November 29, 2021 to December 3, 2021
Virtual and IBS Science Culture Center, Daejeon, South Korea
Asia/Seoul timezone

Analyzing stereoscopic Cherenkov telescope images from TAIGA array using convolutional neural networks

contribution ID 777
Not scheduled
20m
Windmill (Gather.Town)

Windmill

Gather.Town

Poster Track 2: Data Analysis - Algorithms and Tools Posters: Windmill

Speaker

Stanislav Polyakov (Lomonosov Moscow State University, Skobeltsyn Institute of NUclear Physics (RU))

Description

We use convolutional neural networks (CNNs) to analyze monoscopic and stereoscopic images of extensive air showers registered by Cherenkov telescopes of the TAIGA experiment. The networks are trained and evaluated on Monte-Carlo simulated images to identify the type of the primary particle and to estimate the energy of the gamma rays. We compare the performance of the networks trained on monoscopic and stereoscopic images.

References

37th International Cosmic Ray Conference (ICRC 2021) https://pos.sissa.it/395/753/pdf

Speaker time zone Compatible with Europe

Primary authors

Alexander Kryukov (Lomonosov Moscow State University, Skobeltsyn Institute of NUclear Physics (RU)) Stanislav Polyakov (Lomonosov Moscow State University, Skobeltsyn Institute of NUclear Physics (RU)) Andrey Demichev (Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University)

Presentation materials