Speaker
Description
The combined fit of the energy spectrum and shower maximum depth distributions of ultra-high-energy cosmic rays, as measured at the Pierre Auger Observatory, can yield constraints on source parameters. These parameters include the maximum rigidity, the spectral index of the injected energy spectrum, and the initial mass composition. The relationship between the observables measured at Earth and the injection spectrum of homogeneously distributed sources can be modeled using 1-dimensional CRPropa3 simulations. For the inference of the parameters from the measured distributions, we apply a normalizing flow. We investigate the influence of higher event statistics of the depth of shower maximum distributions, which can be now extracted from the surface detector data of the Pierre Auger Observatory using deep learning. Our results indicate that the increased statistics lead to stronger constraints on the parameters. Moreover, the new dataset significantly enhances the analysis of experimental systematic effects.
