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A belief propagation decoder for low density parity check (LDPC) codes

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LDPC

This module provides a suite of tools for building and benmarking low density parity check (LDPC) codes. Features include functions for mod2 (binary) arithmatic and a fast implementation of the belief propagation decoder.

Documentation

The full documentation can be found here.

Installation from PyPi (recommended method)

Installtion from PyPi requires Python>=3.8. To install via pip, run:

pip install -U ldpc

Installation (from source)

Installation from source requires Python>=3.6 and a local C compiler (eg. 'gcc' in Linux or 'clang' in Windows). The LDPC package can then be installed by running:

git clone https://github.com/quantumgizmos/ldpc.git
cd ldpc
pip install -e ldpc

Dependencies

This package makes use of the mod2sparse data structure from Radford Neal's Software for Low Density Parity Check Codes C package.

Attribution

If you use this software in your research please cite as follows:

@software{Roffe_LDPC_Python_tools_2022,
author = {Roffe, Joschka},
title = {{LDPC: Python tools for low density parity check codes}},
url = {https://pypi.org/project/ldpc/},
year = {2022}
}

If you have used the BP+OSD class for quantum error correction, please also cite the following paper:

@article{roffe_decoding_2020,
   title={Decoding across the quantum low-density parity-check code landscape},
   volume={2},
   ISSN={2643-1564},
   url={http://dx.doi.org/10.1103/PhysRevResearch.2.043423},
   DOI={10.1103/physrevresearch.2.043423},
   number={4},
   journal={Physical Review Research},
   publisher={American Physical Society (APS)},
   author={Roffe, Joschka and White, David R. and Burton, Simon and Campbell, Earl},
   year={2020},
   month={Dec}
}

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  • Cython 37.0%
  • C 30.5%
  • Python 25.8%
  • Julia 6.7%