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Catalyst is an experimental package that enables just-in-time (JIT) compilation of hybrid quantum-classical programs.

Catalyst is currently under heavy development — if you have suggestions on the API or use-cases you'd like to be covered, please open an GitHub issue or reach out. We'd love to hear about how you're using the library, collaborate on development, or integrate additional devices and frontends.

Key Features

Overview

Catalyst currently consists of the following components:

In addition, we also provide a Python frontend for PennyLane and JAX:

Installation

Catalyst is officially supported on Linux (aarch64/arm64, x86_64) and macOS (aarch64/arm64, x86_64) platforms, and pre-built binaries are being distributed via the Python Package Index (PyPI) for Python versions 3.10 and higher. To install it, simply run the following pip command:

pip install pennylane-catalyst

Pre-built packages for Windows are not yet available, and comptability with Windows is untested and cannot be guaranteed. If you are using one of these platforms, please try out our Docker and Dev Container images described in the documentation or click this button:

Dev Container.

If you wish to contribute to Catalyst or develop against our runtime or compiler, instructions for building from source are also available.

Trying Catalyst with PennyLane

To get started using the Catalyst JIT compiler from Python, check out our quick start guide, as well as our various examples and tutorials in our documentation.

For an introduction to quantum computing and quantum machine learning, you can also visit the PennyLane website for tutorials, videos, and demonstrations.

Roadmap

To get the details right, we need your help — please send us your use cases by starting a conversation, or trying Catalyst out.

Contributing to Catalyst

We welcome contributions — simply fork the Catalyst repository, and then make a pull request containing your contribution.

We also encourage bug reports, suggestions for new features and enhancements.

Support

If you are having issues, please let us know by posting the issue on our GitHub issue tracker.

We also have a PennyLane discussion forum—come join the community and chat with the PennyLane team.

Note that we are committed to providing a friendly, safe, and welcoming environment for all. Please read and respect the Code of Conduct.

Authors

Catalyst is the work of many contributors.

If you are doing research using Catalyst, please cite our paper:

@article{
  Ittah2024,
  doi = {10.21105/joss.06720},
  url = {https://doi.org/10.21105/joss.06720},
  year = {2024},
  publisher = {The Open Journal},
  volume = {9},
  number = {99},
  pages = {6720},
  author = {David Ittah and Ali Asadi and Erick Ochoa Lopez and Sergei Mironov and Samuel Banning and Romain Moyard and Mai Jacob Peng and Josh Izaac},
  title = {Catalyst: a Python JIT compiler for auto-differentiable hybrid quantum programs},
  journal = {Journal of Open Source Software}
} 

License

Catalyst is free and open source, released under the Apache License, Version 2.0.