PoS - Proceedings of Science
Volume 395 - 37th International Cosmic Ray Conference (ICRC2021) - CRI - Cosmic Ray Indirect
Telescope Array Surface Detector Energy and Arrival Direction Estimation Using Deep Learning
O. Kalashev*, D. Ivanov, M. Kuznetsov, G. Rubtsov, T. Sako, Y. Tsunesada, Y. Zhezher and  On behalf of the Telescope Array collaboration
Full text: pdf
Pre-published on: July 08, 2021
Published on: March 18, 2022
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.
DOI: https://doi.org/10.22323/1.395.0252
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.