TensorQEC.jl
Tensor networks for quantum error correction.
Install / Use
/learn @nzy1997/TensorQEC.jlREADME
This package utilizes the tensor network to study the properties of quantum error correction (QEC).The main features include
- A collection of QEC codes, their stabilizer generators, and their encoding circuits,
- Code distance calculation with integer programming,
- Decoders: truth table, tensor network, integer programming, BPOSD, etc.
- Simulation backends: tensor network, clifford circuit, full amplitude simulation (with Yao.jl), etc.
Installation
TensorQEC is a <a href="https://julialang.org"> <img src="https://raw.githubusercontent.com/JuliaLang/julia-logo-graphics/master/images/julia.ico" width="16em"> Julia Language </a> package. To install TensorQEC, please <a href="https://docs.julialang.org/en/v1/manual/getting-started/">open Julia's interactive session (known as REPL)</a> and press the <kbd>]</kbd> key in the REPL to use the package mode, and then type:
</p>pkg> add TensorQEC
To update, just type up in the package mode.
Benchmark
Repository DecoderBenchmarks.jl is set up to compare the performance of different decoders in different packages.
Contribute
Suggestions and Comments in the Issues are welcome.
Contributions to the documentation are welcome. To build the documentation, please run:
make init init-docs # or make update-docs
make servedocs
