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_
Department, Program, or Center
School of Physics and Astronomy (COS)
Genus, Amelia, "Establishing Parameters for Selecting Eligible Neutral Current Neutrino-Proton Elastic Scattering Events using MINERνA Detector Samples" (2022). Thesis. Rochester Institute of Technology. Accessed from
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