A Monte Carlo study to measure the energy spectra of the primary cosmic-ray components at the knee using a new Tibet AS core detector array

TL;DR

This study uses Monte Carlo simulations and neural networks to evaluate a new hybrid detector array's ability to measure the energy spectra and chemical composition of cosmic rays at the knee.

Contribution

It introduces a novel hybrid detector setup and demonstrates its effectiveness in identifying primary cosmic-ray components using simulation and neural network analysis.

Findings

The new detector array can distinguish between proton, helium, and iron components.

The setup effectively measures the primary energy spectrum at the cosmic-ray knee.

Simulation results support the detector's capability for chemical composition analysis.

Abstract

A new hybrid experiment has been started by AS{\gamma} experiment at Tibet, China, since August 2011, which consists of a low threshold burst-detector-grid (YAC-II, Yangbajing Air shower Core array), the Tibet air-shower array (Tibet-III) and a large underground water Cherenkov muon detector (MD). In this paper, the capability of the measurement of the chemical components (proton, helium and iron) with use of the (Tibet-III+YAC-II) is investigated by means of an extensive Monte Carlo simulation in which the secondary particles are propagated through the (Tibet-III+YAC-II) array and an artificial neural network (ANN) method is applied for the primary mass separation. Our simulation shows that the new installation is powerful to study the chemical compositions, in particular, to obtain the primary energy spectrum of the major component at the knee.