BibTeX

@article{2510.07454v1,
Author        = {Karla Tame-Narvaez and Aleksandra Ćiprijanović and Steven Gardiner and Giuseppe Cerati},
Title         = {Simulation-based inference for neutrino interaction model parameter
  tuning},
Eprint        = {2510.07454v1},
ArchivePrefix = {arXiv},
PrimaryClass  = {hep-ph},
Abstract      = {High-energy physics experiments studying neutrinos rely heavily on
simulations of their interactions with atomic nuclei. Limitations in the
theoretical understanding of these interactions typically necessitate ad hoc
tuning of simulation model parameters to data. Traditional tuning methods for
neutrino experiments have largely relied on simple algorithms for numerical
optimization. While adequate for the modest goals of initial efforts, the
complexity of future neutrino tuning campaigns is expected to increase
substantially, and new approaches will be needed to make progress. In this
paper, we examine the application of simulation-based inference (SBI) to the
neutrino interaction model tuning for the first time. Using a previous tuning
study performed by the MicroBooNE experiment as a test case, we find that our
SBI algorithm can correctly infer the tuned parameter values when confronted
with a mock data set generated according to the MicroBooNE procedure. This
initial proof-of-principle illustrates a promising new technique for
next-generation simulation tuning campaigns for the neutrino experimental
community.},
Year          = {2025},
Month         = {Oct},
Url           = {http://arxiv.org/abs/2510.07454v1},
File          = {2510.07454v1.pdf}
}