Telescope Array Surface Detector Energy and Arrival Direction Estimation Using Deep Learning

The Telescope Array Collaboration

Research output: Contribution to journalConference articlepeer-review

Abstract

A novel ultra-high-energy cosmic rays energy and arrival direction reconstruction method for Telescope Array surface detector is presented. The analysis is based on a deep convolutional neural network using detector signal time series as the input and the network is trained on a large Monte-Carlo dataset. This method is compared in terms of statistical and systematic energy and arrival direction determination errors with the standard Telescope Array surface detector event reconstruction procedure.

Original languageEnglish
Article number252
JournalProceedings of Science
Volume395
Publication statusPublished - 2022 Mar 18
Event37th International Cosmic Ray Conference, ICRC 2021 - Virtual, Berlin, Germany
Duration: 2021 Jul 122021 Jul 23

Bibliographical note

Funding Information:
The cluster of the Theoretical Division of INR RAS was used for the numerical part of the work. The development and application of the machine learning analysis method is supported by the Russian Science Foundation grant No. 17-72-20291 (INR).

Publisher Copyright:
© Copyright owned by the author(s).

All Science Journal Classification (ASJC) codes

  • General

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