Search for Neutrinoless Double Beta Decay with EXO-200 and the Application of Deep Learning to Detector Simulation

The EXO-200 detector is designed to search for the neutrinoless double beta decay (0νββ) of 136Xe. Such a decay, if observed, would demonstrate the Majorana nature of neutrino; set the mass scale of the neutrino sector; and demonstrate lepton number non-conservation. The EXO- 200 detector and its successor, nEXO, use liquid Xenon time projection technology to perform the search. One important performance parameter of the detector is its energy resolution. In the first part of this work, we review the analysis work to improve the energy resolution and the status of the 0νββ search. This includes a description of the advanced analysis techniques used to maximize the energy resolution with improved charge channels, calibration ,and more precise Light-Maps. The second part of this work presents the current state of deep learning efforts towards fast simulations of the scintillation signals using Wasserstein Generative Adversarial Network (GAN) algorithms.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Physics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Li, Shaolei

Contributors dc:contributor

• Yang, Liang
• Perdekamp, Matthias Grosse
• Draper, Patrick I
• MacDougall, Gregory

• Physics

Statement dc:rights

• Copyright 2022 Shaolei Li

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/115319

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F115319