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Inference of the Mass Composition of Cosmic Rays with Energies from 10^{18.5} to 10^{20} eV Using the Pierre Auger
A Abdul Halim1, P Abreu2, M Aglietta3,4
1University of Adelaide, Adelaide, South Australia, Australia.
Physical Review Letters
|February 6, 2025
Summary
Researchers used deep learning to measure the atmospheric depth of shower maximum (Xmax) for cosmic rays. This reveals insights into cosmic ray composition at extreme energies, showing a trend towards heavier and purer elements.
Area of Science:
- Astroparticle Physics
- Cosmic Ray Physics
Background:
- Understanding the origin and nature of ultra-high-energy cosmic rays (UHECRs) is a major challenge in astroparticle physics.
- The mass composition of UHECRs provides crucial clues to their sources and acceleration mechanisms.
Purpose of the Study:
- To measure the atmospheric depth of shower maximum (Xmax) for UHECRs on an event-by-event basis.
- To extend Xmax measurements to unprecedented energies (up to 100 EeV) and analyze their distributions.
- To gain new insights into the mass composition of cosmic rays at extreme energies.
Main Methods:
- Utilized the surface detector of the Pierre Auger Observatory.
- Applied deep learning techniques to infer Xmax on an event-by-event level.
- Analyzed Xmax distributions and their evolution with energy.
Main Results:
- Extended Xmax measurements to 100 EeV, significantly increasing statistics compared to fluorescence detector data.
- Identified three distinct breaks in the rate of change of average Xmax with energy at approximately 6.5, 11, and 31 EeV.
- Observed that the energy evolution of Xmax indicates a progressively heavier and purer cosmic ray composition.
Conclusions:
- The observed trend of increasing Xmax suggests a transition to heavier cosmic ray nuclei at energies above 50 EeV.
- The findings are incompatible with a significant fraction of light nuclei in the 50-100 EeV range.
- The breaks in Xmax evolution correlate with prominent features in the cosmic ray energy spectrum.
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