Exploring jets: substructure and flavour tagging in CMS and ATLAS
High Energy Physics - Experiment
2024-10-21 v1
Abstract
The identification and characterization of jets are crucial tasks for effectively probing fundamental particle interactions. The ATLAS and CMS experiments have developed cutting-edge techniques to improve jet identification and calibration, employing innovative approaches including advanced neural network architectures, attention-based mechanisms, and adversarial training. These proceedings provide a comprehensive review of the state-of-the-art methods employed by both collaborations, highlighting their similarities, unique strengths, and limitations through a comparative analysis.
Keywords
Cite
@article{arxiv.2410.14330,
title = {Exploring jets: substructure and flavour tagging in CMS and ATLAS},
author = {Andrea Malara},
journal= {arXiv preprint arXiv:2410.14330},
year = {2024}
}
Comments
6 pages, 10 figures, Contribution to 12th Edition of the Large Hadron Collider Physics Conference - LHCP2024, Submitted for publication on POS