Welcome to Cheetah’s documentation!¶

Cheetah is a particle tracking accelerator we built specifically to speed up the training of reinforcement learning models.

GitHub repository: https://github.com/desy-ml/cheetah

Paper: https://arxiv.org/abs/2401.05815

Installation¶

Simply install Cheetah from PyPI by running the following command.

pip install cheetah-accelerator

Examples¶

We provide some examples to demonstrate some features of Cheetah and show how to use them. They provide a good entry point to using Cheetah, but they do not represent its full functionality. To move beyond the examples, please refer to the in-depth documentation. If you feel like other examples should be added, feel free to open an issue on GitHub.

Examples

Documentation¶

For more advanced usage, please refer to the in-depth documentation.

Documentation

Cite Cheetah¶

If you use Cheetah, please cite the following two papers:

@misc{kaiser2024cheetah,
  title         = {Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations},
  author        = {Kaiser, Jan and Xu, Chenran and Eichler, Annika and {Santamaria Garcia}, Andrea},
  year          = {2024},
  eprint        = {2401.05815},
  archiveprefix = {arXiv},
  primaryclass  = {physics.acc-ph}
}
@inproceedings{stein2022accelerating,
  title     = {Accelerating Linear Beam Dynamics Simulations for Machine Learning Applications},
  author    = {Stein, Oliver and Kaiser, Jan and Eichler, Annika},
  year      = {2022},
  booktitle = {Proceedings of the 13th International Particle Accelerator Conference}
}

For Developers¶

Activate your virtual environment. (Optional)

Install the cheetah package as editable

pip install -e .

We suggest installing pre-commit hooks to automatically conform with the code formatting in commits:

pip install pre-commit
pre-commit install