Year: 2024
Type: conference-paper
Abstract: This dissertation presents a search for sterile neutrinos using Monte Carlo datasets and experimental data from the NOνA experiment.This work introduces novel machine learning techniques for energy reconstruction in neutral current events.A deep learning-based energy estimator was developed and integrated into the analysis framework.Using this new energy estimator, the sensitivity to sterile neutrino-induced oscillations is evaluated and presented.Furthermore, the dissertation explores potential methods for further improvement of the analysis.
DOI: 10.2172/2530131
Author: Don Wickremasinghe
Institution: Fermi National Accelerator Laboratory
Language: English
Topic: Neutrino Physics Research
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4408348977