PreprintarXiv licencearXiv
Jevons' Paradox and Fast Generative Simulation for HEP: Why Realistic Benchmarking is Essential
Abstract
Simulation is a major computational expense in HEP, and calorimeter simulation in particular drives the overall energy cost of our physics analyses. Future detectors will contain more finely grained calorimeters than ever, and their data analyses will demand unprecedented simulated statistics. Fast generative models redefine what is possible, producing simulations 100 times more efficiently. This article addresses Jevons' paradox in our field and considers the importance of realistic metrics in achieving "true" efficiency.
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BibTeX
@misc{buss2026jevons,
title = {{Jevons' Paradox and Fast Generative Simulation for HEP: Why Realistic Benchmarking is Essential}},
author = {Thorsten Buss and Henry Day-Hall and Frank Gaede and Gregor Kasieczka and Katja Krüger and Anatolii Korol and Thomas Madlener and Peter McKeown and Martina Mozzanica and Lorenzo Valente},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.24306},
eprint = {2609.24306},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.24306},
}
RIS
TY - UNPB
TI - Jevons' Paradox and Fast Generative Simulation for HEP: Why Realistic Benchmarking is Essential
AU - Thorsten Buss
AU - Henry Day-Hall
AU - Frank Gaede
AU - Gregor Kasieczka
AU - Katja Krüger
AU - Anatolii Korol
AU - Thomas Madlener
AU - Peter McKeown
AU - Martina Mozzanica
AU - Lorenzo Valente
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2609.24306
UR - https://arxiv.org/abs/2609.24306
AB - Simulation is a major computational expense in HEP, and calorimeter simulation in particular drives the overall energy cost of our physics analyses. Future detectors will contain more finely grained calorimeters than ever, and their data analyses will demand unprecedented simulated statistics. Fast generative models redefine what is possible, producing simulations 100 times more efficiently. This article addresses Jevons' paradox in our field and considers the importance of realistic metrics in achieving "true" efficiency.
ER -