Observational analysis detects steady gamma-ray emission from the Crab Nebula, highlighting deep learning's advantage over cut-based methods.
The GRAPES-3 experiment, located at an altitude of 2200 metres in, Ooty, Tamil Nadu, India (11.4°N, 76.7°E, 2200 m a.s.l.), records extensive air showers in the TeV–PeV energy range using an array of 400 plastic scintillator detectors arranged in a hexagonal grid over an area of 25,000 m², along with a 560 m² muon detector made of proportional counters. The latter allows showers initiated by γ-rays to be distinguished from those originating in Cosmic Rays. In this work, we compare the performance of different classes of deep learning algorithms against standard cut-based selection techniques in isolating a sample of γ-ray initiated showers from data gathered between 2017 and 2022. We report on a search for steady emission from the Crab Nebula.
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Karthik et al. (2025) studied this question.
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