DOE OSTI · 2566622
Data-driven model validation for neutrino-nucleus cross section measurements
Abstract
Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.
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Abratenko, P. [Tufts University], Alterkait, O. [Tufts University], Andrade Aldana, D. [Illinois Institute of Technology (IIT)], Arellano, L. [The University of Manchester], Asaadi, J. [University of Texas], Ashkenazi, A. [Tel Aviv University], Balasubramanian, S. [Fermi National Accelerator Laboratory (FNAL)], Baller, B. [Fermi National Accelerator Laboratory (FNAL)], Barnard, A. [University of Oxford], Barr, G. [University of Oxford], Barrow, D. [University of Oxford], Barrow, J. [University of Minnesota], Basque, V. [Fermi National Accelerator Laboratory (FNAL)], Bateman, J. [The University of Manchester], Benevides Rodrigues, O. [Illinois Institute of Technology (IIT)], Berkman, S. [Michigan State University], Bhanderi, A. [The University of Manchester], Bhat, A. [University of Chicago], Bhattacharya, M. [Fermi National Accelerator Laboratory (FNAL)], Bishai, M. [Brookhaven National Laboratory (BNL)], Blake, A. [Lancaster University], Bogart, B. [University of Michigan, Ann Arbor] (ORCID:0000000305588934), Bolton, T. [Kansas State University (KSU)], Brunetti, M. B. [University of Warwick], Camilleri, L. [Columbia University], Cao, Y. [The University of Manchester], Caratelli, D. [University of California], Cavanna, F. [Fermi National Accelerator Laboratory (FNAL)], Cerati, G. [Fermi National Accelerator Laboratory (FNAL)], Chappell, A. [University of Warwick], Chen, Y. [SLAC National Accelerator Laboratory], Conrad, J. M. [Massachusetts Institute of Technology (MIT)], Convery, M. [SLAC National Accelerator Laboratory], Cooper-Troendle, L. [University of Pittsburgh], Crespo-Anadón, J. I. [Centro de Investigaciones Energéticas], Cross, R. [University of Warwick], Del Tutto, M. [Fermi National Accelerator Laboratory (FNAL)], Dennis, S. R. [University of Cambridge], Detje, P. [University of Cambridge], Diurba, R. [Universität Bern], Djurcic, Z. [Argonne National Laboratory (ANL)], Duffy, K. [University of Oxford], Dytman, S. [University of Pittsburgh], Eberly, B. [University of Southern Maine], Englezos, P. [Rutgers University], Ereditato, A. [University of Chicago; Fermi National Accelerator Laboratory (FNAL)], Evans, J. J. [The University of Manchester], Fang, C. [University of California], Foreman, W. [Illinois Institute of Technology (IIT); Los Alamos National Laboratory (LANL)], Fleming, B. T. [University of Chicago], Franco, D. [University of Chicago], Furmanski, A. P. [University of Minnesota], Gao, F. [University of California], Garcia-Gamez, D. [Universidad de Granada], Gardiner, S. [Fermi National Accelerator Laboratory (FNAL)], Ge, G. [Columbia University], Gollapinni, S. [Los Alamos National Laboratory (LANL)], Gramellini, E. [The University of Manchester], Green, P. [University of Oxford], Greenlee, H. [Fermi National Accelerator Laboratory (FNAL)], Gu, L. [Lancaster University], Gu, W. [Brookhaven National Laboratory (BNL)], Guenette, R. [The University of Manchester], Guzowski, P. [The University of Manchester], Hagaman, L. [University of Chicago], Handley, M. D. [University of Cambridge], Hen, O. [Massachusetts Institute of Technology (MIT)], Hilgenberg, C. [University of Minnesota], Horton-Smith, G. A. [Kansas State University (KSU)], Imani, Z. [Tufts University], Irwin, B. [University of Minnesota], Ismail, M. S. [University of Pittsburgh], James, C. [Fermi National Accelerator Laboratory (FNAL)], Ji, X. [Nankai University], Jo, J. H. [Brookhaven National Laboratory (BNL)], Johnson, R. A. [University of Cincinnati], Jwa, Y.-J. [Columbia University], Kalra, D. [Columbia University], Karagiorgi, G. [Columbia University], Ketchum, W. [Fermi National Accelerator Laboratory (FNAL)], Kirby, M. [Brookhaven National Laboratory (BNL)], Kobilarcik, T. [Fermi National Accelerator Laboratory (FNAL)], Lane, N. [The University of Manchester], Li, J.-Y. [University of Edinburgh], Li, Y. [Brookhaven National Laboratory (BNL)], Lin, K. [Rutgers University], Littlejohn, B. R. [Illinois Institute of Technology (IIT)], Liu, L. [Fermi National Accelerator Laboratory (FNAL)], Louis, W. C. [Los Alamos National Laboratory (LANL)], Luo, X. [University of California], Mahmud, T. [Lancaster University], Mariani, C. [Center for Neutrino Physics], Marsden, D. [The University of Manchester], Marshall, J. [University of Warwick], Martinez, N. [Kansas State University (KSU)], Martinez Caicedo, D. A. [South Dakota School of Mines and Technology (SDSMT)], Martynenko, S. [Brookhaven National Laboratory (BNL)], Mastbaum, A. [Rutgers University], Mawby, I. [Lancaster University], McConkey, N. [Queen Mary University of London]. 2025-05-15. Data-driven model validation for neutrino-nucleus cross section measurements. https://doi.org/10.1103/physrevd.111.092010
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