Author ORCID Identifier

https://orcid.org/0009-0003-0658-9549

Date Available

5-6-2025

Year of Publication

2025

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy (PhD)

College

Arts and Sciences

Department/School/Program

Physics and Astronomy

Faculty

Bradley Plaster

Faculty

Anatoly Dymarsky

Abstract

The Ultracold Neutron Asymmetry+ (UCNA+) experiment at the Los Alamos Neu- tron Science Center (LANSCE) Ultracold Neutron source is an upgrade of the UCNA experiment, designed to measure the neutron beta decay asymmetry parameter, A 0 , with a precision of less than 0.2% using polarized ultracold neutrons (UCN). Neutron beta decay is governed by the weak interaction, and a precise measurement of A 0 provides a determination of the axial-vector to vector coupling ratio, λ = gA /gV . When combined with a measurement of the neutron lifetime, this allows the extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix element Vud exclusively from neutron decay. A high-precision determination of Vud is critical for testing CKM unitarity, a requirement under the Standard Model. In this dissertation, we provide an overview of neutron beta decay asymmetry experiments and discuss the upgrades to be implemented in the UCNA+ experiment. The improvements are projected to substantially mitigate systematic uncertainties, particularly those arising from elec- tron backscattering, as well as energy calibration and angular effects, which were important sources of systematic uncertainty in UCNA. Using GEANT4 simulations, we conducted a detailed investigation of the impact of experimental conditions, such as foils, dead layers, and detector thresholds, with the goal of reducing the systematic effects in UCNA+ as compared to UCNA.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2025.59

Funding Information

This work was supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under Award Number DE-SC0014622.

Download

Included in

Nuclear Commons

Share

COinS