cudaq-qec-cu13 0.5.0.post1

Accelerated libraries for Quantum Error Correction built on CUDA-Q

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 or aarch64/arm64 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

Optional Dependencies

Some decoders require additional dependencies to operate. You can install them with

• pip install cudaq-qec[tensor-network-decoder] for the Tensor Network Decoder
• pip install cudaq-qec[trt-decoder] for the TensorRT Decoder

Getting Started

For detailed documentation, tutorials, and API reference, visit the CUDA-Q QEC Documentation.

License

Most components of CUDA-Q QEC are open source. The source code is available on GitHub and licensed under Apache License 2.0.

The libcudaq-qec-nv-qldpc-decoder.so library (distributed with CUDA-Q QEC) is closed source and is subject to the NVIDIA Software License Agreement