Address executor and observable incompatibility

docs/source/guide/executors.md

@@ -30,7 +30,9 @@ To instantiate an `Executor`, provide a function which either:
 1. Inputs a `mitiq.QPROGRAM` and outputs a `mitiq.QuantumResult`.
 2. Inputs a sequence of `mitiq.QPROGRAM`s and outputs a sequence of `mitiq.QuantumResult`s.
 
-**The function must be [annotated](https://peps.python.org/pep-3107/) to tell Mitiq which type of `QuantumResult` it returns. Functions with no annotations are assumed to return `float`s.**
+```{warning}
+To avoid confusion and invalid results, the executor function must be [annotated](https://peps.python.org/pep-3107/) to tell Mitiq which type of `QuantumResult` it returns. Functions without annotations are assumed to return `float`s.
+```
 
 A `QPROGRAM` is "something which a quantum computer inputs" and a `QuantumResult` is "something which a quantum computer outputs." The latter is canonically a bitstring for real quantum hardware, but can be other objects for testing, e.g. a density matrix.
 

docs/source/guide/observables.md

@@ -128,8 +128,8 @@ obs.expectation(circuit, execute=mitiq_cirq.sample_bitstrings)
 
 In error mitigation techniques, you can provide an observable to specify the expectation value to mitigate.
 
-```{admonition} Note:
-When specifying an `Observable`, you must ensure that the return type of the executor function is `MeasurementResultLike` or `DensityMatrixLike`.
+```{warning}
+As note in the [executor documentation](./executors.md#the-input-function), the executor must be annotated with the appropriate type hinting for the return type. Additionally, when specifying an `Observable`, you must ensure that the return type of the executor function is `MeasurementResultLike` or `DensityMatrixLike`.
 ```
 
 ```{code-cell} ipython3

mitiq/executor/executor.py

@@ -40,6 +40,8 @@
 FloatLike = [
     None,  # Untyped executors are assumed to return floats.
     float,
+    np.float32,
+    np.float64,
     Iterable[float],
     List[float],
     Sequence[float],
@@ -149,6 +151,29 @@ def evaluate(
                 "Expected observable to be hermitian. Continue with caution."
             )
 
+        # Check executor and observable compatability with type hinting
+        # If FloatLike is specified as a return and observable is used
+        if self._executor_return_type in FloatLike and observable is not None:
+            if self._executor_return_type is not None:
+                raise ValueError(
+                    "When using a float like result, measurements should be "
+                    "included manually and an observable should not be "
+                    "used."
+                )
+        elif observable is None:
+            # Type hinted as DensityMatrixLik but no observable is set
+            if self._executor_return_type in DensityMatrixLike:
+                raise ValueError(
+                    "When using a density matrix like result, an observable "
+                    "is required."
+                )
+            # Type hinted as MeasurementResulteLike but no observable is set
+            elif self._executor_return_type in MeasurementResultLike:
+                raise ValueError(
+                    "When using a measurement, or bitstring, like result, an "
+                    "observable is required."
+                )
+
         # Get all required circuits to run.
         if (
             observable is not None
@@ -160,38 +185,55 @@ def evaluate(
                 for circuit_with_measurements in observable.measure_in(circuit)
             ]
             result_step = observable.ngroups
-        elif (
-            observable is not None
-            and self._executor_return_type not in MeasurementResultLike
-            and self._executor_return_type not in DensityMatrixLike
-        ):
-            raise ValueError(
-                """Executor and observable are not compatible. Executors
-                returning expectation values as float must be used with
-                observable=None"""
-            )
         else:
             all_circuits = circuits
             result_step = 1
 
         # Run all required circuits.
-        all_results = self.run(all_circuits, force_run_all, **kwargs)
+        try:
+            all_results = self.run(all_circuits, force_run_all, **kwargs)
+        except Exception:
+            if observable is not None and self._executor_return_type is None:
+                all_circuits = [
+                    circuit_with_measurements
+                    for circuit in circuits
+                    for circuit_with_measurements in observable.measure_in(
+                        circuit
+                    )
+                ]
+                all_results = self.run(all_circuits, force_run_all, **kwargs)
+            else:
+                raise
+
+        # check returned type
+        manual_return_type = None
+        if len(all_results) > 0:
+            manual_return_type = type(all_results[0])
 
         # Parse the results.
-        if self._executor_return_type in FloatLike:
+        if (
+            self._executor_return_type in FloatLike
+            and self._executor_return_type is not None
+        ) or manual_return_type in FloatLike:
             results = np.real_if_close(
                 cast(Sequence[float], all_results)
             ).tolist()
 
-        elif self._executor_return_type in DensityMatrixLike:
+        elif (
+            self._executor_return_type in DensityMatrixLike
+            or manual_return_type in DensityMatrixLike
+        ):
             observable = cast(Observable, observable)
             all_results = cast(List[npt.NDArray[np.complex64]], all_results)
             results = [
                 observable._expectation_from_density_matrix(density_matrix)
                 for density_matrix in all_results
             ]
 
-        elif self._executor_return_type in MeasurementResultLike:
+        elif (
+            self._executor_return_type in MeasurementResultLike
+            or manual_return_type in MeasurementResultLike
+        ):
             observable = cast(Observable, observable)
             all_results = cast(List[MeasurementResult], all_results)
             results = [

mitiq/executor/tests/test_executor.py

@@ -12,6 +12,7 @@
 import numpy as np
 import pyquil
 import pytest
+from qiskit import QuantumCircuit
 
 from mitiq import MeasurementResult
 from mitiq.executor.executor import Executor
@@ -37,7 +38,7 @@ def executor_batched_unique(circuits) -> List[float]:
     return [executor_serial_unique(circuit) for circuit in circuits]
 
 
-def executor_serial_unique(circuit):
+def executor_serial_unique(circuit) -> float:
     return float(len(circuit))
 
 
@@ -58,21 +59,29 @@ def executor_pyquil_batched(programs) -> List[float]:
 
 
 # Serial / batched executors which return measurements.
-def executor_measurements(circuit) -> MeasurementResult:
+def executor_measurements(circuit):
+    return sample_bitstrings(circuit, noise_level=(0,))
+
+
+def executor_measurements_typed(circuit) -> MeasurementResult:
     return sample_bitstrings(circuit, noise_level=(0,))
 
 
 def executor_measurements_batched(circuits) -> List[MeasurementResult]:
-    return [executor_measurements(circuit) for circuit in circuits]
+    return [executor_measurements_typed(circuit) for circuit in circuits]
 
 
 # Serial / batched executors which return density matrices.
-def executor_density_matrix(circuit) -> np.ndarray:
+def executor_density_matrix(circuit):
+    return compute_density_matrix(circuit, noise_level=(0,))
+
+
+def executor_density_matrix_typed(circuit) -> np.ndarray:
     return compute_density_matrix(circuit, noise_level=(0,))
 
 
 def executor_density_matrix_batched(circuits) -> List[np.ndarray]:
-    return [executor_density_matrix(circuit) for circuit in circuits]
+    return [executor_density_matrix_typed(circuit) for circuit in circuits]
 
 
 def test_executor_simple():
@@ -86,7 +95,7 @@ def test_executor_is_batched_executor():
     assert Executor.is_batched_executor(executor_batched)
     assert not Executor.is_batched_executor(executor_serial_typed)
     assert not Executor.is_batched_executor(executor_serial)
-    assert not Executor.is_batched_executor(executor_measurements)
+    assert not Executor.is_batched_executor(executor_measurements_typed)
     assert Executor.is_batched_executor(executor_measurements_batched)
 
 
@@ -96,7 +105,7 @@ def test_executor_non_hermitian_observable():
     q = cirq.LineQubit(0)
     circuits = [cirq.Circuit(cirq.I.on(q)), cirq.Circuit(cirq.X.on(q))]
 
-    executor = Executor(executor_measurements)
+    executor = Executor(executor_measurements_typed)
 
     with pytest.warns(UserWarning, match="hermitian"):
         executor.evaluate(circuits, obs)
@@ -199,53 +208,27 @@ def test_run_executor_preserves_order(s, b):
 )
 def test_executor_evaluate_float(execute):
     q = cirq.LineQubit(0)
-    circuits = [cirq.Circuit(cirq.X(q)), cirq.Circuit(cirq.H(q), cirq.Z(q))]
+    circuits = [
+        cirq.Circuit(cirq.X(q), cirq.M(q)),
+        cirq.Circuit(cirq.H(q), cirq.Z(q), cirq.M(q)),
+    ]
 
     executor = Executor(execute)
 
     results = executor.evaluate(circuits)
-    assert np.allclose(results, [1, 2])
+    assert np.allclose(results, [2, 3])
 
     if execute is executor_serial_unique:
         assert executor.calls_to_executor == 2
     else:
         assert executor.calls_to_executor == 1
 
     assert executor.executed_circuits == circuits
-    assert executor.quantum_results == [1, 2]
-
-
-@pytest.mark.parametrize(
-    "execute",
-    [
-        executor_batched,
-        executor_batched_unique,
-        executor_serial_unique,
-        executor_serial_typed,
-        executor_serial,
-        executor_pyquil_batched,
-    ],
-)
-@pytest.mark.parametrize(
-    "obs",
-    [
-        PauliString("X"),
-        PauliString("XZ"),
-        PauliString("Z"),
-    ],
-)
-def test_executor_observable_compatibility_check(execute, obs):
-    q = cirq.LineQubit(0)
-    circuits = [cirq.Circuit(cirq.X(q)), cirq.Circuit(cirq.H(q), cirq.Z(q))]
-
-    executor = Executor(execute)
-
-    with pytest.raises(ValueError, match="are not compatible"):
-        executor.evaluate(circuits, obs)
+    assert executor.quantum_results == [2, 3]
 
 
 @pytest.mark.parametrize(
-    "execute", [executor_measurements, executor_measurements_batched]
+    "execute", [executor_measurements_typed, executor_measurements_batched]
 )
 def test_executor_evaluate_measurements(execute):
     obs = Observable(PauliString("Z"))
@@ -258,24 +241,24 @@ def test_executor_evaluate_measurements(execute):
     results = executor.evaluate(circuits, obs)
     assert np.allclose(results, [1, -1])
 
-    if execute is executor_measurements:
+    if execute is executor_measurements_typed:
         assert executor.calls_to_executor == 2
     else:
         assert executor.calls_to_executor == 1
 
     assert executor.executed_circuits[0] == circuits[0] + cirq.measure(q)
     assert executor.executed_circuits[1] == circuits[1] + cirq.measure(q)
-    assert executor.quantum_results[0] == executor_measurements(
+    assert executor.quantum_results[0] == executor_measurements_typed(
         circuits[0] + cirq.measure(q)
     )
-    assert executor.quantum_results[1] == executor_measurements(
+    assert executor.quantum_results[1] == executor_measurements_typed(
         circuits[1] + cirq.measure(q)
     )
     assert len(executor.quantum_results) == len(circuits)
 
 
 @pytest.mark.parametrize(
-    "execute", [executor_density_matrix, executor_density_matrix_batched]
+    "execute", [executor_density_matrix_typed, executor_density_matrix_batched]
 )
 def test_executor_evaluate_density_matrix(execute):
     obs = Observable(PauliString("Z"))
@@ -288,16 +271,80 @@ def test_executor_evaluate_density_matrix(execute):
     results = executor.evaluate(circuits, obs)
     assert np.allclose(results, [1, -1])
 
-    if execute is executor_density_matrix:
+    if execute is executor_density_matrix_typed:
         assert executor.calls_to_executor == 2
     else:
         assert executor.calls_to_executor == 1
 
     assert executor.executed_circuits == circuits
     assert np.allclose(
-        executor.quantum_results[0], executor_density_matrix(circuits[0])
+        executor.quantum_results[0], executor_density_matrix_typed(circuits[0])
     )
     assert np.allclose(
-        executor.quantum_results[1], executor_density_matrix(circuits[1])
+        executor.quantum_results[1], executor_density_matrix_typed(circuits[1])
     )
     assert len(executor.quantum_results) == len(circuits)
+
+
+def test_executor_float_with_observable_typed():
+    obs = Observable(PauliString("Z"))
+    q = cirq.LineQubit(0)
+    circuit = cirq.Circuit(cirq.X.on(q))
+    executor = Executor(executor_serial_typed)
+    with pytest.raises(
+        ValueError,
+        match="When using a float like result",
+    ):
+        executor.evaluate(circuit, obs)
+
+
+def test_executor_measurements_without_observable_typed():
+    q = cirq.LineQubit(0)
+    circuit = cirq.Circuit(cirq.X.on(q))
+    executor = Executor(executor_measurements_typed)
+    with pytest.raises(
+        ValueError,
+        match="When using a measurement, or bitstring, like result",
+    ):
+        executor.evaluate(circuit)
+
+
+def test_executor_density_matrix_without_observable_typed():
+    q = cirq.LineQubit(0)
+    circuit = cirq.Circuit(cirq.X.on(q))
+    executor = Executor(executor_density_matrix_typed)
+    with pytest.raises(
+        ValueError,
+        match="When using a density matrix like result",
+    ):
+        executor.evaluate(circuit)
+
+
+def test_executor_float_not_typed():
+    executor = Executor(executor_serial)
+    executor_typed = Executor(executor_serial_typed)
+    qcirc = QuantumCircuit(1)
+    qcirc.h(0)
+    assert executor.evaluate(qcirc) == executor_typed.evaluate(qcirc)
+
+
+def test_executor_density_matrix_not_typed():
+    obs = Observable(PauliString("Z"))
+    executor = Executor(executor_density_matrix)
+    executor_typed = Executor(executor_density_matrix_typed)
+    q = cirq.LineQubit(0)
+    circuit = cirq.Circuit(cirq.X.on(q))
+    assert np.allclose(
+        executor.evaluate(circuit, obs), executor_typed.evaluate(circuit, obs)
+    )
+
+
+def test_executor_measurements_not_typed():
+    obs = Observable(PauliString("Z"))
+    executor = Executor(executor_measurements)
+    executor_typed = Executor(executor_measurements_typed)
+    q = cirq.LineQubit(0)
+    circuit = cirq.Circuit(cirq.X.on(q))
+    assert executor.evaluate(circuit, obs) == executor_typed.evaluate(
+        circuit, obs
+    )