Generalised Dynamic Radius Jets for Robust Collider Analyses
Abstract
Jets and their reconstructions play a central role in precision measurements and searches for new physics at hadron colliders. Conventional jet clustering algorithms employ a fixed radius parameter, which may not optimally describe events containing jets of varying characteristic sizes. Building on the recently proposed dynamic radius jet clustering framework, we construct several substructure-inspired dynamic radius prescriptions based on jet angularities and energy correlation functions. A detailed study of these algorithms is performed, including detector effects within the Delphes framework and in the presence of high pileup corresponding to an average of 150 interactions per event, with pileup contamination mitigated using the PUPPI algorithm. The performance of the proposed algorithms is compared with that of the standard anti-kt algorithm in boosted Vj (V=W±,Z) and tj events against dijet backgrounds. Using jet substructure observables and multivariate analysis based on boosted decision trees, we find that the dynamic radius algorithms lead to improved reconstruction of boosted heavy-particle jets and achieve better signal-background discrimination compared to the conventional fixed radius anti-kt clustering.
Related
- Probabilistic Energy-Based Neural Networks for Uncertainty-Aware Collider Data Analyses
- Generalised quantum Stein's lemma more robust than ever
- The shadow radius lower bound is more robust than the photon sphere radius lower bound in n-dimensional Einstein gravity
- Generalised Fluctuating Dynamic Density-Functional Theory: Derivation and Applications
- Robust acoustic representation of Japanese vowels under phonation variability using dynamic spectral analysis
BibTeX
@misc{de2026generalised,
title = {{Generalised Dynamic Radius Jets for Robust Collider Analyses}},
author = {Songshaptak De and Tousik Samui and Ritesh K. Singh},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.29862},
eprint = {2609.29862},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.29862},
}
RIS
TY - UNPB
TI - Generalised Dynamic Radius Jets for Robust Collider Analyses
AU - Songshaptak De
AU - Tousik Samui
AU - Ritesh K. Singh
PY - 2026
DA - 2026/09/24
PB - arXiv
DO - 10.48550/arxiv.2609.29862
UR - https://arxiv.org/abs/2609.29862
AB - Jets and their reconstructions play a central role in precision measurements and searches for new physics at hadron colliders. Conventional jet clustering algorithms employ a fixed radius parameter, which may not optimally describe events containing jets of varying characteristic sizes. Building on the recently proposed dynamic radius jet clustering framework, we construct several substructure-inspired dynamic radius prescriptions based on jet angularities and energy correlation functions. A detailed study of these algorithms is performed, including detector effects within the Delphes framework and in the presence of high pileup corresponding to an average of 150 interactions per event, with pileup contamination mitigated using the PUPPI algorithm. The performance of the proposed algorithms is compared with that of the standard anti-k_t algorithm in boosted Vj (V=W^±,Z) and tj events against dijet backgrounds. Using jet substructure observables and multivariate analysis based on boosted decision trees, we find that the dynamic radius algorithms lead to improved reconstruction of boosted heavy-particle jets and achieve better signal-background discrimination compared to the conventional fixed radius anti-k_t clustering.
ER -