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

• Main Authors: Nicusor Arsene, Octavian Sima
• Format: Article
• Language: English
• Published: SpringerOpen 2020-01-01
• Series: European Physical Journal C: Particles and Fields
• Online Access: https://doi.org/10.1140/epjc/s10052-020-7634-2

Abstract The atmospheric depth where the energy deposit profile of secondary particles from extensive air showers (EAS) reaches its maximum, $$X_{\mathrm{max}}$$ Xmax , is related to the primary particle mass. The mass composition of the ultra-high energy cosmic rays (UHECRs) can be inferred from measurements of $$X_{\mathrm{max}}$$ Xmax 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 $$X_{\mathrm{max}}$$ Xmax 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 $$X_{\mathrm{max}}$$ Xmax distributions. Applying this method to the $$X_{\mathrm{max}}$$ Xmax 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.