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Efficient Monte Carlo event generation for neutrino-nucleus exclusive cross sections

Mathias El Baz1,*, Federico Sánchez1, Natalie Jachowicz2, Kajetan Niewczas2, Ashish Kumar Jha2, and Alexis Nikolakopoulos3,4

  • *Contact author: mathias.elbaz@unige.ch
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Phys. Rev. D 111, 113001 – Published 6 June, 2025

DOI: https://doi.org/10.1103/v7sz-vn3b

Abstract

Modern neutrino-nucleus cross section computations need to incorporate sophisticated nuclear models to achieve greater predictive precision. However, the computational complexity of these advanced models often limits their practicality for experimental analyses. To address this challenge, we introduce a new Monte Carlo method utilizing normalizing flows to generate surrogate cross sections that closely approximate those of the original model while significantly reducing computational overhead. As a case study, we built a Monte Carlo event generator for the neutrino-nucleus cross section model developed by the Ghent group. This model employs a Hartree-Fock procedure to establish a quantum mechanical framework in which both the bound and scattering nucleon states are solutions to the mean-field nuclear potential. The surrogate cross sections generated by our method demonstrate excellent accuracy with a relative effective sample size of more than 98.4%, providing a computationally efficient alternative to traditional Monte Carlo sampling methods for differential cross sections.

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Phys. Rev. D 111, 113001– Published 6 June, 2025
  • Received 28 February 2025
  • Accepted 20 May 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

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