The IceCube Neutrino Observatory observes neutrinos interacting deep within the South Pole ice. It consists of 5,160 digital optical modules, which are embedded within a cubic kilometer of ice, over depths of 1,450 m to 2,450 m. At the lower center of the array is the DeepCore subdetector. Its denser sensor configuration lowers the observable energy threshold to the GeV-scale, facilitating the study of atmospheric neutrino oscillations. The precise reconstruction of neutrino direction is critical in the measurements of oscillation parameters. This work presents a method to reconstruct the zenith angle of GeV-scale events in IceCube by using a convolutional neural network and compares the result to that of the current likelihood-based reconstruction algorithm.

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

Bernardini E.;Mancina S.;
2022

Abstract

The IceCube Neutrino Observatory observes neutrinos interacting deep within the South Pole ice. It consists of 5,160 digital optical modules, which are embedded within a cubic kilometer of ice, over depths of 1,450 m to 2,450 m. At the lower center of the array is the DeepCore subdetector. Its denser sensor configuration lowers the observable energy threshold to the GeV-scale, facilitating the study of atmospheric neutrino oscillations. The precise reconstruction of neutrino direction is critical in the measurements of oscillation parameters. This work presents a method to reconstruct the zenith angle of GeV-scale events in IceCube by using a convolutional neural network and compares the result to that of the current likelihood-based reconstruction algorithm.
2022
Proceedings of Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3503928
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