Measurement of the Depth of Maximum of Air-Shower Profiles with energies between $\mathbf{10^{18.5}}$ and $\mathbf{10^{20}}$ eV using the Surface Detector of the Pierre Auger Observatory and Deep Learning

TL;DR

This study uses deep learning to analyze a large dataset of cosmic ray air showers, revealing a trend towards heavier composition at higher energies and identifying structural features related to cosmic ray sources.

Contribution

It introduces a deep-learning-based method for reconstructing $X_{max}$, enabling the first detailed measurement of composition evolution up to 100 EeV with high statistics.

Findings

Confirmation of heavier composition with increasing energy.

Observation of small fluctuations in $X_{max}$ at high energies.

Detection of three spectral features near the ankle, instep, and suppression.

Abstract

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV=$10^{18}$ eV) using the distributions of the depth of shower maximum $X_\mathrm{max}$. The analysis relies on ${\sim}50,000$ events recorded by the Surface Detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the data set 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 $X_\mathrm{max}$ distributions up to 100 EeV. Our findings are threefold: (1.) The evolution of the mean logarithmic mass towards a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (2.) The evolution of the fluctuations of $X_\mathrm{max}$ towards a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in $X_\mathrm{max}$ at the highest energies. (3.) 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.