Selection of numu Events for the MicroBooNE Deep Learning Low Energy Excess Analysis

UNSPECIFIED (2018) Selection of numu Events for the MicroBooNE Deep Learning Low Energy Excess Analysis. Other. UNSPECIFIED.

Abstract

MicroBooNE is a large liquid argon time projection chamber (LArTPC) on Fermilab’s Booster Neutrino Beam (BNB). A main goal of MicroBooNE is to search for the low energy excess (LEE) of electron like events seen by MiniBooNE. Using νµ interactions to constrain νe systematics is a common approach in oscillation experiments, we will adopt it here as well. This takes adantage of the high statistics νµ data and known correlations between electron and muon neutrino fluxes and cross sections. This note provides an overview of the selection of events with one reconstructed muon and one reconstructed proton in (µ1p) in MicroBooNE using a Deep Learning based reconstruction. We then present comparisons between data on our simulated neutrino interaction predictions for some important kinematic distributions. We find that in a sample of data corresponding to 4× 1019 POT, that the data and simulation agree well in shape.