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Deep-learning based reconstruction of the shower maximum X$_{max}$ using the water-Cherenkov detectors of the Pierre Auger Observatory

Pierre Auger Collaboration; Aab, A.; Abreu, P.; Aglietta, M.; Albury, J. M.; Allekotte, I.; Almela, A.; Alvarez-Muñiz, J.; Alves Batista, R.; Anastasi, G. A.; Anchordoqui, L.; Andrada, B.; Andringa, S.; Aramo, C.; Araújo Ferreira, P. R.; Arteaga Velázquez, J. C.; Asorey, H.; Assis, P.; Avila, G.; ... mehr

Abstract:

The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of Xmax are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of Xmax from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of Xmax. The reconstruction relies on the signals induced by shower particles in the ground based water-Cherenkov detectors of the Pierre Auger Observatory. The network architecture features recurrent long short-term memory layers to process the temporal structure of signals and hexagonal convolutions to exploit the symmetry of the surface detector array. We evaluate the performance of the network using air showers simulated with three different hadronic interaction models. Thereafter, we account for long-term detector effects and calibrate the reconstructed Xmax using fluorescence measurements. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000135435
Veröffentlicht am 16.07.2021
Originalveröffentlichung
DOI: 10.1088/1748-0221/16/07/P07019
Scopus
Zitationen: 10
Dimensions
Zitationen: 10
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Astroteilchenphysik (IAP)
Institut für Experimentelle Teilchenphysik (ETP)
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 07.2021
Sprache Englisch
Identifikator ISSN: 1748-0221
KITopen-ID: 1000135435
HGF-Programm 51.13.03 (POF IV, LK 01) Kosmische Strahlung Auger
Erschienen in Journal of Instrumentation
Verlag Institute of Physics Publishing Ltd (IOP Publishing Ltd)
Band 16
Heft 07
Seiten Article: P07019
Vorab online veröffentlicht am 14.07.2021
Nachgewiesen in Dimensions
Scopus
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