Measurement of the depth of maximum of air-shower profiles with energies between 10 18.5 and 10 20 eV using the surface detector of 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 report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV=1018 eV) using the distributions of the depth of shower maximum ??max. The analysis relies on ~50,000 events recorded by the surface detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the dataset offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the fluorescence detector, this enables the first measurement of the evolution of the mean and the standard deviation of the ??max distributions up to 100 EeV. Our findings are threefold: (i) The evolution of the mean logarithmic mass toward a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (ii) The evolution of the fluctuations of ??max toward a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in ??max at the highest energies. (iii) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum.
@article={003237020,author = {HALIM, Adila Binti Abdul; CATALANI, Fernando; SOUZA, Vitor de; SANTOS, Edivaldo Moura; OLIVEIRA, Cainã de; PEIXOTO, Carlos Jose Todero.},title={Measurement of the depth of maximum of air-shower profiles with energies between 10 18.5 and 10 20 eV using the surface detector of the Pierre Auger Observatory and deep learning},journal={Physical Review D},note={v. 111, n. 2, p. 022003-1-022003-30},year={2025}}