Mass composition of ultra-high-energy cosmic rays with the Telescope Array Surface Detector Data

TL;DR

This paper presents an analysis of ultra-high-energy cosmic ray composition using a multivariate approach with the Telescope Array Surface Detector, finding a consistent average atomic mass across a wide energy range.

Contribution

It introduces a boosted decision tree method utilizing 14 observables to determine cosmic ray mass composition, providing a new approach compared to traditional techniques.

Findings

Average atomic mass $\, ext{ln}A=2.0\, ext{±}\,0.1\, ext{(stat.)}\, ext{±}\,0.44\, ext{(syst.)}$ across energies $10^{18}$ to $10^{20}$ eV.

No significant energy dependence observed in the mass composition.

Results are consistent with previous measurements using the $ ext{X}_{ ext{max}}$ technique.

Abstract

The results on ultra-high-energy cosmic rays (UHECR) mass composition obtained with the Telescope Array surface detector are presented. The analysis employs the boosted decision tree (BDT) multivariate analysis built upon 14 observables related to both the properties of the shower front and the lateral distribution function. The multivariate classifier is trained with Monte-Carlo sets of events induced by the primary protons and iron. An average atomic mass of UHECR is presented for energies $10^{18.0}-10^{20.0}\ \mbox{eV}$. The average atomic mass of primary particles shows no significant energy dependence and corresponds to $\langle \ln A \rangle = 2.0 \pm 0.1 (stat.) \pm 0.44 (syst.)$. The result is compared to the mass composition obtained by the Telescope Array with $\mbox{X}_{\mbox{max}}$ technique along with the results of other experiments. Possible systematic errors of the method are discussed.