Study of neutron detector response and related systematic uncertainties in the NOvA oscillation analysis
Date
2023-12
Authors
Rabelhofer, Miranda Jean
Major Professor
Advisor
Sanchez, Mayly
Wetstein, Matt
Weinstein, Amanda
Whisnant, Kerry
Vary, James
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Abstract
NOvA is a long-baseline neutrino oscillation experiment that is comprised of two functionally identical detectors positioned 810km apart. One of the main goals of the experiment is to measure electron neutrino appearance and muon neutrino disappearance at the Far Detector (FD) using neutrinos originating from the NuMI Beam at Fermilab. NOvA uses these observations to constrain several neutrino oscillation parameters, such as the CP violating phase, the atmospheric mass squared difference, and the largest mixing angle.
Before oscillations can happen in the NOvA oscillation analysis, the Near Detector (ND) observes the pure muon neutrino or antineutrino NuMI beam. These observations provide us with a high-statistical probe into understanding any events that could mimic our signal at the FD. This background to the electron neutrino appearance signal at the FD has three main components: charged current muon neutrino, neutral current, and charged current electron neutrino events. To accurately predict the FD background events, NOvA uses three different methods to obtain a data-driven correction to the background components at the ND. These ND constraints are then used in a near-to-far extrapolation to better estimate the samples at the FD. In this dissertation, I will present details of a newly developed background constraint applicable to both the neutrino and antineutrino dominated modes of the NuMI beam. Additionally, a new extrapolation technique for estimating the FD muon neutrino disappearance is presented.
Similar to the backgrounds on the analysis, it is critical to understand the sources of systematic uncertainties to make precise measurements of the oscillation parameters and to make improvements for future analyses. One key systematic for the antineutrino measurements stems from a limited understanding of how neutrons interact in the NOvA detectors. This dissertation discusses new techniques for identifying neutron energy depositions in the NOvA detector including a robust algorithm which is efficient at selecting neutron-linked deposits and provides a relatively pure sample. A neural network trained to identify energy deposits from neutron interaction daughters is also discussed. These tools are used to make comparisons between several neutron interaction simulations. The information from these studies was used to create multiple new ways to estimate the systematic uncertainty due to the neutron model on the NOvA oscillation analysis, and one will be used in upcoming analyses.
Series Number
Journal Issue
Is Version Of
Versions
Series
Academic or Administrative Unit
Type
dissertation