A. Abdul Halim (Avtor), P. Abreu (Avtor), M. Aglietta (Avtor), Andrej Filipčič (Avtor), J. P. Lundquist (Avtor), S. U. Shivashankara (Avtor), Samo Stanič (Avtor), Serguei Vorobiov (Avtor), Danilo Zavrtanik (Avtor), Marko Zavrtanik (Avtor)

Povzetek

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV = 10[sup]18 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.

Ključne besede

ultra-high-energy cosmic rays;UHECRs;extensive air showers;Pierre Auger Observatory;UHECR mass composition;depth of shower maximum;fluorescence detector;surface detector;deep learning;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UNG - Univerza v Novi Gorici
UDK: 52
COBISS: 222998275 Povezava se bo odprla v novem oknu
ISSN: 2470-0029
Št. ogledov: 114
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Strani: str. 1-30
Letnik: ǂVol. ǂ111
Zvezek: ǂissue ǂ2, [article no.] 022003
Čas izdaje: Feb. 2025
DOI: 10.1103/PhysRevD.111.022003
ID: 25738917