I. Kharuk (Avtor), R. U. Abbasi (Avtor), Y. Abe (Avtor), T. Abu-Zayyad (Avtor), M. Allen (Avtor), Yasuhiko Arai (Avtor), R. Arimura (Avtor), E. Barcikowski (Avtor), J. W. Belz (Avtor), D. R. Bergman (Avtor)

Povzetek

We report on the updated results on the search for photon-like-induced events in the data, collected by Telescope Array's Surface Detectors during the last 14 years. In order to search for photon-like-induced events, we trained a neural network on Monte-Carlo simulated data to distinguish between the proton-induced and photon-induced air showers. Both reconstructed composition-sensitive parameters and raw signals registered by the Surface Detectors are used as input data for the neural network. The classification threshold was optimized to provide the strongest possible constraint on the photons' flux.

Ključne besede

Telescope Array;indirect detection;surface detection;ground array;ultra-high energy;cosmic rays;photons;neural network;machine learning;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija: UNG - Univerza v Novi Gorici
UDK: 539.1
COBISS: 167662339 Povezava se bo odprla v novem oknu
ISSN: 1824-8039
Št. ogledov: 306
Št. prenosov: 5
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Vrsta dela (COBISS): Delo ni kategorizirano
Strani: str. 1-10
Čas izdaje: 2023
DOI: 10.22323/1.444.0324
ID: 21815689