NVIDIA

NVIDIA/cuda-quantum

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

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README.md

# Welcome to the CUDA-Q repository

The CUDA-Q Platform for hybrid quantum-classical computers enables integration
and programming of quantum processing units (QPUs), GPUs, and CPUs in one
system. This repository contains the source code for all C++ and Python tools
provided by the CUDA-Q toolkit, including the `nvq++` compiler, the CUDA-Q
runtime, as well as a selection of integrated CPU and GPU backends for rapid
application development and testing.

## Getting Started

To learn more about how to work with CUDA-Q, please take a look at the [CUDA-Q
Documentation][cuda_quantum_docs]. The page also contains [installation
instructions][official_install] for officially released packages.

If you would like to install the latest iteration under development in this
repository and/or add your own modifications, take a look at the [latest
packages][github_packages] deployed on the GitHub Container Registry. For more
information about building CUDA-Q from source, see [these
instructions](./Building.md).

[cuda_quantum_docs]: https://nvidia.github.io/cuda-quantum/latest
[official_install]: https://nvidia.github.io/cuda-quantum/latest/using/quick_start.html#install-cuda-q
[github_packages]:
    https://github.com/orgs/NVIDIA/packages?repo_name=cuda-quantum

## Research Preview: Pulse-Level Programming

CUDA-Q pulse is a new research-preview package for programming at the pulse
level. It provides a Python kernel DSL, pulse and operator dialects, compiler
passes, and an experimental GPU execution path. Because it is a research
preview, its APIs and behavior may change incompatibly or be removed without
notice, and it is not a product-supported CUDA-Q feature.

See the [CUDA-Q pulse README][pulse_readme] for a quick example, build
instructions, and the current scope and limitations.

[pulse_readme]: https://github.com/NVIDIA/cuda-quantum/blob/feature/pulse/pulse/README.md

## Contributing

There are many ways in which you can get involved with CUDA-Q. If you are
interested in developing quantum applications with CUDA-Q, this repository is a
great place to get started! For more information about contributing to the
CUDA-Q platform, please take a look at [Contributing.md](./Contributing.md).

## License

The code in this repository is licensed under [Apache License 2.0](./LICENSE).

Contributing a pull request to this repository requires accepting the
Contributor License Agreement (CLA) declaring that you have the right to, and
actually do, grant us the rights to use your contribution. A CLA-bot will
automatically determine whether you need to provide a CLA and decorate the PR
appropriately. Simply follow the instructions provided by the bot. You will only
need to do this once.

## Feedback

Please let us know your feedback and ideas for the CUDA-Q platform in the
[Discussions][cuda_quantum_discussions] tab of this repository, or file an
[issue][cuda_quantum_issues]. To report security concerns or [Code of
Conduct](./Code_of_Conduct.md) violations, please reach out to
[cuda-quantum@nvidia.com](mailto:cuda-quantum@nvidia.com).

[cuda_quantum_discussions]: https://github.com/NVIDIA/cuda-quantum/discussions
[cuda_quantum_issues]: https://github.com/NVIDIA/cuda-quantum/issues

Repository info

Default branch: main
Latest version: 0.16.0
Created: 15/03/2023
Last activity: 04/11/2026
License: Apache-2.0
Open issues: 565
Watchers: 22

Topics

cpp hacktoberfest python quantum quantum-algorithms quantum-computing quantum-machine-learning quantum-programming-language unitaryhack

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