English

RODEM Jet Datasets

High Energy Physics - Phenomenology 2024-08-22 v1

Abstract

We present the RODEM Jet Datasets, a comprehensive collection of simulated large-radius jets designed to support the development and evaluation of machine-learning algorithms in particle physics. These datasets encompass a diverse range of jet sources, including quark/gluon jets, jets from the decay of W bosons, top quarks, and heavy new-physics particles. The datasets provide detailed substructure information, including jet kinematics, constituent kinematics, and track displacement details, enabling a wide range of applications in jet tagging, anomaly detection, and generative modelling.

Keywords

Cite

@article{arxiv.2408.11616,
  title  = {RODEM Jet Datasets},
  author = {Knut Zoch and John Andrew Raine and Debajyoti Sengupta and Tobias Golling},
  journal= {arXiv preprint arXiv:2408.11616},
  year   = {2024}
}

Comments

The datasets are available on Zenodo at https://doi.org/10.5281/zenodo.12793616

R2 v1 2026-06-28T18:19:29.826Z