The Search For High Energy Tau Neutrinos With The IceCube Neutrino Detector
Open Access
Author:
Pankova, Daria
Graduate Program:
Physics
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
June 17, 2021
Committee Members:
Nitin Samarth, Program Head/Chair Douglas Cowen, Chair & Dissertation Advisor Stephane Coutu, Major Field Member Derek Fox, Outside Unit & Field Member Anna Stasto, Major Field Member
Keywords:
neutrino tau neutrinos IceCube physics machine learning CNN
Abstract:
Neutrinos are fundamental particles that have been studied by physicists extensively
over many decades, yet much about them remains unknown. We do know
that they come in three types or
avors (electron, muon and tau), and we have
observed that the tau
avor is the most elusive, being harder to produce and detect
due to the high mass of its associated tau lepton. The goal of this analysis is to
collect the largest number of astrophysical tau neutrinos to date.
The IceCube Collaboration has already made substantive progress with astrophysical
tau neutrinos. We have discovered two astrophysical tau neutrino
candidates and have excluded the possibility of there being no tau neutrinos at
2:8.
In this analysis of IceCube data we improve the tau neutrino event selection
eciency by roughly a factor of ve. This improvement is attained by lowering
the energy threshold at which we can positively identify tau neutrino interactions
through use of a new data representation coupled with modern machine learning
algorithms.
