Abstract

The neutrino has been a theorized particle since the early 1900’s but its elusive nature has made detecting, understanding, and characterizing it particularly difficult. Experiments to detect neutrinos aim to better discern how this Standard Model particle interacts with matter, its own unique properties, and its ties to the history of our universe. The MINVERvA collaboration studies scattering cross sections by using five different nuclear targets (water, carbon, iron, helium, and lead) to gain a wide array of data involving a range of interaction types. These precision measurements directly reduce the systematic uncertainties for larger neutrino experiments that search for neutrino oscillations (such as NOvA and DUNE). Through this thesis, we aim to study MINERvA data to estimate parameters needed to construct an experimental cross-section for neutral current (NC) elastic neutrino-proton scattering events. We examine events within the 100 MeV to 10 GeV energy range as this contains the highest probability for the desired interaction. We create criteria for differentiating between neutrino-proton versus neutron-proton events to construct a Python script for selecting eligible NC scattering events.

Library of Congress Subject Headings

Neutrino interactions--Detection; Database management; Python (Computer program language_

Publication Date

12-19-2022

Document Type

Thesis

Student Type

Graduate

Degree Name

Physics (MS)

Department, Program, or Center

School of Physics and Astronomy (COS)

Advisor

Aaron McGowan

Advisor/Committee Member

Moumita Das

Advisor/Committee Member

Sheth Nyibule

Campus

RIT – Main Campus

Plan Codes

PHYS-MS

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