Mass composition of Telescope Array's surface detectors events using deep learning
-
92 views
-
1 likes
-
0 favorites
- uploaded July 6, 2021
Discussion timeslot (ZOOM-Meeting): 16. July 2021 - 18:00
ZOOM-Meeting URL: https://icrc2021.desy.de/pf_access_abstracts
Corresponding Session: https://icrc2021-venue.desy.de/channel/Presenter-Forum-1-Evening-All-Categories/48
Abstract:
"The mass composition of ultra-high-energy cosmic rays can be analyzed by employing deep neural networks. We present an improved version of such analysis for Telescope Array's surface detectors data. Our neural network was trained on a large Monte-Carlo dataset simulating the expected experimental data distribution, and then was applied to the actual experimental data. Systematic and model errors are discussed."
Authors: Ivan Kharuk | Mikhail Kuznetsov | Yana Zhezher | Grigory Rubtsov | Oleg Kalashev | For the Telescope Array Collaboration
Collaboration: Telescope Array
Indico-ID: 1148
Proceeding URL: https://pos.sissa.it/395/384
Categories:
Cosmic Ray Indirect, Scientific Contributions
Presenter:
Ivan Kharuk
