:03 +0400 Subject: [PATCH 159/200] doc: New badges --- .github/workflows/publish.yml | 2 +- README.md | 12 +++++++----- 2 files changed, 8 insertions(+), 6 deletions(-) diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 1399089483..c0b9fdf544 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -1,4 +1,4 @@ -name: Deploy docs +name: docs on: workflow_dispatch: diff --git a/README.md b/README.md index bdb1e6f4f8..d53c014e3c 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,8 @@ ![Logo](https://github.com/qiboteam/qibo/blob/master/doc/source/_static/qibo_logo_dark.svg) -![Tests](https://github.com/qiboteam/qibo/workflows/Tests/badge.svg) [![codecov](https://codecov.io/gh/qiboteam/qibo/branch/master/graph/badge.svg?token=1EKZKVEVX0)](https://codecov.io/gh/qiboteam/qibo) -[![DOI](https://zenodo.org/badge/241307936.svg)](https://zenodo.org/badge/latestdoi/241307936) -[![Matrix](https://img.shields.io/matrix/qibo%3Amatrix.org?logo=matrix)](https://matrix.to/#/#qibo:matrix.org) +![PyPI - Version](https://img.shields.io/pypi/v/qibo) +![PyPI - Python Version](https://img.shields.io/pypi/pyversions/qibo) Qibo is an open-source full stack API for quantum simulation and quantum hardware control. @@ -15,6 +14,8 @@ Some of the key features of Qibo are: ## Documentation +[![docs](https://github.com/qiboteam/qibo/actions/workflows/publish.yml/badge.svg)](https://qibo.science/qibo/stable/) + Qibo documentation is available [here](https://qibo.science). ## Minimum Working Examples @@ -49,14 +50,15 @@ result = c(nshots=100) In both cases, the simulation will run in a single device CPU or GPU in double precision `complex128`. ## Citation policy - +[![arXiv](https://img.shields.io/badge/arXiv-2009.01845-b31b1b.svg)](https://arxiv.org/abs/2009.01845) +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3997195.svg)](https://doi.org/10.5281/zenodo.3997195) If you use the package please refer to [the documentation](https://qibo.science/qibo/stable/appendix/citing-qibo.html#publications) for citation instructions. ## Contacts To get in touch with the community and the developers, consider joining the Qibo workspace on Matrix: -https://matrix.to/#/#qibo:matrix.org +[![Matrix](https://img.shields.io/matrix/qibo%3Amatrix.org?logo=matrix)](https://matrix.to/#/#qibo:matrix.org) ## Supporters and collaborators From 9040a3867b23f9777dd65e09a00791ae43c7756e Mon Sep 17 00:00:00 2001 From: Andrea Date: Thu, 8 Feb 2024 08:28:00 +0400 Subject: [PATCH 160/200] doc: Add newline --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index d53c014e3c..2235daa833 100644 --- a/README.md +++ b/README.md @@ -52,6 +52,7 @@ In both cases, the simulation will run in a single device CPU or GPU in double p ## Citation policy [![arXiv](https://img.shields.io/badge/arXiv-2009.01845-b31b1b.svg)](https://arxiv.org/abs/2009.01845) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3997195.svg)](https://doi.org/10.5281/zenodo.3997195) + If you use the package please refer to [the documentation](https://qibo.science/qibo/stable/appendix/citing-qibo.html#publications) for citation instructions. ## Contacts From 8423e90c3878d3a140980863f17d3ffd253f9754 Mon Sep 17 00:00:00 2001 From: Andrea Date: Thu, 8 Feb 2024 09:07:33 +0400 Subject: [PATCH 161/200] fix: Use latest zenodo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2235daa833..59f68ed2d9 100644 --- a/README.md +++ b/README.md @@ -51,7 +51,7 @@ In both cases, the simulation will run in a single device CPU or GPU in double p ## Citation policy [![arXiv](https://img.shields.io/badge/arXiv-2009.01845-b31b1b.svg)](https://arxiv.org/abs/2009.01845) -[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3997195.svg)](https://doi.org/10.5281/zenodo.3997195) +[![DOI](https://zenodo.org/badge/3997195.svg)](https://zenodo.org/badge/latestdoi/3997195) If you use the package please refer to [the documentation](https://qibo.science/qibo/stable/appendix/citing-qibo.html#publications) for citation instructions. From 34640c1922518d07eca9ca86f660f194746b77fe Mon Sep 17 00:00:00 2001 From: Andrea Date: Thu, 8 Feb 2024 12:46:38 +0400 Subject: [PATCH 162/200] fix: Fix DOI --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 59f68ed2d9..46a64fe115 100644 --- a/README.md +++ b/README.md @@ -51,7 +51,7 @@ In both cases, the simulation will run in a single device CPU or GPU in double p ## Citation policy [![arXiv](https://img.shields.io/badge/arXiv-2009.01845-b31b1b.svg)](https://arxiv.org/abs/2009.01845) -[![DOI](https://zenodo.org/badge/3997195.svg)](https://zenodo.org/badge/latestdoi/3997195) +[![DOI](https://zenodo.org/badge/241307936.svg)](https://zenodo.org/badge/latestdoi/241307936) If you use the package please refer to [the documentation](https://qibo.science/qibo/stable/appendix/citing-qibo.html#publications) for citation instructions. From 43f708d8bda5dcbf5a67c9777ee7406103c2cac8 Mon Sep 17 00:00:00 2001 From: MatteoRobbiati Date: Thu, 8 Feb 2024 11:25:33 +0100 Subject: [PATCH 163/200] update backends and ecosystem diagrams --- doc/source/getting-started/backends.svg | 3506 +---------------------- doc/source/qibo_ecosystem.svg | 10 +- 2 files changed, 11 insertions(+), 3505 deletions(-) diff --git a/doc/source/getting-started/backends.svg b/doc/source/getting-started/backends.svg index f41f94df97..10890f53b9 100644 --- a/doc/source/getting-started/backends.svg +++ b/doc/source/getting-started/backends.svg @@ -1,3500 +1,6 @@ - - - - - - image/svg+xml - - - - - - - - +
    Qibo backends
    Simulating on classical hardware
    Clifford
    Qibotn
    Qibojit
    tensorflow
    numpy
    CPU/lightweight
    CPU/GPU high performance
    Specialized
    Executing on quantum hardware
    Qibolab
     diff --git a/doc/source/qibo_ecosystem.svg b/doc/source/qibo_ecosystem.svg index c3ace1030f..5da2b6f483 100644 --- a/doc/source/qibo_ecosystem.svg +++ b/doc/source/qibo_ecosystem.svg @@ -1,13 +1,13 @@ -
    Qibo
    Language API
    Quantum annealing
    Quantum circuits
    Quantum information
    Implementation
    Simulation
    Clifford
    Specialized in Clifford circuits simulation
    Qibotn
    TensorNetwork simulator
    Qibojit
    Efficient device-agnostic simulation with custom operators
    tensorflow
    Simulation of hybrid QML with automatic differentiation
    numpy
    Lightweight, fits +well with any CPU
    Quantum hardware
    Qibocal
    Characterization
    Calibration
    Validation
    Qibolab
    Control drivers
    Convert gates to pulses
    Transpiler
    = backends
    = tools
    RFSoCs
    Application packages
    Qibosoq
    Qibochem
     From 16c8ea90366c4f0da75324463dbf543072900b74 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Fri, 9 Feb 2024 10:14:13 +0400 Subject: [PATCH 164/200] fix --- src/qibo/quantum_info/random_ensembles.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index f8da6a6825..b1be867620 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -579,7 +579,7 @@ def random_clifford( Args: nqubits (int): number of qubits. return_circuit (bool, optional): if ``True``, returns a :class:`qibo.models.Circuit` - object. If ``False``, returns an ``ndarray`` object. Defaults to ``False``. + object. If ``False``, returns an ``ndarray`` object. Defaults to ``True``. density_matrix (bool, optional): used when ``return_circuit=True``. If `True`, the circuit would evolve density matrices. Defaults to ``False``. seed (int or :class:`numpy.random.Generator`, optional): Either a generator of From ed3d652dd9830a95263e0f325f417c81fbb1e23e Mon Sep 17 00:00:00 2001 From: MatteoRobbiati Date: Fri, 9 Feb 2024 09:15:06 +0100 Subject: [PATCH 165/200] fix quantum info box --- doc/source/qibo_ecosystem.svg | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/doc/source/qibo_ecosystem.svg b/doc/source/qibo_ecosystem.svg index 5da2b6f483..032c2a7431 100644 --- a/doc/source/qibo_ecosystem.svg +++ b/doc/source/qibo_ecosystem.svg @@ -1,4 +1,4 @@ -
    Qibo
    Language API
    Quantum annealing
    Quantum circuits
    Quantum information
    Implementation
    Simulation
    Clifford
    Specialized in Clifford circuits simulation
    Qibotn
    TensorNetwork simulator
    Qibojit
    Efficient device-agnostic simulation with custom operators
    tensorflow
    Simulation of hybrid QML with automatic differentiation
    numpy
    Lightweight, fits +well with any CPU
    Quantum hardware
    Qibocal
    Characterization
    Calibration
    Validation
    Qibolab
    Control drivers
    Convert gates to pulses
    Transpiler
    = backends
    = tools
    RFSoCs
    Application packages
    Qibosoq
    Qibochem
     From 457cb71764c2f26b2f19bb6461299c2797e8b8f0 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 10 Feb 2024 11:05:33 +0400 Subject: [PATCH 166/200] tensorflow --- src/qibo/backends/tensorflow.py | 163 +++++++++++--------------------- 1 file changed, 54 insertions(+), 109 deletions(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index cc2a9a9bb0..d29443e57c 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -20,142 +20,87 @@ def __init__(self, dtype): self.tf = tf self.np = tnp + def _get_numpy_gate(self, name, params): + matrix = getattr(NumpyMatrices(self.dtype), name)(*params) + return self.tf.cast(matrix, dtype=self.dtype) + def RX(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - isin = -1j * self.np.sin(theta / 2.0) - return self.tf.cast([[cos, isin], [isin, cos]], dtype=self.dtype) + return self._get_numpy_gate("RX", [theta]) def RY(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - sin = self.np.sin(theta / 2.0) + 0j - return self.tf.cast([[cos, -sin], [sin, cos]], dtype=self.dtype) + return self._get_numpy_gate("RY", [theta]) def RZ(self, theta): - phase = self.np.exp(0.5j * theta) - return self.tf.cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype) + return self._get_numpy_gate("RZ", [theta]) + + def GPI(self, phi): + return self._get_numpy_gate("GPI", [phi]) + + def GPI2(self, phi): + return self._get_numpy_gate("GPI2", [phi]) def U1(self, theta): - phase = self.np.exp(1j * theta) - return self.tf.cast([[1, 0], [0, phase]], dtype=self.dtype) + return self._get_numpy_gate("U1", [theta]) def U2(self, phi, lam): - eplus = self.np.exp(1j * (phi + lam) / 2.0) - eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.tf.cast( - [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]], - dtype=self.dtype, - ) / self.np.sqrt(2) + return self._get_numpy_gate("U2", [phi, lam]) def U3(self, theta, phi, lam): - cost = self.np.cos(theta / 2) - sint = self.np.sin(theta / 2) - eplus = self.np.exp(1j * (phi + lam) / 2.0) - eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.tf.cast( - [ - [self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint], - [eminus * sint, eplus * cost], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("U3", [theta, phi, lam]) + + def U1q(self, theta, phi): + return self._get_numpy_gate("U1q", [theta, phi]) def CRX(self, theta): - r = self.RX(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CRX", [theta]) def CRY(self, theta): - r = self.RY(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CRY", [theta]) def CRZ(self, theta): - r = self.RZ(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CRZ", [theta]) def CU1(self, theta): - r = self.U1(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CU1", [theta]) def CU2(self, phi, lam): - r = self.U2(phi, lam) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CU2", [phi, lam]) def CU3(self, theta, phi, lam): - r = self.U3(theta, phi, lam) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("CU3", [theta, phi, lam]) def fSim(self, theta, phi): - cost = self.np.cos(theta) + 0j - isint = -1j * self.np.sin(theta) - phase = self.np.exp(-1j * phi) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, cost, isint, 0], - [0, isint, cost, 0], - [0, 0, 0, phase], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("fSim", [theta, phi]) def GeneralizedfSim(self, u, phi): - phase = self.np.exp(-1j * phi) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, u[0, 0], u[0, 1], 0], - [0, u[1, 0], u[1, 1], 0], - [0, 0, 0, phase], - ], - dtype=self.dtype, - ) + return self._get_numpy_gate("GeneralizedfSim", [u, phi]) + + def RXX(self, theta): + return self._get_numpy_gate("RXX", [theta]) + + def RYY(self, theta): + return self._get_numpy_gate("RYY", [theta]) + + def RZZ(self, theta): + return self._get_numpy_gate("RZZ", [theta]) + + def RZX(self, theta): + return self._get_numpy_gate("RZX", [theta]) + + def RXXYY(self, theta): + return self._get_numpy_gate("RXXYY", [theta]) + + def MS(self, phi0, phi1, theta): + return self._get_numpy_gate("MS", [phi0, phi1, theta]) + + def GIVENS(self, theta): + return self._get_numpy_gate("GIVENS", [theta]) + + def RBS(self, theta): + return self._get_numpy_gate("RBS", [theta]) + + def DEUTSCH(self, theta): + return self._get_numpy_gate("DEUTSCH", [theta]) def Unitary(self, u): return self.tf.cast(u, dtype=self.dtype) From 15c707d29405e5d5d9acd7c942e5e8dffc2ede89 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sat, 10 Feb 2024 12:34:10 +0400 Subject: [PATCH 167/200] revert changes and add gates properly --- src/qibo/backends/tensorflow.py | 246 ++++++++++++++++++++++++++++---- 1 file changed, 216 insertions(+), 30 deletions(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index d29443e57c..2761a35588 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -20,87 +20,273 @@ def __init__(self, dtype): self.tf = tf self.np = tnp - def _get_numpy_gate(self, name, params): - matrix = getattr(NumpyMatrices(self.dtype), name)(*params) - return self.tf.cast(matrix, dtype=self.dtype) - def RX(self, theta): - return self._get_numpy_gate("RX", [theta]) + cos = self.np.cos(theta / 2.0) + 0j + isin = -1j * self.np.sin(theta / 2.0) + return self.tf.cast([[cos, isin], [isin, cos]], dtype=self.dtype) def RY(self, theta): - return self._get_numpy_gate("RY", [theta]) + cos = self.np.cos(theta / 2.0) + 0j + sin = self.np.sin(theta / 2.0) + 0j + return self.tf.cast([[cos, -sin], [sin, cos]], dtype=self.dtype) def RZ(self, theta): - return self._get_numpy_gate("RZ", [theta]) + phase = self.np.exp(0.5j * theta) + return self.tf.cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype) def GPI(self, phi): - return self._get_numpy_gate("GPI", [phi]) + phase = self.np.exp(1.0j * phi) + return self.tf.cast([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype) def GPI2(self, phi): - return self._get_numpy_gate("GPI2", [phi]) + phase = self.np.exp(1.0j * phi) + return self.tf.cast( + [[1, -1.0j * self.np.conj(phase)], [-1.0j * phase, 1]], dtype=self.dtype + ) / self.np.sqrt(2) def U1(self, theta): - return self._get_numpy_gate("U1", [theta]) + phase = self.np.exp(1j * theta) + return self.tf.cast([[1, 0], [0, phase]], dtype=self.dtype) def U2(self, phi, lam): - return self._get_numpy_gate("U2", [phi, lam]) + eplus = self.np.exp(1j * (phi + lam) / 2.0) + eminus = self.np.exp(1j * (phi - lam) / 2.0) + return self.tf.cast( + [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]], + dtype=self.dtype, + ) / self.np.sqrt(2) def U3(self, theta, phi, lam): - return self._get_numpy_gate("U3", [theta, phi, lam]) + cost = self.np.cos(theta / 2) + sint = self.np.sin(theta / 2) + eplus = self.np.exp(1j * (phi + lam) / 2.0) + eminus = self.np.exp(1j * (phi - lam) / 2.0) + return self.tf.cast( + [ + [self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint], + [eminus * sint, eplus * cost], + ], + dtype=self.dtype, + ) def U1q(self, theta, phi): - return self._get_numpy_gate("U1q", [theta, phi]) + return self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi) def CRX(self, theta): - return self._get_numpy_gate("CRX", [theta]) + r = self.RX(theta) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def CRY(self, theta): - return self._get_numpy_gate("CRY", [theta]) + r = self.RY(theta) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def CRZ(self, theta): - return self._get_numpy_gate("CRZ", [theta]) + r = self.RZ(theta) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def CU1(self, theta): - return self._get_numpy_gate("CU1", [theta]) + r = self.U1(theta) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def CU2(self, phi, lam): - return self._get_numpy_gate("CU2", [phi, lam]) + r = self.U2(phi, lam) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def CU3(self, theta, phi, lam): - return self._get_numpy_gate("CU3", [theta, phi, lam]) + r = self.U3(theta, phi, lam) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, r[0, 0], r[0, 1]], + [0, 0, r[1, 0], r[1, 1]], + ], + dtype=self.dtype, + ) def fSim(self, theta, phi): - return self._get_numpy_gate("fSim", [theta, phi]) + cost = self.np.cos(theta) + 0j + isint = -1j * self.np.sin(theta) + phase = self.np.exp(-1j * phi) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, cost, isint, 0], + [0, isint, cost, 0], + [0, 0, 0, phase], + ], + dtype=self.dtype, + ) def GeneralizedfSim(self, u, phi): - return self._get_numpy_gate("GeneralizedfSim", [u, phi]) + phase = self.np.exp(-1j * phi) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, u[0, 0], u[0, 1], 0], + [0, u[1, 0], u[1, 1], 0], + [0, 0, 0, phase], + ], + dtype=self.dtype, + ) def RXX(self, theta): - return self._get_numpy_gate("RXX", [theta]) + cos = self.np.cos(theta / 2.0) + 0j + isin = -1j * self.np.sin(theta / 2.0) + return self.tf.cast( + [ + [cos, 0, 0, isin], + [0, cos, isin, 0], + [0, isin, cos, 0], + [isin, 0, 0, cos], + ], + dtype=self.dtype, + ) def RYY(self, theta): - return self._get_numpy_gate("RYY", [theta]) + cos = self.np.cos(theta / 2.0) + 0j + isin = -1j * self.np.sin(theta / 2.0) + return self.tf.cast( + [ + [cos, 0, 0, -isin], + [0, cos, isin, 0], + [0, isin, cos, 0], + [-isin, 0, 0, cos], + ], + dtype=self.dtype, + ) def RZZ(self, theta): - return self._get_numpy_gate("RZZ", [theta]) + phase = self.np.exp(0.5j * theta) + return self.tf.cast( + [ + [self.np.conj(phase), 0, 0, 0], + [0, phase, 0, 0], + [0, 0, phase, 0], + [0, 0, 0, self.np.conj(phase)], + ], + dtype=self.dtype, + ) def RZX(self, theta): - return self._get_numpy_gate("RZX", [theta]) + cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) + return self.tf.cast( + [ + [cos, -1j * sin, 0, 0], + [-1j * sin, cos, 0, 0], + [0, 0, cos, 1j * sin], + [0, 0, 1j * sin, cos], + ], + dtype=self.dtype, + ) def RXXYY(self, theta): - return self._get_numpy_gate("RXXYY", [theta]) + cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, cos, -1j * sin, 0], + [0, -1j * sin, cos, 0], + [0, 0, 0, 1], + ], + dtype=self.dtype, + ) def MS(self, phi0, phi1, theta): - return self._get_numpy_gate("MS", [phi0, phi1, theta]) + plus = self.np.exp(1.0j * (phi0 + phi1)) + minus = self.np.exp(1.0j * (phi0 - phi1)) + + return self.tf.cast( + [ + [ + self.np.cos(theta / 2), + 0, + 0, + -1.0j * self.np.conj(plus) * self.np.sin(theta / 2), + ], + [ + 0, + self.np.cos(theta / 2), + -1.0j * self.np.conj(minus) * self.np.sin(theta / 2), + 0, + ], + [0, -1.0j * minus * self.np.sin(theta / 2), self.np.cos(theta / 2), 0], + [-1.0j * plus * self.np.sin(theta / 2), 0, 0, self.np.cos(theta / 2)], + ], + dtype=self.dtype, + ) def GIVENS(self, theta): - return self._get_numpy_gate("GIVENS", [theta]) + return self.tf.cast( + [ + [1, 0, 0, 0], + [0, self.np.cos(theta), -self.np.sin(theta), 0], + [0, self.np.sin(theta), self.np.cos(theta), 0], + [0, 0, 0, 1], + ], + dtype=self.dtype, + ) def RBS(self, theta): - return self._get_numpy_gate("RBS", [theta]) + return self.GIVENS(-theta) def DEUTSCH(self, theta): - return self._get_numpy_gate("DEUTSCH", [theta]) + sin = self.np.sin(theta) + 0j # 0j necessary for right tensorflow dtype + cos = self.np.cos(theta) + return self.tf.cast( + [ + [1, 0, 0, 0, 0, 0, 0, 0], + [0, 1, 0, 0, 0, 0, 0, 0], + [0, 0, 1, 0, 0, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0], + [0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 0, 0], + [0, 0, 0, 0, 0, 0, 1j * cos, sin], + [0, 0, 0, 0, 0, 0, sin, 1j * cos], + ], + dtype=self.dtype, + ) + def Unitary(self, u): return self.tf.cast(u, dtype=self.dtype) From 4b3ac59a65cb246d0182e0fc976df8e32ad33a92 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sat, 10 Feb 2024 08:34:38 +0000 Subject: [PATCH 168/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/backends/tensorflow.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index 2761a35588..2f61234534 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -287,7 +287,6 @@ def DEUTSCH(self, theta): dtype=self.dtype, ) - def Unitary(self, u): return self.tf.cast(u, dtype=self.dtype) From a8109744649ab7cf169523fcbe32d207bc809b19 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 11 Feb 2024 10:18:51 +0400 Subject: [PATCH 169/200] fix bug --- src/qibo/backends/tensorflow.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index 2f61234534..939c2385b5 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -209,7 +209,7 @@ def RZZ(self, theta): ) def RZX(self, theta): - cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) + cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j return self.tf.cast( [ [cos, -1j * sin, 0, 0], @@ -221,7 +221,7 @@ def RZX(self, theta): ) def RXXYY(self, theta): - cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) + cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j return self.tf.cast( [ [1, 0, 0, 0], @@ -272,7 +272,7 @@ def RBS(self, theta): def DEUTSCH(self, theta): sin = self.np.sin(theta) + 0j # 0j necessary for right tensorflow dtype - cos = self.np.cos(theta) + cos = self.np.cos(theta) + 0j return self.tf.cast( [ [1, 0, 0, 0, 0, 0, 0, 0], From 7b03730beeb199e744f11d6f9a3d64dfb3735240 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 11 Feb 2024 10:42:13 +0400 Subject: [PATCH 170/200] fix bug --- src/qibo/backends/tensorflow.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index 939c2385b5..c57f7db8cf 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -235,23 +235,23 @@ def RXXYY(self, theta): def MS(self, phi0, phi1, theta): plus = self.np.exp(1.0j * (phi0 + phi1)) minus = self.np.exp(1.0j * (phi0 - phi1)) - + cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j return self.tf.cast( [ [ - self.np.cos(theta / 2), + cos, 0, 0, - -1.0j * self.np.conj(plus) * self.np.sin(theta / 2), + -1.0j * self.np.conj(plus) * sin, ], [ 0, - self.np.cos(theta / 2), - -1.0j * self.np.conj(minus) * self.np.sin(theta / 2), + cos, + -1.0j * self.np.conj(minus) * sin, 0, ], - [0, -1.0j * minus * self.np.sin(theta / 2), self.np.cos(theta / 2), 0], - [-1.0j * plus * self.np.sin(theta / 2), 0, 0, self.np.cos(theta / 2)], + [0, -1.0j * minus * sin, cos, 0], + [-1.0j * plus * sin, 0, 0, cos], ], dtype=self.dtype, ) From 85f26bc518229454cd7ce1ccc5acdcfea25bb15e Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Sun, 11 Feb 2024 10:45:31 +0400 Subject: [PATCH 171/200] pre-commit --- src/qibo/backends/tensorflow.py | 14 ++------------ 1 file changed, 2 insertions(+), 12 deletions(-) diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index c57f7db8cf..a710f0c165 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -238,18 +238,8 @@ def MS(self, phi0, phi1, theta): cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j return self.tf.cast( [ - [ - cos, - 0, - 0, - -1.0j * self.np.conj(plus) * sin, - ], - [ - 0, - cos, - -1.0j * self.np.conj(minus) * sin, - 0, - ], + [cos, 0, 0, -1.0j * self.np.conj(plus) * sin], + [0, cos, -1.0j * self.np.conj(minus) * sin, 0], [0, -1.0j * minus * sin, cos, 0], [-1.0j * plus * sin, 0, 0, cos], ], From 7816653a9d9d62ecc63ccbd257efa838a3a887c0 Mon Sep 17 00:00:00 2001 From: scarrazza Date: Mon, 12 Feb 2024 19:26:31 +0100 Subject: [PATCH 172/200] adding doi --- doc/source/appendix/citing-qibo.rst | 22 +++++++++++++++++++++- 1 file changed, 21 insertions(+), 1 deletion(-) diff --git a/doc/source/appendix/citing-qibo.rst b/doc/source/appendix/citing-qibo.rst index 40f8a3b456..7d08dc2e2d 100644 --- a/doc/source/appendix/citing-qibo.rst +++ b/doc/source/appendix/citing-qibo.rst @@ -69,8 +69,28 @@ Peer-Reviewed Articles * S. Efthymiou, A. Orgaz-Fuertes, R. Carobene, J. Cereijo, A. Pasquale, S. Ramos-Calderer, S. Bordoni, D. Fuentes-Ruiz, A. Candido, E. Pedicillo, M. Robbiati, Y.P. Tan, J. Wilkens, I. Roth, J.I. Latorre, S. Carrazza, *Qibolab: - an open-source hybrid quantum operating system* (2023), (`arXiv:2308.06313`_). + an open-source hybrid quantum operating system* (2023), + `doi:10.22331/q-2024-02-12-1247`_, (`arXiv:2308.06313`_). + In *BibTeX* format: + + .. code-block:: text + + @article{qibolab_paper, + doi = {10.22331/q-2024-02-12-1247}, + url = {https://doi.org/10.22331/q-2024-02-12-1247}, + title = {Qibolab: an open-source hybrid quantum operating system}, + author = {Efthymiou, Stavros and Orgaz-Fuertes, Alvaro and Carobene, Rodolfo and Cereijo, Juan and Pasquale, Andrea and Ramos-Calderer, Sergi and Bordoni, Simone and Fuentes-Ruiz, David and Candido, Alessandro and Pedicillo, Edoardo and Robbiati, Matteo and Tan, Yuanzheng Paul and Wilkens, Jadwiga and Roth, Ingo and Latorre, Jos{\'{e}} Ignacio and Carrazza, Stefano}, + journal = {{Quantum}}, + issn = {2521-327X}, + publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}}, + volume = {8}, + pages = {1247}, + month = feb, + year = {2024} + } + +.. _`doi:10.22331/q-2024-02-12-1247`: https://doi.org/10.22331/q-2024-02-12-1247 .. _`arXiv:2308.06313`: https://arxiv.org/abs/2308.06313 * R. Carobene, A. Candido, J. Serrano, A.O-Fuertes, A. Giachero, S. Carrazza, From dd0614753c5305914e9113b702315d10cc4398c1 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 13 Feb 2024 00:23:41 +0000 Subject: [PATCH 173/200] [pre-commit.ci] pre-commit autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black: 24.1.1 → 24.2.0](https://github.com/psf/black/compare/24.1.1...24.2.0) --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 28dfdd0dfc..b8632cdd54 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -9,7 +9,7 @@ repos: - id: check-yaml - id: debug-statements - repo: https://github.com/psf/black - rev: 24.1.1 + rev: 24.2.0 hooks: - id: black - repo: https://github.com/pycqa/isort From f944957ea3ae23acb1a3891702e9b0f1f7608652 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 11:20:46 +0400 Subject: [PATCH 174/200] stavros' suggestion --- src/qibo/backends/npmatrices.py | 96 ++++++------ src/qibo/backends/tensorflow.py | 260 +------------------------------- 2 files changed, 46 insertions(+), 310 deletions(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index ee65e90275..6cdbeb3973 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -1,5 +1,7 @@ from functools import cached_property +from scipy.linalg import block_diag + from qibo.config import raise_error @@ -12,6 +14,9 @@ def __init__(self, dtype): self.dtype = dtype self.np = np + def _cast(self, x, dtype): + return self.np.array(x, dtype=dtype) + @cached_property def H(self): return self.np.array([[1, 1], [1, -1]], dtype=self.dtype) / self.np.sqrt(2) @@ -66,35 +71,35 @@ def M(self): # pragma: no cover def RX(self, theta): cos = self.np.cos(theta / 2.0) + 0j isin = -1j * self.np.sin(theta / 2.0) - return self.np.array([[cos, isin], [isin, cos]], dtype=self.dtype) + return self._cast([[cos, isin], [isin, cos]], dtype=self.dtype) def RY(self, theta): cos = self.np.cos(theta / 2.0) + 0j - sin = self.np.sin(theta / 2.0) - return self.np.array([[cos, -sin], [sin, cos]], dtype=self.dtype) + sin = self.np.sin(theta / 2.0) + 0j + return self._cast([[cos, -sin], [sin, cos]], dtype=self.dtype) def RZ(self, theta): phase = self.np.exp(0.5j * theta) - return self.np.array([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype) + return self._cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype) def GPI(self, phi): phase = self.np.exp(1.0j * phi) - return self.np.array([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype) + return self._cast([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype) def GPI2(self, phi): phase = self.np.exp(1.0j * phi) - return self.np.array( + return self._cast( [[1, -1.0j * self.np.conj(phase)], [-1.0j * phase, 1]], dtype=self.dtype ) / self.np.sqrt(2) def U1(self, theta): phase = self.np.exp(1j * theta) - return self.np.array([[1, 0], [0, phase]], dtype=self.dtype) + return self._cast([[1, 0], [0, phase]], dtype=self.dtype) def U2(self, phi, lam): eplus = self.np.exp(1j * (phi + lam) / 2.0) eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.np.array( + return self._cast( [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]], dtype=self.dtype, ) / self.np.sqrt(2) @@ -104,7 +109,7 @@ def U3(self, theta, phi, lam): sint = self.np.sin(theta / 2) eplus = self.np.exp(1j * (phi + lam) / 2.0) eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.np.array( + return self._cast( [ [self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint], [eminus * sint, eplus * cost], @@ -153,34 +158,28 @@ def CSXDG(self): return self.np.transpose(self.np.conj(self.CSX)) def CRX(self, theta): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.RX(theta) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.RX(theta)) def CRY(self, theta): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.RY(theta) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.RY(theta)) def CRZ(self, theta): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.RZ(theta) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.RZ(theta)) def CU1(self, theta): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.U1(theta) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.U1(theta)) def CU2(self, phi, lam): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.U2(phi, lam) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.U2(phi, lam)) def CU3(self, theta, phi, lam): - m = self.np.eye(4, dtype=self.dtype) - m[2:, 2:] = self.U3(theta, phi, lam) - return m + identity = [[1.0, 0.0], [0.0, 1.0]] + return block_diag(identity, self.U3(theta, phi, lam)) @cached_property def SWAP(self): @@ -228,7 +227,7 @@ def fSim(self, theta, phi): cost = self.np.cos(theta) + 0j isint = -1j * self.np.sin(theta) phase = self.np.exp(-1j * phi) - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, cost, isint, 0], @@ -255,7 +254,7 @@ def SYC(self): def GeneralizedfSim(self, u, phi): phase = self.np.exp(-1j * phi) - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, complex(u[0, 0]), complex(u[0, 1]), 0], @@ -268,7 +267,7 @@ def GeneralizedfSim(self, u, phi): def RXX(self, theta): cos = self.np.cos(theta / 2.0) + 0j isin = -1j * self.np.sin(theta / 2.0) - return self.np.array( + return self._cast( [ [cos, 0, 0, isin], [0, cos, isin, 0], @@ -281,7 +280,7 @@ def RXX(self, theta): def RYY(self, theta): cos = self.np.cos(theta / 2.0) + 0j isin = -1j * self.np.sin(theta / 2.0) - return self.np.array( + return self._cast( [ [cos, 0, 0, -isin], [0, cos, isin, 0], @@ -293,7 +292,7 @@ def RYY(self, theta): def RZZ(self, theta): phase = self.np.exp(0.5j * theta) - return self.np.array( + return self._cast( [ [self.np.conj(phase), 0, 0, 0], [0, phase, 0, 0], @@ -304,8 +303,8 @@ def RZZ(self, theta): ) def RZX(self, theta): - cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) - return self.np.array( + cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j + return self._cast( [ [cos, -1j * sin, 0, 0], [-1j * sin, cos, 0, 0], @@ -316,8 +315,8 @@ def RZX(self, theta): ) def RXXYY(self, theta): - cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2) - return self.np.array( + cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j + return self._cast( [ [1, 0, 0, 0], [0, cos, -1j * sin, 0], @@ -330,29 +329,20 @@ def RXXYY(self, theta): def MS(self, phi0, phi1, theta): plus = self.np.exp(1.0j * (phi0 + phi1)) minus = self.np.exp(1.0j * (phi0 - phi1)) - - return self.np.array( + cos = self.np.cos(theta / 2) + 0j + sin = self.np.sin(theta / 2) + 0j + return self._cast( [ - [ - self.np.cos(theta / 2), - 0, - 0, - -1.0j * self.np.conj(plus) * self.np.sin(theta / 2), - ], - [ - 0, - self.np.cos(theta / 2), - -1.0j * self.np.conj(minus) * self.np.sin(theta / 2), - 0, - ], - [0, -1.0j * minus * self.np.sin(theta / 2), self.np.cos(theta / 2), 0], - [-1.0j * plus * self.np.sin(theta / 2), 0, 0, self.np.cos(theta / 2)], + [cos, 0, 0, -1.0j * self.np.conj(plus) * sin], + [0, cos, -1.0j * self.np.conj(minus) * sin, 0], + [0, -1.0j * minus * sin, cos, 0], + [-1.0j * plus * sin, 0, 0, cos], ], dtype=self.dtype, ) def GIVENS(self, theta): - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, self.np.cos(theta), -self.np.sin(theta), 0], diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py index a710f0c165..6490b37d9e 100644 --- a/src/qibo/backends/tensorflow.py +++ b/src/qibo/backends/tensorflow.py @@ -20,265 +20,11 @@ def __init__(self, dtype): self.tf = tf self.np = tnp - def RX(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - isin = -1j * self.np.sin(theta / 2.0) - return self.tf.cast([[cos, isin], [isin, cos]], dtype=self.dtype) - - def RY(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - sin = self.np.sin(theta / 2.0) + 0j - return self.tf.cast([[cos, -sin], [sin, cos]], dtype=self.dtype) - - def RZ(self, theta): - phase = self.np.exp(0.5j * theta) - return self.tf.cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype) - - def GPI(self, phi): - phase = self.np.exp(1.0j * phi) - return self.tf.cast([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype) - - def GPI2(self, phi): - phase = self.np.exp(1.0j * phi) - return self.tf.cast( - [[1, -1.0j * self.np.conj(phase)], [-1.0j * phase, 1]], dtype=self.dtype - ) / self.np.sqrt(2) - - def U1(self, theta): - phase = self.np.exp(1j * theta) - return self.tf.cast([[1, 0], [0, phase]], dtype=self.dtype) - - def U2(self, phi, lam): - eplus = self.np.exp(1j * (phi + lam) / 2.0) - eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.tf.cast( - [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]], - dtype=self.dtype, - ) / self.np.sqrt(2) - - def U3(self, theta, phi, lam): - cost = self.np.cos(theta / 2) - sint = self.np.sin(theta / 2) - eplus = self.np.exp(1j * (phi + lam) / 2.0) - eminus = self.np.exp(1j * (phi - lam) / 2.0) - return self.tf.cast( - [ - [self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint], - [eminus * sint, eplus * cost], - ], - dtype=self.dtype, - ) - - def U1q(self, theta, phi): - return self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi) - - def CRX(self, theta): - r = self.RX(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def CRY(self, theta): - r = self.RY(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def CRZ(self, theta): - r = self.RZ(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def CU1(self, theta): - r = self.U1(theta) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def CU2(self, phi, lam): - r = self.U2(phi, lam) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def CU3(self, theta, phi, lam): - r = self.U3(theta, phi, lam) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, 1, 0, 0], - [0, 0, r[0, 0], r[0, 1]], - [0, 0, r[1, 0], r[1, 1]], - ], - dtype=self.dtype, - ) - - def fSim(self, theta, phi): - cost = self.np.cos(theta) + 0j - isint = -1j * self.np.sin(theta) - phase = self.np.exp(-1j * phi) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, cost, isint, 0], - [0, isint, cost, 0], - [0, 0, 0, phase], - ], - dtype=self.dtype, - ) - - def GeneralizedfSim(self, u, phi): - phase = self.np.exp(-1j * phi) - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, u[0, 0], u[0, 1], 0], - [0, u[1, 0], u[1, 1], 0], - [0, 0, 0, phase], - ], - dtype=self.dtype, - ) - - def RXX(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - isin = -1j * self.np.sin(theta / 2.0) - return self.tf.cast( - [ - [cos, 0, 0, isin], - [0, cos, isin, 0], - [0, isin, cos, 0], - [isin, 0, 0, cos], - ], - dtype=self.dtype, - ) - - def RYY(self, theta): - cos = self.np.cos(theta / 2.0) + 0j - isin = -1j * self.np.sin(theta / 2.0) - return self.tf.cast( - [ - [cos, 0, 0, -isin], - [0, cos, isin, 0], - [0, isin, cos, 0], - [-isin, 0, 0, cos], - ], - dtype=self.dtype, - ) - - def RZZ(self, theta): - phase = self.np.exp(0.5j * theta) - return self.tf.cast( - [ - [self.np.conj(phase), 0, 0, 0], - [0, phase, 0, 0], - [0, 0, phase, 0], - [0, 0, 0, self.np.conj(phase)], - ], - dtype=self.dtype, - ) - - def RZX(self, theta): - cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j - return self.tf.cast( - [ - [cos, -1j * sin, 0, 0], - [-1j * sin, cos, 0, 0], - [0, 0, cos, 1j * sin], - [0, 0, 1j * sin, cos], - ], - dtype=self.dtype, - ) - - def RXXYY(self, theta): - cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, cos, -1j * sin, 0], - [0, -1j * sin, cos, 0], - [0, 0, 0, 1], - ], - dtype=self.dtype, - ) - - def MS(self, phi0, phi1, theta): - plus = self.np.exp(1.0j * (phi0 + phi1)) - minus = self.np.exp(1.0j * (phi0 - phi1)) - cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j - return self.tf.cast( - [ - [cos, 0, 0, -1.0j * self.np.conj(plus) * sin], - [0, cos, -1.0j * self.np.conj(minus) * sin, 0], - [0, -1.0j * minus * sin, cos, 0], - [-1.0j * plus * sin, 0, 0, cos], - ], - dtype=self.dtype, - ) - - def GIVENS(self, theta): - return self.tf.cast( - [ - [1, 0, 0, 0], - [0, self.np.cos(theta), -self.np.sin(theta), 0], - [0, self.np.sin(theta), self.np.cos(theta), 0], - [0, 0, 0, 1], - ], - dtype=self.dtype, - ) - - def RBS(self, theta): - return self.GIVENS(-theta) - - def DEUTSCH(self, theta): - sin = self.np.sin(theta) + 0j # 0j necessary for right tensorflow dtype - cos = self.np.cos(theta) + 0j - return self.tf.cast( - [ - [1, 0, 0, 0, 0, 0, 0, 0], - [0, 1, 0, 0, 0, 0, 0, 0], - [0, 0, 1, 0, 0, 0, 0, 0], - [0, 0, 0, 1, 0, 0, 0, 0], - [0, 0, 0, 0, 1, 0, 0, 0], - [0, 0, 0, 0, 0, 1, 0, 0], - [0, 0, 0, 0, 0, 0, 1j * cos, sin], - [0, 0, 0, 0, 0, 0, sin, 1j * cos], - ], - dtype=self.dtype, - ) + def _cast(self, x, dtype): + return self.tf.cast(x, dtype=dtype) def Unitary(self, u): - return self.tf.cast(u, dtype=self.dtype) + return self._cast(u, dtype=self.dtype) class TensorflowBackend(NumpyBackend): From a773410ce5890e1ca1b51a0bedf574b1ee342fde Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 12:59:22 +0400 Subject: [PATCH 175/200] fix controlled gates --- src/qibo/backends/npmatrices.py | 63 +++++++++++++++++++++++++-------- 1 file changed, 49 insertions(+), 14 deletions(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index 6cdbeb3973..12600e8b39 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -1,7 +1,5 @@ from functools import cached_property -from scipy.linalg import block_diag - from qibo.config import raise_error @@ -158,28 +156,65 @@ def CSXDG(self): return self.np.transpose(self.np.conj(self.CSX)) def CRX(self, theta): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.RX(theta)) + cos = self.np.cos(theta / 2.0) + 0j + isin = -1j * self.np.sin(theta / 2.0) + matrix = [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, cos, isin], + [0, 0, isin, cos], + ] + return self._cast(matrix, dtype=self.dtype) def CRY(self, theta): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.RY(theta)) + cos = self.np.cos(theta / 2.0) + 0j + sin = self.np.sin(theta / 2.0) + 0j + matrix = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, cos, -sin], [0, 0, sin, cos]] + return self._cast(matrix, dtype=self.dtype) def CRZ(self, theta): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.RZ(theta)) + phase = self.np.exp(0.5j * theta) + matrix = [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, self.np.conj(phase), 0], + [0, 0, 0, phase], + ] + return self._cast(matrix, dtype=self.dtype) def CU1(self, theta): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.U1(theta)) + phase = self.np.exp(1j * theta) + matrix = [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, phase], + ] + return self._cast(matrix, dtype=self.dtype) def CU2(self, phi, lam): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.U2(phi, lam)) + eplus = self.np.exp(1j * (phi + lam) / 2.0) / self.np.sqrt(2) + eminus = self.np.exp(1j * (phi - lam) / 2.0) / self.np.sqrt(2) + matrix = [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, self.np.conj(eplus), -self.np.conj(eminus)], + [0, 0, eminus, eplus], + ] + return self._cast(matrix, dtype=self.dtype) def CU3(self, theta, phi, lam): - identity = [[1.0, 0.0], [0.0, 1.0]] - return block_diag(identity, self.U3(theta, phi, lam)) + cost = self.np.cos(theta / 2) + sint = self.np.sin(theta / 2) + eplus = self.np.exp(1j * (phi + lam) / 2.0) + eminus = self.np.exp(1j * (phi - lam) / 2.0) + matrix = [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint], + [0, 0, eminus * sint, eplus * cost], + ] + return self._cast(matrix, dtype=self.dtype) @cached_property def SWAP(self): From afedc609dd03ac6a9c9a3edc1f29a34b4da15dbc Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 14:18:56 +0400 Subject: [PATCH 176/200] fix coverage --- tests/test_quantum_info_quantum_networks.py | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/tests/test_quantum_info_quantum_networks.py b/tests/test_quantum_info_quantum_networks.py index 9345ee3ede..1f20a97b45 100644 --- a/tests/test_quantum_info_quantum_networks.py +++ b/tests/test_quantum_info_quantum_networks.py @@ -28,6 +28,13 @@ def test_errors(backend): matrix = random_density_matrix(2**3, backend=backend) net = QuantumNetwork(matrix, (2,) * 3, backend=backend) + comb_partition = (2,) * 4 + comb_sys_out = (False, True) * 2 + comb = random_density_matrix(2**4, backend=backend) + comb_choi = QuantumNetwork( + comb, comb_partition, system_output=comb_sys_out, backend=backend + ) + with pytest.raises(TypeError): QuantumNetwork(channel.to_choi(backend=backend), partition=True) @@ -91,6 +98,18 @@ def test_errors(backend): with pytest.raises(NotImplementedError): net @ network + with pytest.raises(ValueError): + network @ net + + with pytest.raises(ValueError): + network @ QuantumNetwork(comb, (16, 16), pure=True, backend=backend) + + with pytest.raises(ValueError): + comb_choi @ QuantumNetwork(comb, (16, 16), pure=True, backend=backend) + + with pytest.raises(ValueError): + comb_choi @ net + with pytest.raises(ValueError): QuantumNetwork(matrix, (1, 2), backend=backend) From d180c71159bd056f55be2c3f95edf97f4c317e0f Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 16:35:03 +0400 Subject: [PATCH 177/200] fix seed --- tests/test_quantum_info_clifford.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_quantum_info_clifford.py b/tests/test_quantum_info_clifford.py index 3290aefc31..d6e12b3a36 100644 --- a/tests/test_quantum_info_clifford.py +++ b/tests/test_quantum_info_clifford.py @@ -68,7 +68,7 @@ def test_clifford_to_circuit(backend, nqubits, algorithm): if backend.__class__.__name__ == "TensorflowBackend": pytest.skip("CliffordBackend not defined for Tensorflow engine.") - clifford = random_clifford(nqubits, backend=backend) + clifford = random_clifford(nqubits, seed=10, backend=backend) symplectic_matrix_original = Clifford.from_circuit( clifford, engine=backend From 90826ff1cd2804857de7ecc67489941f5cf7e09a Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Tue, 13 Feb 2024 17:00:32 +0400 Subject: [PATCH 178/200] backend agnostic matrix definitions --- src/qibo/backends/npmatrices.py | 78 ++++++++++++++++++++------------- 1 file changed, 47 insertions(+), 31 deletions(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index 12600e8b39..ba7f14640d 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -17,51 +17,53 @@ def _cast(self, x, dtype): @cached_property def H(self): - return self.np.array([[1, 1], [1, -1]], dtype=self.dtype) / self.np.sqrt(2) + return self._cast([[1, 1], [1, -1]], dtype=self.dtype) / self.np.sqrt(2) @cached_property def X(self): - return self.np.array([[0, 1], [1, 0]], dtype=self.dtype) + return self._cast([[0, 1], [1, 0]], dtype=self.dtype) @cached_property def Y(self): - return self.np.array([[0, -1j], [1j, 0]], dtype=self.dtype) + return self._cast([[0, -1j], [1j, 0]], dtype=self.dtype) @cached_property def Z(self): - return self.np.array([[1, 0], [0, -1]], dtype=self.dtype) + return self._cast([[1, 0], [0, -1]], dtype=self.dtype) @cached_property def SX(self): - return self.np.array([[1 + 1j, 1 - 1j], [1 - 1j, 1 + 1j]], dtype=self.dtype) / 2 + return self._cast([[1 + 1j, 1 - 1j], [1 - 1j, 1 + 1j]], dtype=self.dtype) / 2 @cached_property def SXDG(self): - return self.np.transpose(self.np.conj(self.SX)) + return self._cast([[1 - 1j, 1 + 1j], [1 + 1j, 1 - 1j]], dtype=self.dtype) / 2 @cached_property def S(self): - return self.np.array([[1, 0], [0, 1j]], dtype=self.dtype) + return self._cast([[1, 0], [0, 1j]], dtype=self.dtype) @cached_property def SDG(self): - return self.np.conj(self.S) + return self._cast([[1, 0], [0, -1j]], dtype=self.dtype) @cached_property def T(self): - return self.np.array( + return self._cast( [[1, 0], [0, self.np.exp(1j * self.np.pi / 4.0)]], dtype=self.dtype ) @cached_property def TDG(self): - return self.np.conj(self.T) + return self._cast( + [[1, 0], [0, self.np.exp(-1j * self.np.pi / 4.0)]], dtype=self.dtype + ) def I(self, n=2): - return self.np.eye(n, dtype=self.dtype) + return self._cast(self.np.eye(n, dtype=self.dtype), dtype=self.dtype) def Align(self, n=2): - return self.I(n) + return self._cast(self.I(n), dtype=self.dtype) def M(self): # pragma: no cover raise_error(NotImplementedError) @@ -98,9 +100,10 @@ def U2(self, phi, lam): eplus = self.np.exp(1j * (phi + lam) / 2.0) eminus = self.np.exp(1j * (phi - lam) / 2.0) return self._cast( - [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]], + [[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]] + / self.np.sqrt(2), dtype=self.dtype, - ) / self.np.sqrt(2) + ) def U3(self, theta, phi, lam): cost = self.np.cos(theta / 2) @@ -116,24 +119,26 @@ def U3(self, theta, phi, lam): ) def U1q(self, theta, phi): - return self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi) + return self._cast( + self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi), dtype=self.dtype + ) @cached_property def CNOT(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]], dtype=self.dtype ) @cached_property def CY(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, -1j], [0, 0, 1j, 0]], dtype=self.dtype, ) @cached_property def CZ(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, -1]], dtype=self.dtype ) @@ -141,7 +146,7 @@ def CZ(self): def CSX(self): a = (1 + 1j) / 2 b = self.np.conj(a) - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, 1, 0, 0], @@ -153,7 +158,17 @@ def CSX(self): @cached_property def CSXDG(self): - return self.np.transpose(self.np.conj(self.CSX)) + a = (1 - 1j) / 2 + b = self.np.conj(a) + return self._cast( + [ + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, a, b], + [0, 0, b, a], + ], + dtype=self.dtype, + ) def CRX(self, theta): cos = self.np.cos(theta / 2.0) + 0j @@ -218,19 +233,19 @@ def CU3(self, theta, phi, lam): @cached_property def SWAP(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]], dtype=self.dtype ) @cached_property def iSWAP(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 0, 1j, 0], [0, 1j, 0, 0], [0, 0, 0, 1]], dtype=self.dtype ) @cached_property def SiSWAP(self): - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, 1 / self.np.sqrt(2), 1j / self.np.sqrt(2), 0], @@ -242,7 +257,7 @@ def SiSWAP(self): @cached_property def SiSWAPDG(self): - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, 1 / self.np.sqrt(2), -1j / self.np.sqrt(2), 0], @@ -254,7 +269,7 @@ def SiSWAPDG(self): @cached_property def FSWAP(self): - return self.np.array( + return self._cast( [[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, -1]], dtype=self.dtype ) @@ -277,7 +292,7 @@ def SYC(self): cost = self.np.cos(self.np.pi / 2) + 0j isint = -1j * self.np.sin(self.np.pi / 2) phase = self.np.exp(-1j * self.np.pi / 6) - return self.np.array( + return self._cast( [ [1, 0, 0, 0], [0, cost, isint, 0], @@ -392,14 +407,14 @@ def RBS(self, theta): @cached_property def ECR(self): - return self.np.array( + return self._cast( [[0, 0, 1, 1j], [0, 0, 1j, 1], [1, -1j, 0, 0], [-1j, 1, 0, 0]], dtype=self.dtype, ) / self.np.sqrt(2) @cached_property def TOFFOLI(self): - return self.np.array( + return self._cast( [ [1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], @@ -409,13 +424,14 @@ def TOFFOLI(self): [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 1, 0], - ] + ], + dtype=self.dtype, ) def DEUTSCH(self, theta): sin = self.np.sin(theta) + 0j # 0j necessary for right tensorflow dtype - cos = self.np.cos(theta) - return self.np.array( + cos = self.np.cos(theta) + 0j + return self._cast( [ [1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], From 0a1407f3f0d77ad35c655e78fdd4944a048567b2 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 19:17:15 +0400 Subject: [PATCH 179/200] two seeds --- tests/test_quantum_info_clifford.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_quantum_info_clifford.py b/tests/test_quantum_info_clifford.py index d6e12b3a36..cc32aadcde 100644 --- a/tests/test_quantum_info_clifford.py +++ b/tests/test_quantum_info_clifford.py @@ -62,13 +62,14 @@ def test_clifford_from_circuit(backend, measurement): backend.assert_allclose(obj.probabilities(), result.probabilities()) +@pytest.mark.parametrize("seed", [None, 10]) @pytest.mark.parametrize("algorithm", ["AG04", "BM20"]) @pytest.mark.parametrize("nqubits", [1, 2, 3, 10, 50]) def test_clifford_to_circuit(backend, nqubits, algorithm): if backend.__class__.__name__ == "TensorflowBackend": pytest.skip("CliffordBackend not defined for Tensorflow engine.") - clifford = random_clifford(nqubits, seed=10, backend=backend) + clifford = random_clifford(nqubits, seed=seed, backend=backend) symplectic_matrix_original = Clifford.from_circuit( clifford, engine=backend From cf95b450820ccd5a6be90107fe17107eb26de432 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Tue, 13 Feb 2024 19:17:57 +0400 Subject: [PATCH 180/200] fix test --- tests/test_quantum_info_clifford.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_quantum_info_clifford.py b/tests/test_quantum_info_clifford.py index cc32aadcde..7ca2577087 100644 --- a/tests/test_quantum_info_clifford.py +++ b/tests/test_quantum_info_clifford.py @@ -65,7 +65,7 @@ def test_clifford_from_circuit(backend, measurement): @pytest.mark.parametrize("seed", [None, 10]) @pytest.mark.parametrize("algorithm", ["AG04", "BM20"]) @pytest.mark.parametrize("nqubits", [1, 2, 3, 10, 50]) -def test_clifford_to_circuit(backend, nqubits, algorithm): +def test_clifford_to_circuit(backend, nqubits, algorithm, seed): if backend.__class__.__name__ == "TensorflowBackend": pytest.skip("CliffordBackend not defined for Tensorflow engine.") From f4ca928850b59777a0c102a0d6d1518297eb0688 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 14 Feb 2024 08:32:04 +0400 Subject: [PATCH 181/200] fix seed --- tests/test_quantum_info_clifford.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_quantum_info_clifford.py b/tests/test_quantum_info_clifford.py index 7ca2577087..ebde9aff5c 100644 --- a/tests/test_quantum_info_clifford.py +++ b/tests/test_quantum_info_clifford.py @@ -62,7 +62,7 @@ def test_clifford_from_circuit(backend, measurement): backend.assert_allclose(obj.probabilities(), result.probabilities()) -@pytest.mark.parametrize("seed", [None, 10]) +@pytest.mark.parametrize("seed", [1, 10]) @pytest.mark.parametrize("algorithm", ["AG04", "BM20"]) @pytest.mark.parametrize("nqubits", [1, 2, 3, 10, 50]) def test_clifford_to_circuit(backend, nqubits, algorithm, seed): From 19583bcc2931c989bb6802c836e0cf9b96f87dae Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Wed, 14 Feb 2024 13:05:02 +0400 Subject: [PATCH 182/200] fix `tensorflow` issues --- src/qibo/backends/npmatrices.py | 36 +++++++++++++++++++++------------ 1 file changed, 23 insertions(+), 13 deletions(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index ba7f14640d..fd7c78db1e 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -25,7 +25,7 @@ def X(self): @cached_property def Y(self): - return self._cast([[0, -1j], [1j, 0]], dtype=self.dtype) + return self._cast([[0j, -1j], [1j, 0j]], dtype=self.dtype) @cached_property def Z(self): @@ -41,11 +41,11 @@ def SXDG(self): @cached_property def S(self): - return self._cast([[1, 0], [0, 1j]], dtype=self.dtype) + return self._cast([[1 + 0j, 0j], [0j, 1j]], dtype=self.dtype) @cached_property def SDG(self): - return self._cast([[1, 0], [0, -1j]], dtype=self.dtype) + return self._cast([[1 + 0j, 0j], [0j, -1j]], dtype=self.dtype) @cached_property def T(self): @@ -132,7 +132,12 @@ def CNOT(self): @cached_property def CY(self): return self._cast( - [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, -1j], [0, 0, 1j, 0]], + [ + [1 + 0j, 0j, 0j, 0j], + [0j, 1 + 0j, 0j, 0j], + [0j, 0j, 0j, -1j], + [0j, 0j, 1j, 0j], + ], dtype=self.dtype, ) @@ -247,10 +252,10 @@ def iSWAP(self): def SiSWAP(self): return self._cast( [ - [1, 0, 0, 0], - [0, 1 / self.np.sqrt(2), 1j / self.np.sqrt(2), 0], - [0, 1j / self.np.sqrt(2), 1 / self.np.sqrt(2), 0], - [0, 0, 0, 1], + [1 + 0j, 0j, 0j, 0j], + [0j, 1 / self.np.sqrt(2) + 0j, 1j / self.np.sqrt(2), 0j], + [0j, 1j / self.np.sqrt(2), 1 / self.np.sqrt(2) + 0j, 0j], + [0j, 0j, 0j, 1 + 0j], ], dtype=self.dtype, ) @@ -259,10 +264,10 @@ def SiSWAP(self): def SiSWAPDG(self): return self._cast( [ - [1, 0, 0, 0], - [0, 1 / self.np.sqrt(2), -1j / self.np.sqrt(2), 0], - [0, -1j / self.np.sqrt(2), 1 / self.np.sqrt(2), 0], - [0, 0, 0, 1], + [1 + 0j, 0j, 0j, 0j], + [0j, 1 / self.np.sqrt(2) + 0j, -1j / self.np.sqrt(2), 0j], + [0j, -1j / self.np.sqrt(2), 1 / self.np.sqrt(2) + 0j, 0j], + [0j, 0j, 0j, 1 + 0j], ], dtype=self.dtype, ) @@ -408,7 +413,12 @@ def RBS(self, theta): @cached_property def ECR(self): return self._cast( - [[0, 0, 1, 1j], [0, 0, 1j, 1], [1, -1j, 0, 0], [-1j, 1, 0, 0]], + [ + [0j, 0j, 1 + 0j, 1j], + [0j, 0j, 1j, 1 + 0j], + [1 + 0j, -1j, 0j, 0j], + [-1j, 1 + 0j, 0j, 0j], + ], dtype=self.dtype, ) / self.np.sqrt(2) From ee34da2f25e2d0a2b9f20b48a911c7982a18a699 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 14 Feb 2024 14:58:39 +0400 Subject: [PATCH 183/200] avoid raise_error in block decomposition --- src/qibo/transpiler/blocks.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/src/qibo/transpiler/blocks.py b/src/qibo/transpiler/blocks.py index 5b881d9e06..6e2b1122a2 100644 --- a/src/qibo/transpiler/blocks.py +++ b/src/qibo/transpiler/blocks.py @@ -65,8 +65,8 @@ def fuse(self, block, name: Optional[str] = None): (:class:`qibo.transpiler.blocks.Block`): fusion of the two input blocks. """ if not self.qubits == block.qubits: - raise BlockingError( - "In order to fuse two blocks their qubits must coincide." + raise_error( + BlockingError, "In order to fuse two blocks their qubits must coincide." ) return Block(qubits=self.qubits, gates=self.gates + block.gates, name=name) @@ -200,12 +200,11 @@ def block_decomposition(circuit: Circuit, fuse: bool = True): remove_list = [first_block] if len(initial_blocks[1:]) > 0: for second_block in initial_blocks[1:]: - try: + if second_block.qubits == first_block.qubits: first_block = first_block.fuse(second_block) remove_list.append(second_block) - except BlockingError: - if not first_block.commute(second_block): - break + elif not first_block.commute(second_block): + break blocks.append(first_block) _remove_gates(initial_blocks, remove_list) From 783f9082d5aa7beb26f97d227332059bf298951d Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 14 Feb 2024 14:40:55 +0400 Subject: [PATCH 184/200] ... --- src/qibo/backends/npmatrices.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index fd7c78db1e..09a794cef6 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -163,6 +163,7 @@ def CSX(self): @cached_property def CSXDG(self): + # return self.np.conj(self.CSX) a = (1 - 1j) / 2 b = self.np.conj(a) return self._cast( From 2984d2dc7fd38e08442d0c0f2e5340744a27254e Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 14 Feb 2024 15:06:04 +0400 Subject: [PATCH 185/200] test with qibojit update --- pyproject.toml | 6 +++--- src/qibo/backends/npmatrices.py | 1 - 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index bb2b539695..bdcd37e76b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,7 +62,7 @@ dill = "^0.3.6" pytest-cov = "^4.0.0" pylint = "^3.0.3" matplotlib = "^3.7.0" -qibojit = { git = "https://github.com/qiboteam/qibojit.git" } +qibojit = { git = "https://github.com/qiboteam/qibojit.git", brach = "sxdg" } tensorflow = { version = "^2.14.1", markers = "sys_platform == 'linux'" } [tool.poe.tasks] @@ -79,7 +79,7 @@ optional = true [tool.poetry.group.cuda11.dependencies] cupy-cuda11x = "^12.0.0" cuquantum-python-cu11 = "^23.3.0" -qibojit = { git = "https://github.com/qiboteam/qibojit.git" } +qibojit = { git = "https://github.com/qiboteam/qibojit.git"} [tool.poetry.group.cuda12] optional = true @@ -87,7 +87,7 @@ optional = true [tool.poetry.group.cuda12.dependencies] cupy-cuda12x = "^12.0.0" cuquantum-python-cu12 = "^23.3.0" -qibojit = { git = "https://github.com/qiboteam/qibojit.git" } +qibojit = { git = "https://github.com/qiboteam/qibojit.git"} [tool.pylint.reports] output-format = "colorized" diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index 09a794cef6..fd7c78db1e 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -163,7 +163,6 @@ def CSX(self): @cached_property def CSXDG(self): - # return self.np.conj(self.CSX) a = (1 - 1j) / 2 b = self.np.conj(a) return self._cast( From ba5ae244110f7b1dc29d2589e8b0a1466b055e13 Mon Sep 17 00:00:00 2001 From: simone bordoni Date: Wed, 14 Feb 2024 16:10:14 +0400 Subject: [PATCH 186/200] update tests dependency --- poetry.lock | 1448 ++++++++++++++++++++++++------------------------ pyproject.toml | 6 +- 2 files changed, 736 insertions(+), 718 deletions(-) diff --git a/poetry.lock b/poetry.lock index d9f70f1364..ef54e2c382 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,24 +2,24 @@ [[package]] name = "absl-py" -version = "2.0.0" +version = "2.1.0" description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py." optional = false python-versions = ">=3.7" files = [ - {file = "absl-py-2.0.0.tar.gz", hash = "sha256:d9690211c5fcfefcdd1a45470ac2b5c5acd45241c3af71eed96bc5441746c0d5"}, - {file = "absl_py-2.0.0-py3-none-any.whl", hash = "sha256:9a28abb62774ae4e8edbe2dd4c49ffcd45a6a848952a5eccc6a49f3f0fc1e2f3"}, + {file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"}, + {file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"}, ] [[package]] name = "alabaster" -version = "0.7.13" -description = "A configurable sidebar-enabled Sphinx theme" +version = "0.7.16" +description = "A light, configurable Sphinx theme" optional = false -python-versions = ">=3.6" +python-versions = ">=3.9" files = [ - {file = "alabaster-0.7.13-py3-none-any.whl", hash = "sha256:1ee19aca801bbabb5ba3f5f258e4422dfa86f82f3e9cefb0859b283cdd7f62a3"}, - {file = "alabaster-0.7.13.tar.gz", hash = "sha256:a27a4a084d5e690e16e01e03ad2b2e552c61a65469419b907243193de1a84ae2"}, + {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"}, + {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"}, ] [[package]] @@ -46,13 +46,13 @@ trio = ["trio (>=0.23)"] [[package]] name = "astroid" -version = "3.0.2" +version = "3.0.3" description = "An abstract syntax tree for Python with inference support." optional = false python-versions = ">=3.8.0" files = [ - {file = "astroid-3.0.2-py3-none-any.whl", hash = "sha256:d6e62862355f60e716164082d6b4b041d38e2a8cf1c7cd953ded5108bac8ff5c"}, - {file = "astroid-3.0.2.tar.gz", hash = "sha256:4a61cf0a59097c7bb52689b0fd63717cd2a8a14dc9f1eee97b82d814881c8c91"}, + {file = "astroid-3.0.3-py3-none-any.whl", hash = "sha256:92fcf218b89f449cdf9f7b39a269f8d5d617b27be68434912e11e79203963a17"}, + {file = "astroid-3.0.3.tar.gz", hash = "sha256:4148645659b08b70d72460ed1921158027a9e53ae8b7234149b1400eddacbb93"}, ] [package.dependencies] @@ -124,19 +124,22 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"] [[package]] name = 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deletion(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py index fd7c78db1e..0e1e4705e3 100644 --- a/src/qibo/backends/npmatrices.py +++ b/src/qibo/backends/npmatrices.py @@ -245,7 +245,13 @@ def SWAP(self): @cached_property def iSWAP(self): return self._cast( - [[1, 0, 0, 0], [0, 0, 1j, 0], [0, 1j, 0, 0], [0, 0, 0, 1]], dtype=self.dtype + [ + [1+0j, 0j, 0j, 0j], + [0j, 0j, 1j, 0j], + [0j, 1j, 0j, 0j], + [0j, 0j, 0j, 1+0j], + ], + dtype=self.dtype ) @cached_property From efa49006116fc8d57c14bbf0502ca1bd105d23bc Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 14 Feb 2024 14:34:38 +0000 Subject: [PATCH 188/200] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- src/qibo/backends/npmatrices.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/src/qibo/backends/npmatrices.py b/src/qibo/backends/npmatrices.py 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cupy-cuda12x = "^12.0.0" cuquantum-python-cu12 = "^23.3.0" -qibojit = { git = "https://github.com/qiboteam/qibojit.git", branch = "sxdg" } +qibojit = { git = "https://github.com/qiboteam/qibojit.git" } [tool.pylint.reports] output-format = "colorized" From 208dbdb7da9a93e3c9d0ae68beea7ec6045a699a Mon Sep 17 00:00:00 2001 From: Alessandro Candido Date: Thu, 15 Feb 2024 10:17:06 +0100 Subject: [PATCH 190/200] chore: Add codecov threshold, and remove PR annotations --- .github/.codecov.yml | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/.github/.codecov.yml b/.github/.codecov.yml index 0c6bd02622..1bf339e4b0 100644 --- a/.github/.codecov.yml +++ b/.github/.codecov.yml @@ -1,3 +1,12 @@ +coverage: + status: + project: + default: + threshold: 0.5% + +github_checks: + annotations: false + ignore: - "setup.py" - "src/qibo/tests/test_custom_functions.py" From d96e52f3e26d48b51191a703ef07a30de1492acc Mon Sep 17 00:00:00 2001 From: Alessandro Candido Date: Thu, 15 Feb 2024 11:01:15 +0100 Subject: [PATCH 191/200] chore: Unhide codecov file Since already inside a hidden folder --- .github/{.codecov.yml => codecov.yml} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename .github/{.codecov.yml => codecov.yml} (100%) diff --git a/.github/.codecov.yml b/.github/codecov.yml similarity index 100% rename from .github/.codecov.yml rename to .github/codecov.yml From 4722f501cc87229be80ad412d5a67f04cb767bef Mon Sep 17 00:00:00 2001 From: MatteoRobbiati Date: Thu, 15 Feb 2024 17:36:58 +0100 Subject: [PATCH 192/200] fix math rendering --- src/qibo/quantum_info/random_ensembles.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index b1be867620..3571274770 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -32,7 +32,8 @@ def _ppf(self, theta: float): def uniform_sampling_U3(ngates: int, seed=None, backend=None): - """Samples parameters for Haar-random :math:`U_{3}`s (:class:`qibo.gates.U3`). + """ + Samples parameters for Haar-random :math:`U_{3}` (``qibo.gates.U3``). Args: ngates (int): Total number of :math:`U_{3}`s to be sampled. From f73be7c9b730edefddab7ee1b68723589e07cf01 Mon Sep 17 00:00:00 2001 From: Matteo Robbiati <62071516+MatteoRobbiati@users.noreply.github.com> Date: Thu, 15 Feb 2024 17:38:41 +0100 Subject: [PATCH 193/200] Update random_ensembles.py --- src/qibo/quantum_info/random_ensembles.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index 3571274770..d16b77f416 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -32,8 +32,7 @@ def _ppf(self, theta: float): def uniform_sampling_U3(ngates: int, seed=None, backend=None): - """ - Samples parameters for Haar-random :math:`U_{3}` (``qibo.gates.U3``). + """Samples parameters for Haar-random :math:`U_{3}` (``qibo.gates.U3``). Args: ngates (int): Total number of :math:`U_{3}`s to be sampled. 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-content-hash = "ceb8a39781a941368015611e00cb7e27ded43108428c638ea38576d759e0a3da" +content-hash = "32240d5c176ef55b4c88f63adf9489e3b0cffeb430b9b40ca1c53dc08291ac1c" diff --git a/pyproject.toml b/pyproject.toml index 52f27ec003..82b35e3938 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -31,7 +31,7 @@ tabulate = "^0.9.0" numpy = "^1.26.4" networkx = "^3.2.1" cvxpy = {version = "^1.4.2", optional = true} -tensorflow = {version = "^2.14.1", optional = true} +tensorflow = { version = "^2.14.1", markers = "sys_platform == 'linux' or sys_platform == 'darwin'", optional = true} [tool.poetry.group.dev] optional = true From 82ade86eaed41c6cf253f9ae88fab368c7d69aa2 Mon Sep 17 00:00:00 2001 From: scarrazza Date: Fri, 16 Feb 2024 06:36:41 +0100 Subject: [PATCH 197/200] fixing extra spaces added by poetry --- pyproject.toml | 8 -------- 1 file changed, 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 82b35e3938..da2ee7a8d4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -77,10 +77,6 @@ docs = "make -C doc html" docs-clean = "make -C doc clean" test-docs = "make -C doc doctest" - - - - [tool.poetry.group.cuda11] optional = true @@ -89,10 +85,6 @@ cupy-cuda11x = "^12.0.0" cuquantum-python-cu11 = "^23.3.0" qibojit = { git = "https://github.com/qiboteam/qibojit.git" } - - - - [tool.poetry.group.cuda12] optional = true From 498857db63e29a424bae90cfa2647b62ceaf93b5 Mon Sep 17 00:00:00 2001 From: Renato Mello Date: Fri, 16 Feb 2024 10:00:36 +0400 Subject: [PATCH 198/200] doc fix --- src/qibo/quantum_info/random_ensembles.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/qibo/quantum_info/random_ensembles.py b/src/qibo/quantum_info/random_ensembles.py index d16b77f416..94159cf1b2 100644 --- a/src/qibo/quantum_info/random_ensembles.py +++ b/src/qibo/quantum_info/random_ensembles.py @@ -32,10 +32,10 @@ def _ppf(self, theta: float): def uniform_sampling_U3(ngates: int, seed=None, backend=None): - """Samples parameters for Haar-random :math:`U_{3}` (``qibo.gates.U3``). + """Samples parameters for Haar-random :class:`qibo.gates.U3`. Args: - ngates (int): Total number of :math:`U_{3}`s to be sampled. + ngates (int): Total number of :math:`U_{3}` gates to be sampled. seed (int or :class:`numpy.random.Generator`, optional): Either a generator of random numbers or a fixed seed to initialize a generator. If ``None``, initializes a generator with a random seed. Default: ``None``. @@ -44,7 +44,7 @@ def uniform_sampling_U3(ngates: int, seed=None, backend=None): Defaults to ``None``. Returns: - (ndarray): array of shape (``ngates``, :math:`3`). + ndarray: array of shape (``ngates``, :math:`3`). """ if not isinstance(ngates, int): raise_error( From 47b251845c8cbc6dea15348d91f6ec32240576f8 Mon Sep 17 00:00:00 2001 From: Alessandro Candido Date: Fri, 16 Feb 2024 09:58:45 +0100 Subject: [PATCH 199/200] chore: Remove no longer required exceptions for Codecov --- .github/codecov.yml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.github/codecov.yml b/.github/codecov.yml index 1bf339e4b0..5571132e2b 100644 --- a/.github/codecov.yml +++ b/.github/codecov.yml @@ -6,7 +6,3 @@ coverage: github_checks: annotations: false - -ignore: - - "setup.py" - - "src/qibo/tests/test_custom_functions.py" From a47e60c0712bc99c80357d72ceb6cf5bc50e9a1a Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 20 Feb 2024 00:40:38 +0000 Subject: [PATCH 200/200] [pre-commit.ci] pre-commit autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/asottile/pyupgrade: v3.15.0 → v3.15.1](https://github.com/asottile/pyupgrade/compare/v3.15.0...v3.15.1) --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index b8632cdd54..9e5265c24b 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -18,7 +18,7 @@ repos: - id: isort args: ["--profile", "black"] - repo: https://github.com/asottile/pyupgrade - rev: v3.15.0 + rev: v3.15.1 hooks: - id: pyupgrade - repo: https://github.com/hadialqattan/pycln