Improving Neutrino-Nuclei Interaction Models: Recommendations and Case Studies on Peelle's Pertinent Puzzle
Abstract
Improving the modeling of neutrino-nuclei interactions using data-driven methods is crucial for high-precision neutrino oscillation experiments. This paper investigates Peelle's Pertinent Puzzle (PPP) in the context of neutrino measurements, a longstanding challenge to fitting theoretical models to experimental data. Inconsistencies in data-model comparisons hinder efforts to enhance the accuracy and reliability of model predictions. We analyze various sources contributing to these inconsistencies and propose strategies to address them, supported by practical case studies. We advocate for incorporating model fitting exercises as a standard practice in cross section publications to enhance the robustness of results. We use a common analysis framework to explore PPP-related challenges with MicroBooNE and T2K data in an unified manner. Our findings offer valuable insights for improving the accuracy and reliability of neutrino-nuclei interaction models, particularly by systematically tuning models using data.
Keywords
Cite
@article{arxiv.2509.17945,
title = {Improving Neutrino-Nuclei Interaction Models: Recommendations and Case Studies on Peelle's Pertinent Puzzle},
author = {S. Abe and L. Aliaga-Soplin and J. Barrow and L. Bathe-Peters and B. Bogart and L. Cooper-Troendle and R. Diurba and S. Dytman and S. Gardiner and L. Hagaman and M. S. Ismail and J. Isaacson and J. Kim and L. Liu and J. McKean and N. Nayak and A. Papadopoulou and L. Pickering and X. Qian and K. Skwarczynski and J. Tena Vidal and J. Wolfs},
journal= {arXiv preprint arXiv:2509.17945},
year = {2025}
}