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Bibliographic Details
Main Authors: Ragoni, Simone, Seger, Janet
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2602.10692
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author Ragoni, Simone
Seger, Janet
author_facet Ragoni, Simone
Seger, Janet
contents We present a fast surrogate for the Equivalent Photon Approximation (EPA) flux in ultraperipheral collisions (UPCs), based on a Bayesian neural network (BNN) trained over analytical flux integrals with an iterative procedure focused on regions of high relative uncertainties to minimise the number of integrations. The surrogate propagates experimentally available uncertainties on the neutron skin thickness and surface diffuseness. Once trained, this surrogate technique brings an estimated gain of two orders of magnitude in CPU time. The implementation provides a modular framework for rapidly propagating updated nuclear priors and assessing uncertainties for photon flux in future UPC analyses.
format Preprint
id arxiv_https___arxiv_org_abs_2602_10692
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A fast Bayesian surrogate for the photon flux in ultra-peripheral collisions
Ragoni, Simone
Seger, Janet
High Energy Physics - Phenomenology
We present a fast surrogate for the Equivalent Photon Approximation (EPA) flux in ultraperipheral collisions (UPCs), based on a Bayesian neural network (BNN) trained over analytical flux integrals with an iterative procedure focused on regions of high relative uncertainties to minimise the number of integrations. The surrogate propagates experimentally available uncertainties on the neutron skin thickness and surface diffuseness. Once trained, this surrogate technique brings an estimated gain of two orders of magnitude in CPU time. The implementation provides a modular framework for rapidly propagating updated nuclear priors and assessing uncertainties for photon flux in future UPC analyses.
title A fast Bayesian surrogate for the photon flux in ultra-peripheral collisions
topic High Energy Physics - Phenomenology
url https://arxiv.org/abs/2602.10692