Dissemin is shutting down on January 1st, 2025

Published in

arXiv, 2021

DOI: 10.48550/arxiv.2107.02122

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021), 2021

DOI: 10.22323/1.395.1054

IOP Publishing, Journal of Instrumentation, 11(16), p. C11001, 2021

DOI: 10.1088/1748-0221/16/11/c11001

Links

Tools

Export citation

Search in Google Scholar

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

Journal article published in 2022 by IceCube, Julia Tjus ORCID, Rasha Abbasi, Markus Ackermann, Jenni Adams, Juanan A. Aguilar, M. Ahlers, Maryon Ahrens, S. Yu, Cyril Martin Alispach, Antonio Augusto Alves, Najia Moureen Binte Amin, Rui An, Karen Andeen, Tyler Anderson and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Question mark in circle
Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

Abstract The IceCube Neutrino Observatory is designed to observe neutrinos interacting deep within the South Pole ice sheet. It consists of 5160 digital optical modules, which are arrayed over a cubic kilometer from 1450 m to 2450 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 about 10 GeV 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 contribution, I will discuss a method to reconstruct the zenith angle of 10-GeV scale events in IceCube using a convolutional neural network and compare the result to that of the current likelihood-based reconstruction algorithm.