A CNN predicts ln A from longitudinal shower profiles with bias under 0.4, resolution 1-1.5, and proton-iron merit factor 2.19, outperforming simpler ML models on shape parameters and remaining robust to hadronic model changes.
Aab, et al., Features of the Energy Spectrum of Cosmic Rays above 2.5×10 18 eV Using the Pierre Auger Observatory, Phys
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Prospects for Deep-Learning-Based Mass Reconstruction of Ultra-High-Energy Cosmic Rays using Simulated Air-Shower Profiles
A CNN predicts ln A from longitudinal shower profiles with bias under 0.4, resolution 1-1.5, and proton-iron merit factor 2.19, outperforming simpler ML models on shape parameters and remaining robust to hadronic model changes.