Investigations of Photon-Hadron Separation at the Pierre Auger Observatory using Monte Carlo Simulations

Cosmic ray detectors like the 3000 km2 surface array of the Pierre Auger Observatory are capable of observing high-energy photons in the range of 1018 to 1020 eV if the flux is sufficiently high. Since the mean free path of the photons increases with energy in the ultra-high energy range, extragalactic sources can be probed up to distances of few Mpc. However, no clear candidates for ultra-high energy photons have been identified yet, so simulations must be used to study typical trigger patterns and observables for discriminating photons from hadrons.

Neural networks show promise of improved discriminating variables but require the training data to be very well understood. In contrast to hadron showers, photon-induced showers are expected to penetrate deeper in the atmosphere and have a steeper lateral distribution function, since the secondary particles almost exclusively belong to the electromagnetic component. Therefore, a number of elements in the the existing simulation and reconstruction chain, which has been developed and tuned for hadron-induced showers, need to be revisited for the case of ultra-high energy photons. In this contribution, we examine the parameters used to define how particle thinning in Corsika shower simulations is done and discuss implications for classical and machine learning based shower reconstruction algorithms.