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Compile members data into JSON file #740

Merged
merged 2 commits into from
Jul 3, 2024
Merged

Compile members data into JSON file #740

merged 2 commits into from
Jul 3, 2024

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frankharkins
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@frankharkins frankharkins commented Jul 3, 2024

Summary

  • Add script to generate members.json
  • Compile JSON on push to main and host with GitHub pages

Rather than committing the JSON file as we did in the past, this PR keeps it out of version control and hosts it with GitHub pages. The file should be accessible at https://qiskit.github.io/ecosystem/members-data.json. We'll want to keep the pages website around so we can redirect users.

We build the website in CI, so the tests will fail if there's an error compiling the JSON file.

Here's how the file looks:

{"members": [{"name": "Azure Quantum", "url": "https://github.com/microsoft/azure-quantum-python", "description": "Submit quantum jobs written in Q#, Qiskit, or Cirq to the Azure Quantum service.", "licence": "MIT license", "labels": [], "created_at": 1715084759.598566, "stars": 117, "group": "provider"}, {"name": "qiskit-classroom-converter", "url": "https://github.com/KMU-quantum-classroom/qiskit-classroom-converter", "description": "Convert quantum circuits, matrices, and bra-ket strings. This converter includes the following conversion functions: quantum circuit to bra-ket notation, quantum circuit to matrix, matrix to quantum circuit, bra-ket notation to matrix.", "licence": "Apache License 2.0", "labels": ["Converter"], "website": "https://github.com/KMU-quantum-classroom", "stars": 2, "group": "other"}, {"name": "caml_qiskit", "url": "https://github.com/dakk/caml_qiskit", "description": "OCaml wrapper for Qiskit quantum computing toolkit", "licence": "MIT license", "contact_info": "[email protected]", "labels": [], "stars": 9, "group": "other", "documentation": "https://dakk.github.io/caml_qiskit/"}, {"name": "Qiskit on IQM", "url": "https://github.com/iqm-finland/qiskit-on-iqm", "description": "Qiskit adapter for IQM's quantum computers.", "licence": "Apache 2.0", "labels": [], "created_at": 1715085233.375706, "stars": 17, "group": "provider"}, {"name": "Quantum Prototype Template", "url": "https://github.com/qiskit-community/quantum-prototype-template", "description": "A template repository for generating new quantum prototypes based on Qiskit.", "licence": "Apache License 2.0", "affiliations": "Qiskit Community", "labels": ["Productivity"], "stars": 40, "group": "other"}, {"name": "POVM Toolbox", "url": "https://github.com/qiskit-community/povm-toolbox", "description": "A toolbox for the implementation of positive operator-valued measures (POVMs).", "licence": "Apache License 2.0", "contact_info": "[email protected]", "alternatives": "_No response_", "affiliations": "_No response_", "labels": ["Quantum information"], "stars": 5, "group": "other", "documentation": "https://qiskit-community.github.io/povm-toolbox/"}, {"name": "Qiskit QEC", "url": "https://github.com/qiskit-community/qiskit-qec", "description": "For quantum error correction developers, experimentalists, and theorists.", "licence": "Apache 2.0", "labels": ["Algorithms", "Error correction", "Circuit"], "created_at": 1662992390.122591, "updated_at": 1662992390.122597, "stars": 74, "group": "other"}, {"name": "Qiskit Algorithms", "url": "https://github.com/qiskit-community/qiskit-algorithms", "description": "A library of quantum algorithms for near-term quantum devices with short-depth circuits.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "IBM Quantum", "labels": ["Algorithms"], "stars": 87, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-algorithms/"}, {"name": "Circuit Knitting Toolbox", "url": "https://github.com/Qiskit-Extensions/circuit-knitting-toolbox", "description": "Decompose large circuits into smaller, hardware-executable circuits, then use their results to reconstruct the original circuit's outcome. This toolbox includes entanglement forging, circuit knitting, and classical embedding.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "labels": ["Algorithms", "Circuit"], "created_at": 1670427445.884067, "updated_at": 1670427445.884068, "stars": 67, "group": "other", "documentation": "https://qiskit-extensions.github.io/circuit-knitting-toolbox/"}, {"name": "QiskitOpt.jl", "url": "https://github.com/psrenergy/QiskitOpt.jl", "description": "QiskitOpt.jl is a Julia package that exports a JuMP wrapper for qiskit-optimization.", "licence": "MIT license", "contact_info": "[email protected], [email protected], [email protected], [email protected], [email protected]", "affiliations": "@psrenergy and USRA", "labels": ["Algorithms", "Julia"], "created_at": 1673642669.650459, "updated_at": 1673642669.650464, "stars": 9, "group": "applications"}, {"name": "Variational Quantum Linear Solver Prototype", "url": "https://github.com/QuantumApplicationLab/vqls-prototype", "description": "The Variational Quantum Linear Solver (VQLS) uses an optimization approach to solve linear systems of equations. The vqls-prototype allows to easily setup and deploy a VQLS instance on different backends through the use of qiskit primitives and the runtime library.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "alternatives": "The prototype builds on the qiskit-textbook chapter and tutorial. The prototype allows to use the primitives and use different cost function and test circuits to optimize the parameters.", "affiliations": "Netherlands eScience Center @ Quantum Application Lab, Amsterdam NL", "labels": ["Algorithms", "Optimization"], "created_at": 1683906067.55753, "updated_at": 1683906067.557535, "stars": 10, "group": "applications"}, {"name": "Qiskit Nature", "url": "https://github.com/qiskit-community/qiskit-nature", "description": "Model and solve problems in physics, chemistry, material science, and biology by using quantum simulations.", "licence": "Apache 2.0", "labels": ["Algorithms", "Physics", "Chemistry"], "created_at": 1636403009.16708, "updated_at": 1636403009.167082, "stars": 278, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-nature/"}, {"name": "Qiskit Optimization", "url": "https://github.com/qiskit-community/qiskit-optimization", "description": "Model optimization problems, convert them between different representations, and solve them by using quantum optimization algorithms on simulators or systems.", "licence": "Apache 2.0", "labels": ["Algorithms", "Optimization"], "created_at": 1636403009.538761, "updated_at": 1636403009.538763, "stars": 214, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-optimization/"}, {"name": "Quantum Inspire SDK", "url": "https://github.com/QuTech-Delft/quantuminspire", "description": "This platform allows you to execute quantum algorithms using the cQASM language.", "licence": "Apache 2.0", "labels": ["Algorithms"], "created_at": 1678827878.401835, "updated_at": 1678827878.401836, "stars": 62, "group": "other"}, {"name": "Pennylane-Qiskit", "url": "https://github.com/PennyLaneAI/pennylane-qiskit", "description": "The PennyLane-Qiskit plugin integrates the Qiskit quantum computing framework with PennyLane's quantum machine learning capabilities.", "licence": "Apache 2.0", "labels": ["Converter"], "created_at": 1678827878.782751, "updated_at": 1678827878.782752, "stars": 170, "group": "other"}, {"name": "Mitiq", "url": "https://github.com/unitaryfund/mitiq", "description": "Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers.", "licence": "Apache 2.0", "labels": ["Error mitigation"], "created_at": 1678827878.932437, "updated_at": 1678827878.932437, "stars": 343, "group": "other"}, {"name": "qiskit-superstaq", "url": "https://github.com/Infleqtion/client-superstaq/tree/main/qiskit-superstaq", "description": "This package is used to access SuperstaQ via a Web API through Qiskit. Qiskit programmers can take advantage of the applications, pulse level optimizations, and write-once-target-all features of SuperstaQ with this package.", "licence": "Apache 2.0", "contact_info": "", "alternatives": "", "labels": ["Converter"], "created_at": 1678827878.760089, "updated_at": 1678827878.76009, "group": "provider"}, {"name": "QoptKIT", "url": "https://github.com/SOQCSAdmin/QoptKIT", "description": "Optical circuits in Qiskit. Translate Qiskit circuits to quantum-optical circuits made of phase shifters and beamsplitters, simulate the circuit, then translate the outcome back to a qubit encoding.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "National University of Ireland Maynooth", "labels": ["Circuit simulator"], "stars": 1, "group": "other", "documentation": "https://soqcsadmin.github.io/QoptKIT/"}, {"name": "qlasskit", "url": "https://github.com/dakk/qlasskit", "description": "Qlasskit is a Python library that allows quantum developers to write classical algorithms in pure Python and translate them into quantum circuits.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "The project is partially funded by the UnitaryFund microgrant.", "labels": ["Converter"], "website": "https://dakk.github.io/qlasskit/", "stars": 48, "group": "other"}, {"name": "pyRiemann-qiskit", "url": "https://github.com/pyRiemann/pyRiemann-qiskit", "description": "A library for supervised machine learning based on quantum computing and Riemannian geometry. The project is built on top of the Qiskit and pyRiemann projects and focuses on the classification of time series data.", "licence": "BSD 3-Clause \"New\" or \"Revised\" license", "contact_info": "[email protected]", "affiliations": "pyRiemann (https://github.com/pyRiemann)", "labels": ["Machine learning"], "stars": 21, "group": "applications", "documentation": "https://pyriemann-qiskit.readthedocs.io/"}, {"name": "Qiskit Nature + CP2K Embedding", "url": "https://github.com/mrossinek/qiskit-nature-cp2k", "description": "This project contains the utilities that are required for the communication between Qiskit Nature and CP2K.", "licence": "Apache License 2.0", "labels": ["Chemistry"], "stars": 1, "group": "applications", "reference_paper": "https://arxiv.org/abs/2404.18737"}, {"name": "dynacir", "url": "https://github.com/derek-wang-ibm/dynacir", "description": "Dynacir is a transpilation plugin for Qiskit that optimizes dynamic quantum circuits.", "licence": "Apache License 2.0", "affiliations": "IBM Quantum", "labels": [], "stars": 0, "group": "transpiler_plugin"}, {"name": "Qiskit Research", "url": "https://github.com/qiskit-community/qiskit-research", "description": "Run quantum computing research experiments by using Qiskit and IBM Quantum services, demonstrating best practices by example.", "licence": "Apache 2.0", "labels": ["Paper implementation"], "created_at": 1662992208.202283, "updated_at": 1662992208.20229, "stars": 64, "group": "other"}, {"name": "Qiskit Braket provider", "url": "https://github.com/qiskit-community/qiskit-braket-provider", "description": "Execute Qiskit programs on AWS quantum computing hardware devices through Amazon Braket.", "licence": "Apache 2.0", "labels": [], "created_at": 1715085130.096724, "stars": 56, "group": "provider"}, {"name": "dense-ev", "url": "https://github.com/atlytle/dense-ev", "description": "Implements expectation value measurements in Qiskit using optimal dense grouping. Dense-ev provides an improvement of ~2^m over naive grouping and (3/2)^m over qubit-wise commuting groups.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "University of Illinois at Urbana-Champaign", "labels": ["Paper implementation"], "stars": 9, "group": "other", "reference_paper": "https://arxiv.org/abs/2305.11847"}, {"name": "pytket-qiskit", "url": "https://github.com/CQCL/pytket-qiskit", "description": "An extension to Pytket (a python module for interfacing with CQC tket) that allows Pytket circuits to be run on IBM backends and simulators, as well as conversion to and from Qiskit representations.", "licence": "Apache 2.0", "labels": ["Converter"], "created_at": 1661869851.523229, "updated_at": 1661869851.523229, "stars": 13, "group": "other"}, {"name": "qiskit-symb", "url": "https://github.com/SimoneGasperini/qiskit-symb", "description": "Easy-to-use Python package designed to enable symbolic quantum computation in Qiskit. It provides the basic tools for the symbolic evaluation of statevectors, density matrices, and unitary operators directly created from parametric Qiskit quantum circuits. The implementation is based on the Sympy library as backend for symbolic expressions manipulation.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "labels": ["Quantum information", "Circuit simulator"], "created_at": 1680254616.930627, "updated_at": 1680254616.930632, "stars": 23, "group": "other"}, {"name": "Qiskit Scaleway", "url": "https://github.com/scaleway/qiskit-scaleway", "description": "A Python package to run quantum circuits on Scaleway infrastructure, providing access to simulators on powerful hardware (CPU and GPU).", "licence": "Apache License 2.0", "contact_info": "[email protected]", "labels": ["Circuit simulator", "OpenQASM"], "website": "https://www.scaleway.com", "stars": 2, "group": "provider", "documentation": "https://pypi.org/project/qiskit-scaleway/"}, {"name": "Quantum Kernel Training", "url": "https://github.com/qiskit-community/prototype-quantum-kernel-training", "description": "Train and use quantum kernels for machine learning. This toolkit is for researchers and practitioners looking to explore and apply these algorithms to their work.", "licence": "Apache 2.0", "contact_info": "", "alternatives": "", "labels": ["Prototype", "Machine learning"], "created_at": 1645480343.964777, "updated_at": 1645480343.964777, "stars": 39, "group": "applications"}, {"name": "mthree", "url": "https://github.com/Qiskit-Partners/mthree", "description": "Matrix-free Measurement Mitigation (M3). Reduce the effects of readout errors from noisy quantum hardware.", "licence": "Apache 2.0", "contact_info": "", "alternatives": "", "labels": ["IBM maintained", "Error mitigation"], "created_at": 1678827878.805163, "updated_at": 1678827878.805164, "stars": 34, "group": "other"}, {"name": "PurpleCaffeine", "url": "https://github.com/IceKhan13/purplecaffeine", "description": "Project is aimed to create simple general interface to track quantum experiments, store and search them in an easy way.", "licence": "Apache License 2.0", "affiliations": "QAMP", "labels": ["Productivity", "Jupyter notebook"], "created_at": 1688661859.080258, "updated_at": 1688661859.080264, "stars": 7, "group": "other", "documentation": "https://icekhan13.github.io/purplecaffeine/index.html"}, {"name": "Quantum MasterChef", "url": "https://github.com/shravanpatel30/Quantum-MasterChef", "description": "A unique and immersive quantum computing game that combines the excitement of culinary arts with the challenges of quantum mechanics to teach about qiskit and quantum computing.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "labels": ["Circuit", "Education", "Game"], "stars": 1, "group": "other"}, {"name": "Qiskit Rigetti Provider", "url": "https://github.com/rigetti/qiskit-rigetti", "description": "Rigetti Provider for Qiskit.", "licence": "Apache 2.0", "labels": [], "created_at": 1678827878.136911, "updated_at": 1678827878.136912, "stars": 8, "group": "provider"}, {"name": "quPython", "url": "https://github.com/frankharkins/quPython", "description": "Write quantum programs as Python functions instead of circuit objects. Create higher-level quantum data types and return measurement results as bool-like objects.", "licence": "MIT license", "contact_info": "[email protected]", "labels": ["Circuit", "Converter", "Productivity"], "stars": 4, "group": "other"}, {"name": "QPong", "url": "https://github.com/HuangJunye/QPong", "description": "A quantum version of the classic game Pong built with Qiskit and PyGame", "licence": "Apache 2.0", "contact_info": "[email protected]", "labels": ["Game"], "created_at": 1678827877.979398, "updated_at": 1678827877.979398, "stars": 119, "group": "other"}, {"name": "Qiskit Quantinuum provider", "url": "https://github.com/qiskit-community/qiskit-quantinuum-provider", "description": "Provider to access Quantinuum quantum devices.", "licence": "Apache 2.0", "labels": [], "created_at": 1715085347.688097, "stars": 22, "group": "provider"}, {"name": "Qiskit Qulacs", "url": "https://github.com/Gopal-Dahale/qiskit-qulacs", "description": "Qiskit-Qulacs allows users to execute Qiskit programs using Qulacs backend.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "Supported by the Unitary Fund microgrant program: https://unitary.fund/grants/", "labels": ["Circuit simulator", "Converter"], "stars": 8, "group": "provider", "documentation": "https://qiskit-qulacs.netlify.app/"}, {"name": "Qiskit SAT Synthesis", "url": "https://github.com/qiskit-community/qiskit-sat-synthesis", "description": "Synthesis plugins for Cliffords, linear functions, permutations, and more", "licence": "Apache License 2.0", "contact_info": "[email protected]", "alternatives": "There are other quantum circuit compilation tools that use SAT-solving to search for optimum circuits, for instance: MQT QMAP (https://github.com/cda-tum/mqt-qmap), and tweedledum (https://github.com/boschmitt/tweedledum).", "affiliations": "IBM", "labels": [], "stars": 2, "group": "transpiler_plugin"}, {"name": "TorchQuantum", "url": "https://github.com/mit-han-lab/torchquantum", "description": "A PyTorch-centric hybrid classical-quantum dynamic neural networks framework.", "licence": "Apache 2.0", "labels": ["Machine learning"], "created_at": 1678827878.611621, "updated_at": 1678827878.611622, "stars": 1224, "group": "applications"}, {"name": "Qiskit Experiments", "url": "https://github.com/Qiskit-Extensions/qiskit-experiments", "description": "Run characterizing, calibrating, and benchmarking experiments.", "licence": "Apache 2.0", "labels": ["IBM maintained", "Algorithms", "Hardware"], "created_at": 1661785302.25299, "updated_at": 1661785302.25299, "stars": 146, "group": "other", "documentation": "https://qiskit.org/ecosystem/experiments/"}, {"name": "zoose-codespace", "url": "https://github.com/ianhellstrom/zoose-codespace", "description": "GitHub Codespace template repository based on Zoose Quantum, a custom Docker image with everything included, so you can be up and running with any of the major quantum libraries (incl. Qiskit) with only two clicks! No installation required. Ideal for beginners or people who want to code quantum circuits on the go. Code quantum circuits straight in your browser with VSCode.", "licence": "MIT license", "contact_info": "ian \\[..at..\\] databaseline \\[..dot..\\] tech", "alternatives": "qBraid: commercial hosted notebooks", "labels": ["Jupyter notebook"], "created_at": 1670402642.907656, "updated_at": 1670402642.907662, "stars": 0, "group": "other"}, {"name": "Qiskit Dynamics", "url": "https://github.com/Qiskit-Extensions/qiskit-dynamics", "description": "Build, transform, and solve time-dependent quantum systems.", "licence": "Apache 2.0", "labels": ["IBM maintained", "Physics"], "created_at": 1628883441.121108, "updated_at": 1628883441.121111, "stars": 96, "group": "applications", "documentation": "https://qiskit.org/ecosystem/dynamics/"}, {"name": "Qiskit Finance", "url": "https://github.com/qiskit-community/qiskit-finance", "description": "This framework includes uncertainty components for stock/securities problems, Ising translators for portfolio optimizations, and data providers to source real or random data for finance experiments.", "licence": "Apache 2.0", "labels": ["Algorithms", "Finance"], "created_at": 1636403009.368607, "updated_at": 1636403009.368609, "stars": 218, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-finance/"}, {"name": "Qiskit Machine Learning", "url": "https://github.com/qiskit-community/qiskit-machine-learning", "description": "Use flexible building blocks, such as quantum kernels and neural networks, to create quantum machine learning algorithms.", "licence": "Apache 2.0", "labels": ["Algorithms", "Machine learning"], "created_at": 1636403010.012954, "updated_at": 1636403010.012956, "stars": 616, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-machine-learning/"}, {"name": "qiskit-qubit-reuse", "url": "https://github.com/qiskit-community/qiskit-qubit-reuse", "description": "A Qiskit transpiler stage plugin that reuses qubits through mid-circuit measurement and reset.", "licence": "Apache License 2.0", "affiliations": "IBM", "labels": ["Paper implementation"], "stars": 13, "group": "transpiler_plugin"}, {"name": "Qiskit IonQ Provider", "url": "https://github.com/Qiskit-Partners/qiskit-ionq", "description": "This project contains a provider that allows access to IonQ ion trap quantum systems.", "licence": "Apache 2.0", "contact_info": "", "alternatives": "", "labels": ["Partner"], "created_at": 1670427446.011674, "updated_at": 1670427446.011675, "stars": 41, "group": "provider"}, {"name": "qdao", "url": "https://github.com/Zhaoyilunnn/qdao", "description": "A lightweight framework to enable configurable memory consumption when simulating large quantum circuits.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "Institute of Computing Technology, Chinese Academy of Sciences.", "labels": ["Circuit simulator"], "stars": 7, "group": "other"}, {"name": "Qiskit Serverless", "url": "https://github.com/Qiskit/qiskit-serverless", "description": "Execute Qiskit programs as long-running jobs and distribute them across many CPUs, GPUs, and QPUs.", "licence": "Apache License 2.0", "contact_info": "[email protected]", "labels": ["Software development kit"], "created_at": 1670427445.627174, "updated_at": 1670427445.627175, "stars": 51, "group": "other"}, {"name": "Bosonic Qiskit", "url": "https://github.com/C2QA/bosonic-qiskit", "description": "NQI C2QA project to simulate hybrid boson-qubit systems within Qiskit.", "licence": "BSD 2-Clause Simplified or FreeBSD license", "labels": ["Physics"], "created_at": 1678827878.841977, "updated_at": 1678827878.841978, "stars": 43, "group": "applications"}, {"name": "Qiskit Aer", "url": "https://github.com/Qiskit/qiskit-aer", "description": "High-performance quantum computing simulators with realistic noise models.", "licence": "Apache 2.0", "labels": ["IBM maintained", "Circuit simulator"], "created_at": 1636403010.377695, "updated_at": 1636403010.377697, "stars": 461, "group": "other", "documentation": "https://qiskit.org/ecosystem/aer"}, {"name": "Qiskit Nature PySCF", "url": "https://github.com/qiskit-community/qiskit-nature-pyscf", "description": "A third-party integration plugin of Qiskit Nature and PySCF.", "licence": "Apache License 2.0", "labels": ["Chemistry"], "created_at": 1678827878.723733, "updated_at": 1678827878.723734, "stars": 18, "group": "applications", "documentation": "https://qiskit-community.github.io/qiskit-nature-pyscf/"}, {"name": "ffsim", "url": "https://github.com/qiskit-community/ffsim", "description": "ffsim is a software library for simulating fermionic quantum circuits that conserve particle number and the Z component of spin.", "licence": "Apache License 2.0", "affiliations": "IBM", "labels": ["Chemistry", "Circuit simulator", "IBM maintained", "Rust"], "website": "https://qiskit-community.github.io/ffsim/", "stars": 19, "group": "applications"}, {"name": "Alice & Bob Qiskit provider", "url": "https://github.com/Alice-Bob-SW/qiskit-alice-bob-provider", "description": "Access Alice & Bob QPUs and emulators using Qiskit.", "licence": "Apache 2.0", "labels": [], "created_at": 1715084994.136498, "stars": 19, "group": "provider"}, {"name": "Qiskit AQT Provider", "url": "https://github.com/qiskit-community/qiskit-aqt-provider", "description": "Qiskit provider for ion-trap quantum computers from Alpine Quantum Technologies (AQT).", "licence": "Apache License 2.0", "contact_info": "[email protected]", "affiliations": "Alpine Quantum Technologies GmbH", "labels": [], "website": "https://www.aqt.eu/qc-systems/", "stars": 27, "group": "provider", "documentation": "https://qiskit-community.github.io/qiskit-aqt-provider/"}, {"name": "OpenQASM", "url": "https://github.com/openqasm/openqasm", "description": "An imperative programming language for near-term quantum computing. Describe quantum programs by using the measurement-based quantum circuit model with support for classical feedforward flow control based on measurement outcomes.", "licence": "Apache 2.0", "affiliations": "OpenQASM specification contributors", "labels": ["OpenQASM"], "created_at": 1660223774.444544, "updated_at": 1660223774.44455, "website": "https://openqasm.com/", "stars": 1183, "group": "other"}, {"name": "qMuVi", "url": "https://github.com/garymooney/qmuvi", "description": "Convert circuits into audiovisual experiences, bridging the gap between complex quantum computations and human perception. Render music videos that reveal the evolution of quantum states, making quantum computing more intuitive and accessible.", "licence": "GNU Library or \"Lesser\" General Public License (LGPL)", "contact_info": "[email protected]", "affiliations": "The University of Melbourne", "labels": ["Converter", "Visualization", "Education"], "stars": 13, "group": "other", "documentation": "https://garymooney.github.io/qmuvi/"}, {"name": "qBraid", "url": "https://github.com/qBraid/qBraid", "description": "The qBraid-SDK is a Python toolkit for cross-framework abstraction, transpilation, and execution of quantum programs.", "licence": "GNU General Public License (GPL)", "contact_info": "[email protected]", "alternatives": "There are some alternatives to individual modules within the qBraid-SDK e.g. to execute a Qiskit circuit on an AWS device, you could use the qiskit-braket-provider. 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Closes #739

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Great idea to host it on GH Pages! It seems like we'll still be able to redirect the index page while preserving this new page: https://docs.github.com/en/contributing/writing-for-github-docs/configuring-redirects#configuring-external-redirects

We should experiment with a sample project before we push the new redirects live in however many weeks, to reduce the risk we accidentally redirect this new page

@frankharkins frankharkins merged commit c94994a into main Jul 3, 2024
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@frankharkins frankharkins deleted the FH/compile-json branch July 3, 2024 14:13
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