Karlsruhe 2024 – scientific programme

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T: Fachverband Teilchenphysik

T 36: Gamma astronomy 2

T 36.3: Talk

Tuesday, March 5, 2024, 16:30–16:45, Geb. 30.22: kl. HS A

Deep-Learning-Based Gamma/Hadron Separation in the Southern Wide-field Gamma-ray Observatory — •Martin Schneider, Jonas Glombitza, Christopher van Eldik, and Markus Pirke for the SWGO collaboration — ECAP, FAU Erlangen-Nürnberg

The Southern Wide-field Gamma-ray Observatory (SWGO) is a next-generation ground-based observatory in the R&D phase. It will feature a large array of water-Cherenkov detectors (WCD) at high elevations in South America, enabling gamma-ray observations at energies from ~100GeV up to the PeV region. The primary challenge in gamma-ray observations is the rejection of hadronic showers to ensure a high signal-to-noise ratio. Various tank designs and layouts are currently evaluated for their gamma/hadron separation capabilities. This talk will explore the application of a deep-learning-based classification algorithm that processes low-level station information via graph neural networks, demonstrating the effective operation across various configurations.

Keywords: SWGO; Gamma-ray Observations; Air Showers; Deep Learning; Graph Neural Networks