Data-driven Model Validation For Neutrino Cross Section Measurements

by Lee Hagaman (student@uchicago.edu)

Thursday 21 Nov 2024, 15:00 → 17:00 US/Eastern

Room 2-160

Neutrino-nucleus cross section measurements are often performed using event topologies which have complex detector efficiencies and smearings, and non-negligible backgrounds. Therefore, the use of a neutrino event generator is required in order to estimate these factors before unfolding a cross section measurement, and this inevitably leads to model dependence of the extracted cross section. To reduce this model dependence, it is common to validate the unfolding using fake data sets produced by different event generators, but this method has limitations. In this seminar, I will describe data-driven model validation techniques and how we use them to address model dependence in the MicroBooNE experiment.

lhagaman_bnl_model_validation.pdf