cudaq-qec


Namecudaq-qec JSON
Version 0.1.0 PyPI version JSON
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home_pageNone
SummaryAccelerated libraries for Quantum Error Correction built on CUDA-Q
upload_time2024-11-18 19:17:34
maintainerNVIDIA Corporation & Affiliates
docs_urlNone
authorNVIDIA Corporation & Affiliates
requires_python>=3.10
licenseNone
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            # CUDA-Q QEC Library

CUDA-Q QEC is a high-performance quantum error correction library 
that leverages NVIDIA GPUs to accelerate classical decoding and 
processing of quantum error correction codes. The library provides optimized 
implementations of common QEC tasks including syndrome extraction, 
decoding, and logical operation tracking.

**Note**: CUDA-Q QEC is currently only supported on Linux operating systems using
`x86_64` processors. CUDA-Q QEC does not require a GPU to use, but some 
components are GPU-accelerated.

## Features

- Fast syndrome extraction and processing on GPUs
- Common decoders for surface codes and other topological codes
- Real-time decoding capabilities for quantum feedback
- Integration with CUDA-Q quantum program execution

## Getting Started

For detailed documentation, tutorials, and API reference, visit the 
[CUDA-Q QEC Documentation](https://nvidia.github.io/cudaqx/components/qec/introduction.html).

## License

CUDA-Q QEC is an open source project. The source code is available on
[GitHub][github_link] and licensed under [Apache License
2.0](https://github.com/NVIDIA/cudaqx/blob/main/LICENSE). 

[github_link]: https://github.com/NVIDIA/cudaqx/tree/main/libs/qec
            

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    "description": "# CUDA-Q QEC Library\n\nCUDA-Q QEC is a high-performance quantum error correction library \nthat leverages NVIDIA GPUs to accelerate classical decoding and \nprocessing of quantum error correction codes. The library provides optimized \nimplementations of common QEC tasks including syndrome extraction, \ndecoding, and logical operation tracking.\n\n**Note**: CUDA-Q QEC is currently only supported on Linux operating systems using\n`x86_64` processors. CUDA-Q QEC does not require a GPU to use, but some \ncomponents are GPU-accelerated.\n\n## Features\n\n- Fast syndrome extraction and processing on GPUs\n- Common decoders for surface codes and other topological codes\n- Real-time decoding capabilities for quantum feedback\n- Integration with CUDA-Q quantum program execution\n\n## Getting Started\n\nFor detailed documentation, tutorials, and API reference, visit the \n[CUDA-Q QEC Documentation](https://nvidia.github.io/cudaqx/components/qec/introduction.html).\n\n## License\n\nCUDA-Q QEC is an open source project. The source code is available on\n[GitHub][github_link] and licensed under [Apache License\n2.0](https://github.com/NVIDIA/cudaqx/blob/main/LICENSE). \n\n[github_link]: https://github.com/NVIDIA/cudaqx/tree/main/libs/qec",
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