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.
HALIM, Adila Binti Abdul; CATALANI, Fernando; SOUZA, Vitor de; SANTOS, Edivaldo Moura; OLIVEIRA, Cainã de; PEIXOTO, Carlos Jose Todero.
HALIM, Adila Binti Abdul; CATALANI, Fernando; SOUZA, Vitor de; SANTOS, Edivaldo Moura; OLIVEIRA, Cainã de; PEIXOTO, Carlos Jose Todero.
Abstract: We present measurements of the atmospheric depth of the shower maximum ??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 ??max distributions up to energies of 100 EeV (1020 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 ??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 ??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.
@article={003236753,author = {HALIM, Adila Binti Abdul; CATALANI, Fernando; SOUZA, Vitor de; SANTOS, Edivaldo Moura; OLIVEIRA, Cainã de; PEIXOTO, Carlos Jose Todero.},title={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},journal={Physical Review Letters},note={v. 134, n. 2, p. 021001-1-021001-10},year={2025}}