Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Identification of electromagnetic and hadronic EASs using neural network for TAIGA scintillation detector array. / TAIGA Collaboration.
в: Journal of Instrumentation, Том 17, № 5, P05023, 01.05.2022.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Identification of electromagnetic and hadronic EASs using neural network for TAIGA scintillation detector array
AU - the TAIGA Collaboration
AU - Astapov, I.
AU - Bezyazeekov, P.
AU - Blank, M.
AU - Bonvech, E.
AU - Borodin, A.
AU - Brueckner, M.
AU - Budnev, N.
AU - Bulan, A.
AU - Chernov, D.
AU - Chiavassa, A.
AU - Dyachok, A.
AU - Gafarov, A.
AU - Garmash, A.
AU - Grebenyuk, V.
AU - Gress, E.
AU - Gress, O.
AU - Gress, T.
AU - Grinyuk, A.
AU - Grishin, O.
AU - Horns, D.
AU - Igoshin, A.
AU - Ilyushin, M.
AU - Ivanova, A. D.
AU - Ivanova, A. L.
AU - Kalmykov, N.
AU - Kindin, V.
AU - Kiryuhin, S.
AU - Kokoulin, R.
AU - Kompaniets, K.
AU - Korosteleva, E.
AU - Kozhin, V.
AU - Kravchenko, E.
AU - Kryukov, A.
AU - Kuotb, A.
AU - Kuzmichev, L.
AU - Lagutin, A.
AU - Lavrova, M.
AU - Lemeshev, Y.
AU - Lubsandorzhiev, B.
AU - Lubsandorzhiev, N.
AU - Lukanov, A.
AU - Lukyantsev, D.
AU - Malakhov, S.
AU - Mirgazov, R.
AU - Mirzoyan, R.
AU - Monkhoev, R.
AU - Osipova, E.
AU - Sokolov, A.
AU - Vaidyanathan, A.
AU - Vorobyov, V.
N1 - Publisher Copyright: © 2022 IOP Publishing Ltd and Sissa Medialab
PY - 2022/5/1
Y1 - 2022/5/1
N2 - The TAIGA experiment in Tunka valley is expanding the present scintillation detector array with new TAIGA-Muon detector stations. A simulation model was developed for optimization of the layout of the new stations and study of the identification performance of the array. The extensive air showers (EASs) were simulated with the CORSIKA simulation tool, and the detector response was simulated with the GEANT4 package. EASs induced by gamma quanta or protons in the energy range from 1 PeV to 10 PeV and the zenith angle range from 0° to 45°, are used for these studies. For the identification of high energy extensive air showers, a method based on a neural network was suggested. With this method, the proton identification efficiency is more than 90%, while the gamma identification efficiency not less than 50%.
AB - The TAIGA experiment in Tunka valley is expanding the present scintillation detector array with new TAIGA-Muon detector stations. A simulation model was developed for optimization of the layout of the new stations and study of the identification performance of the array. The extensive air showers (EASs) were simulated with the CORSIKA simulation tool, and the detector response was simulated with the GEANT4 package. EASs induced by gamma quanta or protons in the energy range from 1 PeV to 10 PeV and the zenith angle range from 0° to 45°, are used for these studies. For the identification of high energy extensive air showers, a method based on a neural network was suggested. With this method, the proton identification efficiency is more than 90%, while the gamma identification efficiency not less than 50%.
KW - Data processing methods
KW - Detector modelling and simulations I (interaction of radiation with matter, interaction of photons with matter, interaction of hadrons with matter, etc)
KW - Particle identification methods
KW - Scintillators, scintillation and light emission processes (solid, gas and liquid scintillators)
UR - http://www.scopus.com/inward/record.url?scp=85130715126&partnerID=8YFLogxK
U2 - 10.1088/1748-0221/17/05/P05023
DO - 10.1088/1748-0221/17/05/P05023
M3 - Article
AN - SCOPUS:85130715126
VL - 17
JO - Journal of Instrumentation
JF - Journal of Instrumentation
SN - 1748-0221
IS - 5
M1 - P05023
ER -
ID: 36188263