UHECRs mass composition from $X_{\max }$ distributions

Abstract

The atmospheric depth where the energy deposit profile of secondary particles from extensive air showers (EAS) reaches its maximum, $X_{\max }$, is related to the primary particle mass. The mass composition of the ultra-high energy cosmic rays (UHECRs) can be inferred from measurements of $X_{\max }$ distributions in each energy interval, by fitting these distributions with Monte Carlo (MC) templates for four primary species (p, He, N and Fe). On the basis of simulations, we show that a high abundance of some intermediate elements in the $X_{\max }$ distributions, e.g. Ne or Si, may affect the quality of the fit and also the reconstructed fractions of different species with respect to their true values. We propose a method for finding the "best combination" of elements in each energy interval from a larger set of primaries (p, He, C, N, O, Ne, Si and Fe) which best describes the $X_{\max }$ distributions. Applying this method to the $X_{\max }$ distributions measured by the Pierre Auger Observatory (2014), we found that the "best combination" of elements which best describe the data suggest the presence of Ne or Si in some low energy bins for the EPOS-LHC model.

Accepted for publication in European Physical Journal C

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Cited by in corpus (2)

• Mass Composition of UHECRs from $X_{\max }$ Distributions Recorded by the Pierre Auger and Telescope Array Observatories
• Learning the Composition of Ultra High Energy Cosmic Rays