Measurement of the depth of maximum of air-shower profiles with energies between 1018.5 and 1020 eV using the surface detector of the Pierre Auger Observatory and deep learning
Document Type
Article
Publication Date
2-1-2025
Department
Department of Physics
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 Xmax. 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 Xmax 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 Xmax 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 Xmax 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.
Publication Title
Physical Review D
Recommended Citation
Abdul Halim, A.,
Abreu, P.,
Aglietta, M.,
Allekotte, I.,
Almeida Cheminant, K.,
Almela, A.,
Fick, B.,
Nguyen, K.,
Nitz, D.,
&
et al.
(2025).
Measurement of the depth of maximum of air-shower profiles with energies between 1018.5 and 1020 eV using the surface detector of the Pierre Auger Observatory and deep learning.
Physical Review D,
111(2).
http://doi.org/10.1103/PhysRevD.111.022003
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/1364