Electromagnetic shower identification in the SAND Calorimeter of the DUNE Near Detector

Cagnoli, Irene (2021) Electromagnetic shower identification in the SAND Calorimeter of the DUNE Near Detector. [Laurea magistrale], Università di Bologna, Corso di Studio in Physics [LM-DM270]
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Abstract

The Deep Underground Neutrino Experiment (DUNE) is a next generation, long-baseline accelerator experiment designed to significantly contribute to the study of neutrino oscillations with unprecedented level of sensitivity. It envisages to observe neutrinos from a high intensity wide-band neutrino beam with a Near Detector (ND) system at the Fermi National Accelerator Laboratory and a Far Detector (FD) at ∼ 1300 km from the beam source at Sanford Laboratory, in South Dakota. The System for on-Axis Neutrino Detection (SAND) is one of the three detectors of the ND complex which provides continuous on-axis beam monitoring and performs various physics measurements. This work concerns a study on the electromagnetic calorimeter (ECAL) capabilities of the SAND detector to perform e.m. showers and muon tracks discrimination. In particular, a new clustering algorithm to reconstruct events in the ECAL not exploiting at all Monte Carlo truth has been developed and studied for the first time. A multivariate analysis based on machine-learning techniques has been implemented to perform a classification of the clusters reconstructed by the clustering algorithm and study the capabilities in electromagnetic showers and muon tracks discrimination. The classification analysis is operated in two separated steps: (a) the multivariate methods are trained and validated using a dedicated dataset obtained by simulating particle guns of electrons and muons originated close to the ECAL; (b) the selected optimal classifiers are tested with simulated neutrino interactions in the SAND detector considering the case of a ν µ -dominated beam in neutrino mode. Finally, the calorimeter performance in discriminating electromagnetic showers from muons is preliminary evaluated in terms of the product of efficiency times the signal purity.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Cagnoli, Irene
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
NUCLEAR AND SUBNUCLEAR PHYSICS
Ordinamento Cds
DM270
Parole chiave
DUNE,neutrino,SAND,calorimeter,clustering algorithm,particle identification,multivariate analysis
Data di discussione della Tesi
24 Settembre 2021
URI

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