Neutrino Direction Reconstruction using a CNN for GeV-Scale Neutrinos in IceCube

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  • uploaded July 8, 2021

Discussion timeslot (ZOOM-Meeting): 15. July 2021 - 18:00
ZOOM-Meeting URL: https://desy.zoom.us/j/91999581729
ZOOM-Meeting ID: 91999581729
ZOOM-Meeting Passcode: ICRC2021
Corresponding Session: https://icrc2021-venue.desy.de/channel/37-Reconstruction-amp-Analysis-Techniques-NU/126
Live-Stream URL: https://icrc2021-venue.desy.de/livestream/Discussion-05/6

Abstract:
'The IceCube Neutrino Observatory is designed to observe neutrinos interacting deep within the South Pole ice. It consists of 5,160 digital optical modules, which are arrayed over a cubic kilometer from 1,450 m to 2,450 m depth. At the lower center of the array is the DeepCore subdetector. It has a denser configuration which lowers the observable energy threshold to the GeV scale and creates the opportunity to study neutrino oscillations with low energy atmospheric neutrinos. A precise reconstruction of neutrino direction is critical in the measurements of oscillation parameters. In this poster, I will present a method to reconstruct the zenith angle of GeV-scale events in IceCube by using a convolutional neural network (CNN) and compare the result to that of the current likelihood-based reconstruction algorithm.'

Authors: Shiqi Yu | For the IceCube Collaboration
Collaboration: IceCube

Indico-ID: 647
Proceeding URL: https://pos.sissa.it/395/1054

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Shiqi Yu


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