Discriminating sub-TeV gamma and hadron-induced showers through their footprints

Abstract

Gamma/hadron discrimination in ground-based gamma-ray observatories at the sub-TeV energy range is challenging as traditional muon-based methods become less effective at lower energies. This work explores a novel gamma/hadron discrimination method for Extensive Air Shower arrays that analyzes the shower signal footprint patterns using a state-of-the-art pre-trained Vision Transformer (ViT). The resilience of the method to background noise, such as atmospheric muons and low-energy proton showers, along with its adaptability to different zenith angles and array configurations, demonstrates its potential for application in current and future ground-based gamma-ray observatories.

13 pages, 13 figures

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Cited by in corpus (1)

• Enhancing Neutrino Reconstruction in Water-Cherenkov Air Shower Arrays Using Multi-Photosensors