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| Microsoft Quantum Development Kit | |
|---|---|
| Name | Microsoft Quantum Development Kit |
| Developer | Microsoft |
| Initial release | 2017 |
| Latest release | 2024 |
| Programming languages | Q#, Python, C# |
| Platforms | Windows, macOS, Linux |
| License | MIT, proprietary components |
Microsoft Quantum Development Kit is a software development suite for quantum computing created by Microsoft Research and Microsoft. It provides a programming language, compilers, simulators, libraries, and tooling for developing and testing quantum algorithms on classical hardware and for deployment to quantum hardware research platforms. The kit is aimed at researchers, developers, and educators working on quantum algorithms, quantum chemistry, optimization, and quantum information science.
The Quantum Development Kit originates from efforts within Microsoft Research and integrates with Azure initiatives, reflecting collaborations across IBM Research, Google Research, Rigetti Computing, IonQ, and academic groups at MIT, Caltech, Harvard University, University of Oxford, University of Cambridge, ETH Zurich, University of Waterloo, Perimeter Institute, University of Chicago, Stanford University, Princeton University, University of California, Berkeley, UC Berkeley, University of Toronto, National University of Singapore, Tsinghua University, Peking University, Max Planck Society, Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, Oak Ridge National Laboratory, Argonne National Laboratory, NASA, DARPA, European Commission quantum initiatives, and consortia such as QED-C and Quantum Economic Development Consortium. The kit positions itself amid quantum software ecosystems like Qiskit, Cirq, Forest (Rigetti), OpenFermion, and ProjectQ.
Key components include the Q# language compiler, the QDK libraries, quantum chemistry libraries, numerics libraries, and simulators. The package ties into Visual Studio, Visual Studio Code, Azure Quantum, GitHub, Azure DevOps, Jupyter Notebook, Anaconda, Conda Forge, PyPI, NuGet, and package managers to distribute artifacts. It interoperates with toolchains from LLVM, .NET Foundation, Mono, CPython, IPython, Docker, Kubernetes, CMake, Bazel, and continuous integration systems used by organizations like Travis CI, CircleCI, Jenkins, and GitLab CI.
The primary language is Q#, developed alongside researchers and engineers from Microsoft Research and informed by programming languages research from groups at Carnegie Mellon University, EPFL, Ecole Polytechnique, Cornell University, Columbia University, Yale University, University of Maryland, University of British Columbia, and Singapore University of Technology and Design. Q# integrates with classical host languages including Python and C#, enabling hybrid algorithms similar to approaches in Variational Quantum Eigensolver research and frameworks used by IBM and Google. The programming model supports quantum operations, adjoint and controlled functors, type system features influenced by work at Harvard University and MIT CSAIL, and standard libraries for quantum chemistry and numerics drawing on methods from NWChem, PySCF, Psi4, Gaussian (software), and algorithms like Shor's algorithm, Grover's algorithm, Quantum phase estimation, Variational quantum eigensolver, and Quantum approximate optimization algorithm.
Tooling integrates with Visual Studio, Visual Studio Code, JupyterLab, and GitHub Codespaces and supports debugging, tracing, and performance profiling. Integration touches ecosystems surrounding Azure Machine Learning, Azure DevOps, PowerShell, Bash, and identity services like Azure Active Directory. Collaborative workflows intersect with projects at IEEE, ACM, SIAM, APS, Royal Society, National Science Foundation, and standardization efforts like ISO and W3C where software interoperability is relevant.
The kit includes full-state simulators, sparse simulators, and resource-estimation tools for fault-tolerant circuits, comparable to simulators developed by IBM Research, Google AI Quantum, Rigetti Computing, Quantinuum, Honeywell Quantum Solutions, and academic teams at University of Innsbruck and University of Sydney. Emulation and noise modeling enable studies related to error mitigation and quantum error correction codes from groups at Caltech, MIT Lincoln Laboratory, University of Illinois Urbana–Champaign, TUDelft, University of Bristol, and University of Geneva. Performance engineering leverages contributions from Intel, AMD, NVIDIA, ARM Limited, and HPC centers such as Argonne National Laboratory and Oak Ridge National Laboratory.
Users apply the kit to quantum algorithms in cryptanalysis research tied to RSA, Elliptic-curve cryptography, and post-quantum cryptography discourse in venues like NIST standardization programs and the Crypto (conference), to quantum chemistry problems explored at Caltech, MPI for Quantum Optics, Lawrence Livermore National Laboratory, and industrial partners like BASF, Bayer, Volkswagen, Airbus, Siemens, Goldman Sachs, JP Morgan, Accenture, and Deloitte. Optimization use cases draw on connections to Microsoft Research Cambridge operations research teams, collaborations with D-Wave Systems in annealing contexts, and logistics studies relevant to UPS and Maersk. Educational deployments appear in courses at MIT, Stanford University, University of Cambridge, ETH Zurich, and summer schools such as Qiskit Camp adaptations.
Development began in the mid-2010s within Microsoft Research with public announcements and releases around 2017, aligning with the emergence of quantum hardware demonstrated by Google, IBM, IonQ, Rigetti, and Quantinuum. Roadmaps and research papers were presented at conferences like QIP, ICML, NeurIPS, CPC (Computer Physics Communications), PLDI, POPL, SIGPLAN, APS March Meeting, TQC, and symposia hosted by Royal Society and IEEE Quantum Week. The project has seen contributions from collaborators at Cambridge Quantum Computing (now merged into Quantinuum), startups spun out of University of Oxford, and partnerships with cloud providers such as Amazon Web Services and Google Cloud for comparative research.
The toolkit is distributed through package managers like NuGet and PyPI with core components under open-source licenses (including MIT) and some integrations provided under Microsoft's proprietary terms via Azure Quantum service agreements. Academic and commercial users engage under terms referenced in Microsoft's documentation and enterprise contracts often negotiated alongside cloud consumption agreements with Azure.
Category:Quantum computing software