Inference of the Mass Composition of Cosmic Rays with Energies from 10^{18.5} to 10^{20} eV Using the Pierre Auger Observatory and Deep Learning.

We present measurements of the atmospheric depth of the shower maximum X_{max}, inferred for the first time on an event-by-event level using the surface detector of the Pierre Auger Observatory. Using deep learning, we were able to extend measurements of the X_{max} distributions up to energies of 100 EeV (10^{20}  eV), not yet revealed by current measurements, providing new insights into the mass composition of cosmic rays at extreme energies. Gaining a 10-fold increase in statistics compared to the fluorescence detector data, we find evidence that the rate of change of the average X_{max} with the logarithm of energy features three breaks at 6.5±0.6(stat)±1(syst)  EeV, 11±2(stat)±1(syst)  EeV, and 31±5(stat)±3(syst)  EeV, in the vicinity to the three prominent features (ankle, instep, suppression) of the cosmic-ray flux. The energy evolution of the mean and standard deviation of the measured X_{max} distributions indicates that the mass composition becomes increasingly heavier and purer, thus being incompatible with a large fraction of light nuclei between 50 and 100 EeV.