Date of Award
Doctor of Philosophy (PhD)
cross-section, LArTPC, MicroBooNE, neutrino
Muon Decay-at-Rest (μDAR) produces electron-neutrinos (νe) in the 0 to 53 MeV energy range. The given range is especially interesting for its similarity to Supernovae-produced νe. The Deep Underground Neutrino Experiment (DUNE) has as one of its main goals to measure Supernovae neutrinos on the occasion of a Galactic Supernova burst. To optimize the chances of detection, a low-energy neutrino-LAr cross-section (XS) measurement is a piece of important information to have at hand. MicroBooNE presents a good opportunity to explore the low-energy ν-LAr detection and XS using the μDAR neutrinos and therefore develop the tools necessary for DUNE to interpret the results of a supernova neutrino detection. MicroBooNE is a LArTPC that has been collecting neutrino data since October 2015 from the Booster Neutrino Beam (BNB) and off-axis to the Neutrinos at the Main Injector (NuMI) beam, both copious sources of μDAR neutrinos. In this thesis, we present a first attempt to measure MeV-scale neutrinos in a LArTPC. To do that, we use specific MeV-scale reconstruction tools combined with other traditional reconstruction tools used in MicroBooNE. We discuss the tool’s performance, limitations, and provide suggestions on how to improve them. This analyzes looks for μDAR neutrino- argon charged current interactions in the NuMI Run1 data, that contains 2×1020 POT. We observed 9,176 signal candidates. The number of expected background events is 8,776, the majority from cosmic rays. We establish a XS upper limit of < σ >= 1.99 × 10−37cm2/Ar, which corresponds to 551.9 times the nominal prediction from MARLEY, the neutrino generator used in this work. Despite the lack of sensitivity, this work is the first of its kind and sets the foundation for future similar analysis in the future. In the conclusions, we discuss how this results can be further improved in MicroBooNE.
Benevides Rodrigues, Ohana, "Search for NuMI muDAR Electron Neutrinos in MicroBooNE" (2022). Dissertations - ALL. 1591.