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oscarhiggott committed Jan 22, 2021
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![Continuous Integration](https://github.com/oscarhiggott/PyMatching/workflows/Continuous%20Integration/badge.svg)
[![codecov](https://codecov.io/gh/oscarhiggott/PyMatching/branch/master/graph/badge.svg)](https://codecov.io/gh/oscarhiggott/PyMatching)
[![docs](https://readthedocs.org/projects/pymatching/badge/?version=latest&style=plastic)](https://readthedocs.org/projects/pymatching/builds/)
[![PyPI version](https://badge.fury.io/py/PyMatching.svg)](https://badge.fury.io/py/PyMatching)
[![Unitary Fund](https://img.shields.io/badge/Supported%20By-UNITARY%20FUND-brightgreen.svg?style=for-the-badge)](http://unitary.fund)

PyMatching is a fast Python/C++ library for decoding quantum error correcting codes (QECC) using the Minimum Weight Perfect Matching (MWPM) decoder. PyMatching can decode codes for which each error generates a pair of syndrome defects (or only a single defect at a boundary). Codes that satisfy these properties include two-dimensional topological codes such as the [toric code](https://en.wikipedia.org/wiki/Toric_code), the [surface code](https://arxiv.org/abs/quant-ph/0110143) and [2D hyperbolic codes](https://arxiv.org/abs/1506.04029). PyMatching can handle boundaries, measurement errors and weighted edges in the matching graph. Since the core algorithms are written in C++, PyMatching is much faster than a pure Python NetworkX implementation.
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```
This is the recommended way to install PyMatching, since it does not require you to build the C++ extension. Note that PyMatching requires Python 3.6 or later.

If instead you would like to install PyMatching from source, clone the repository (using the `--recursive` flag to include the lib/pybind11 submodule), and then use `pip` to install:
If instead you would like to install PyMatching from source, clone the repository (using the `--recursive` flag to include the lib/pybind11 submodule) and then use `pip` to install:
```
git clone --recursive https://github.com/oscarhiggott/PyMatching.git
pip install -e ./PyMatching
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