Welcome to qujax’s documentation!

qujax is a JAX-based Python library for the classical simulation of quantum circuits. It is designed to be simple, fast and flexible.

It follows a functional programming design by translating circuits into pure functions. This allows qujax to seamlessly and directly interface with JAX, enabling direct access to its powerful automatic differentiation tools, just-in-time compiler, vectorization capabilities, GPU/TPU integration and growing ecosystem of packages.

If you are new to the library, we recommend that you head to the Getting started section of the documentation. More advanced use-cases, including the training of parameterised quantum circuits, can be found in Examples.

The source code can be found on GitHub. The pytket-qujax extension can be used to translate a tket circuit directly into qujax.

Important note: qujax circuit parameters are expressed in units of \(\pi\) (e.g. in the range \([0,2]\) as opposed to \([0, 2\pi]\)).

Install

qujax is hosted on PyPI and can be installed with

pip install qujax

Cite

If you have used qujax in your code or research, we kindly ask that you cite it. You can use the following BibTeX entry for this:

@article{qujax2023,
  author = {Duffield, Samuel and Matos, Gabriel and Johannsen, Melf},
  doi = {10.21105/joss.05504},
  journal = {Journal of Open Source Software},
  month = sep,
  number = {89},
  pages = {5504},
  title = {{qujax: Simulating quantum circuits with JAX}},
  url = {https://joss.theoj.org/papers/10.21105/joss.05504},
  volume = {8},
  year = {2023}
}

Contents

Documentation:

API Reference: