Exploring Reconstructed Proton and Muon Distributions from Simulated Neutrino Interactions in LArTPC
Session Number
PHYS 01
Advisor(s)
Zelimir Djurcic, Argonne National Laboratory
Discipline
Physical Science
Start Date
17-4-2025 10:45 AM
End Date
17-4-2025 11:00 AM
Abstract
The main objective of this project is to study neutrino interaction in the Liquid Argon Time Projection Chamber (LArTPC), mainly those between muon neutrinos and argon atoms, producing final state particles in the detector. Event simulation software based on GENIE and GIANT4 are used to simulate the neutrino interactions that take place in the ArgonCube 2x2 Demonstrator, the novel type of LArTPC for the Deep Underground Neutrino Experiment (DUNE). These interactions will then be reconstructed and identified using SPINE which uses reconstruction-based machine-learning techniques. From these data sets, we observe the final state particles and characterize their energy using Python application code. We demonstrate these observations on a special case, νμ +n→p+μ−, of muon and proton final states as it allows for more simple energy reconstruction. By observing track lengths and interaction angles of these particles, we can understand important features of energy deposits by protons and muons to determine the total energy of the incoming neutrino. The precise measurement of energy is ultimately required for the test of CP violations in the neutrino oscillation equation. These observations will aid the preparations for the future Deep Underground Neutrino Experiment (DUNE) set to start in the next decade.
Exploring Reconstructed Proton and Muon Distributions from Simulated Neutrino Interactions in LArTPC
The main objective of this project is to study neutrino interaction in the Liquid Argon Time Projection Chamber (LArTPC), mainly those between muon neutrinos and argon atoms, producing final state particles in the detector. Event simulation software based on GENIE and GIANT4 are used to simulate the neutrino interactions that take place in the ArgonCube 2x2 Demonstrator, the novel type of LArTPC for the Deep Underground Neutrino Experiment (DUNE). These interactions will then be reconstructed and identified using SPINE which uses reconstruction-based machine-learning techniques. From these data sets, we observe the final state particles and characterize their energy using Python application code. We demonstrate these observations on a special case, νμ +n→p+μ−, of muon and proton final states as it allows for more simple energy reconstruction. By observing track lengths and interaction angles of these particles, we can understand important features of energy deposits by protons and muons to determine the total energy of the incoming neutrino. The precise measurement of energy is ultimately required for the test of CP violations in the neutrino oscillation equation. These observations will aid the preparations for the future Deep Underground Neutrino Experiment (DUNE) set to start in the next decade.