Energy Reconstruction in Analysis of Cherenkov Telescopes Images in TAIGA Experiment Using Deep Learning Methods

Imaging Atmospheric Cherenkov Telescopes (IACT) of TAIGA astrophysical complex allow to observe high energy gamma radiation helping to study many astrophysical objects and processes. TAIGA-IACT enables us to select gamma quanta from the total cosmic radiation flux and recover their primary parameter...

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Veröffentlicht in:	arXiv.org 2022-11
Hauptverfasser:	Gres, E O, Kryukov, A P
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Cosmic rays Deep learning Direction of arrival Energy spectra Gamma ray telescopes Image processing Image reconstruction Machine learning Neural networks Parameterization Parameters Physics - High Energy Astrophysical Phenomena Physics - Instrumentation and Methods for Astrophysics Radiation Taiga & tundra Telescopes
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