Air Shower Reconstruction using Deep Learning with the HAWC Observatory

The High-Altitude Water Cherenkov (HAWC) Observatory observes gamma rays with energies from 300 GeV to above 100 TeV. For each gamma-ray event, HAWC reconstructs the incident angle by using the timing information of the photomultiplier tubes triggered by the air shower particles. We investigate the use of Deep Learning to improve the angular resolution of HAWC. We train a Vision Transformer with simulated data and compare the performance to the current HAWC reconstruction.