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.
|Journal||Proceedings of Science|
|Publication status||Published - 2022 Mar 18|
|Event||37th International Cosmic Ray Conference, ICRC 2021 - Virtual, Berlin, Germany|
Duration: 2021 Jul 12 → 2021 Jul 23
Bibliographical noteFunding 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).
© Copyright owned by the author(s).
All Science Journal Classification (ASJC) codes