lgatr 1.1.0

Lorentz-Equivariant Geometric Algebra Transformer for High-Energy Physics

Lorentz-Equivariant Geometric Algebra Transformer

This repository contains a standalone implementation of the Lorentz-Equivariant Geometric Algebra Transformer (L-GATr) by Jonas Spinner, Víctor Bresó, Pim de Haan, Tilman Plehn, Huilin Qu, Jesse Thaler, and Johann Brehmer. L-GATr uses spacetime geometric algebra representations to construct Lorentz-equivariant layers and combines them into a transformer architecture. You can read more about L-GATr in the following two papers and in the L-GATr documentation:

• Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics (ML audience)
• A Lorentz-Equivariant Transformer for All of the LHC (HEP audience)

Installation

You can either install the latest release using pip

pip install lgatr

or clone the repository and install the package in dev mode

git clone https://github.com/heidelberg-hepml/lgatr.git
cd lgatr
pip install -e .

How to use L-GATr

Please have a look at our example notebooks for how to use LGATr and ConditionalLGATr.

Features

• L-GATr encoder and decoder as LGATr and ConditionalLGATr
• Additional attention backends, installation via pip install lgatr[xformers_attention] and pip install lgatr[flex_attention]
• Support for torch's automatic mixed precision; critical operations are performed in float32
• Interface to the geometric algebra: Embedding and extracting multivectors; spurions for symmetry breaking at the input level
• Many hyperparameters to play with, organized via the SelfAttentionConfig, CrossAttentionConfig, MLPConfig and LGATRConfig objects

Examples

• https://github.com/spinjo/weaver-core/blob/lgatr/weaver/nn/model/LGATr.py: L-GATr in the CMS boosted object tagging library weaver
• https://github.com/heidelberg-hepml/lorentz-gatr: Original LGATr implementation used for the papers

Let us know if you use lgatr, so we can add your repo to the list!

Citation

If you find this code useful in your research, please cite the following papers

@article{Brehmer:2024yqw,
    author = "Brehmer, Johann and Bres\'o, V\'\i{}ctor and de Haan, Pim and Plehn, Tilman and Qu, Huilin and Spinner, Jonas and Thaler, Jesse",
    title = "{A Lorentz-Equivariant Transformer for All of the LHC}",
    eprint = "2411.00446",
    archivePrefix = "arXiv",
    primaryClass = "hep-ph",
    reportNumber = "MIT-CTP/5802",
    month = "11",
    year = "2024"
}
@inproceedings{spinner2025lorentz,
  title={Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics},
  author={Spinner, Jonas and Bres{\'o}, Victor and De Haan, Pim and Plehn, Tilman and Thaler, Jesse and Brehmer, Johann},
  booktitle={Advances in Neural Information Processing Systems},
  year={2024},
  volume={37},
  eprint = {2405.14806},
  url = {https://arxiv.org/abs/2405.14806}
}
@inproceedings{brehmer2023geometric,
  title = {Geometric Algebra Transformer},
  author = {Brehmer, Johann and de Haan, Pim and Behrends, S{\"o}nke and Cohen, Taco},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2023},
  volume = {36},
  eprint = {2305.18415},
  url = {https://arxiv.org/abs/2305.18415},
}