Inference of the Mass Composition of Cosmic Rays with Energies from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mn>10</mml:mn><mml:mn>18.5</mml:mn></mml:msup></mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>20</mml:mn></mml:mrow></mml:msup><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>eV</mml:mi></mml:mrow></mml:math> Using the Pierre Auger Observatory and Deep Learning
Abstract
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.