Direction Reconstruction using a CNN for GeV-Scale Neutrinos in IceCube
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 dense...
Main Authors: | , , , , , , , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/363257 https://dipot.ulb.ac.be/dspace/bitstream/2013/363257/3/ICRC2021_1054.pdf |
Summary: | 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. 0 SCOPUS: cp.p info:eu-repo/semantics/published |
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