📝 SummarXiv

Abstract

The origin of ultra-high-energy cosmic rays, with energies $E \geq 10^{18}$ eV, remains unknown. Among the key observables used to investigate their nature are the energy spectrum, the arrival direction distribution, and the composition as a function of energy. The composition of the primary cosmic ray is inferred from properties of the extensive air showers they initiate, particularly from parameters sensitive to the primary mass. The most sensitive parameters to the primary mass are the atmospheric depth of the shower maximum, typically measured with fluorescence telescopes, and the muon content of the shower, measured using dedicated muon detectors. A commonly used observable in composition studies is the muon density at a fixed distance from the shower axis, derived by evaluating the reconstructed muon lateral distribution function (MLDF) at a reference distance. A specific type of muon detector features two acquisition modes: binary and integrator (commonly referred to as ADC mode, for Analog-to-Digital Converter). The binary mode allows for direct muon counting, while the ADC mode infers the muon number from the integrated signal of the detector response. Existing methods reconstruct the MLDF using data from either acquisition mode individually, or by combining both, but usually assigning a single mode per detector station in a given event. This work presents a novel method to reconstruct the MLDF based on a likelihood approach that simultaneously incorporates data from both acquisition modes at each detector station. We apply our method to the underground muon detectors of the Pierre Auger Observatory as a case study. However, this general approach can be applied to future detectors with dual acquisition capabilities. Our results demonstrate that the combined method outperforms traditional techniques that rely solely on either binary or ADC mode data.