Innovative Approaches to Unravel the Shower Components' Energy Spectrum with a Single Hybrid Station

TL;DR

This paper introduces two innovative experimental methods using a single hybrid detector station to measure the energy spectra of electromagnetic and muonic components in extensive air showers, enhancing cosmic ray analysis.

Contribution

The work presents novel strategies combining detector responses and machine learning to extract detailed energy spectra from a single station, improving upon traditional multi-detector approaches.

Findings

First method extracts electromagnetic and muonic energy tails.

Second method uses machine learning for muon direction reconstruction.

Demonstrates feasibility at Pierre Auger Observatory.

Abstract

Accurately measuring the energy of shower particles reaching the ground remains a challenge due to the inherent limitations of typical cosmic ray experiments. In this work, we present two experimental strategies to determine the energy spectra of the electromagnetic and muonic components of extensive air showers, leveraging a single hybrid detector station within a regular cosmic ray array. This station consists of a scintillator surface detector (SSD), a water Cherenkov detector (WCD), and Resistive Plate Chambers (RPCs), with a prototype currently being tested at the Pierre Auger Observatory. The first approach exploits the different responses of each detector to the same particles traversing them, allowing, for the first time, the extraction of the high-energy tail of the electromagnetic spectrum and the low-energy tail of the muonic spectrum. The second strategy utilizes machine learning tools to reconstruct the direction of muons using the WCD+RPC system. By correlating this information with the reconstructed muon production depth, the muon kinematical delay can be analyzed, providing access to its energy spectrum.