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Advancing Tools for Simulation-Based Inference

H Bahl, V Bresó, G De Crescenzo, T Plehn - arXiv preprint arXiv …, 2024 - arxiv.org
Neuroscience paper hep-ph Suggest

… We study the benefit of modern simulation-based inference to constrain particle interactions at the LHC. We explore ways to incorporate known physics structures into …

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BibTeX

@article{2410.07315v3,
Author        = {Henning Bahl and Victor Bresó and Giovanni De Crescenzo and Tilman Plehn},
Title         = {Advancing Tools for Simulation-Based Inference},
Eprint        = {2410.07315v3},
DOI           = {10.21468/SciPostPhysCore.8.3.060},
ArchivePrefix = {arXiv},
PrimaryClass  = {hep-ph},
Abstract      = {We study the benefit of modern simulation-based inference to constrain
particle interactions at the LHC. We explore ways to incorporate known physics
structures into likelihood estimation, specifically morphing-aware estimation
and derivative learning. Technically, we introduce a new and more efficient
smearing algorithm, illustrate how uncertainties can be approximated through
repulsive ensembles, and show how equivariant networks can improve likelihood
estimation. After illustrating these aspects for a toy model, we target
di-boson production at the LHC and find that our improvements significantly
increase numerical control and stability.},
Year          = {2024},
Month         = {Oct},
Note          = {SciPost Phys. Core 8, 060 (2025)},
Url           = {http://arxiv.org/abs/2410.07315v3},
File          = {2410.07315v3.pdf}
}

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