https://doi.org/10.1140/epjc/s10052-023-12344-7
Regular Article - Experimental Physics
Reconstruction of air shower muon lateral distribution functions using integrator and binary modes of underground muon detectors
1
Instituto de Tecnologías en Detección y Astropartículas (CNEA, CONICET, UNSAM), Av. General Paz 1499, San Martín, B1650KNA, Buenos Aires, Argentina
2
Karlsruher Institut für Technologie, Institut für Kernphysik, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Baden-Württemberg, Germany
a
varada.varma@iteda.cnea.gov.ar
Received:
18
July
2023
Accepted:
8
December
2023
Published online:
19
December
2023
The investigation of cosmic rays holds significant importance in the realm of particle physics, enabling us to expand our understanding beyond atomic confines. However, the origin and characteristics of ultra-high-energy cosmic rays remain elusive, making them a crucial topic of exploration in the field of astroparticle physics. Currently, our examination of these cosmic rays relies on studying the extensive air showers (EAS) generated as they interact with atmospheric nuclei during their passage through Earth’s atmosphere. Accurate comprehension of cosmic ray composition is vital in determining their source. Notably, the muon content of EAS and the atmospheric depth of the shower maximum serve as the most significant indicators of primary mass composition. In this study, we present two novel methods for reconstructing particle densities based on muon counts obtained from underground muon detectors (UMDs) at varying distances to the shower axis. Our methods were analyzed using Monte Carlo air shower simulations. To demonstrate these techniques, we utilized the muon content measurements from the UMD of the Pierre Auger cosmic ray Observatory, an array of detectors dedicated to measuring extensive air showers. Our newly developed reconstruction methods, employed with two distinct UMD data acquisition modes, showcased minimal bias and standard deviation. Furthermore, we conducted a comparative analysis of our approaches against previously established methodologies documented in existing literature.
© The Author(s) 2023
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Funded by SCOAP3. SCOAP3 supports the goals of the International Year of Basic Sciences for Sustainable Development.
