Production of $K^{\pm}$ charged particles spectra with cosmic ray models simulation

The purpose of this analysis is to conduct a simulation study and evaluate the performance of a few hadronic interaction models in the production of $K^{\pm}$ charged particles measured by the ALICE experiment in proton-proton collisions at $\sqrt s$ = 900 GeV using modified Hagedorn function with embedded transverse flow velocity. Simulation models in this analysis are widely used to describe the propagation of cosmic air showers in the atmosphere. Among the employed hadronic interaction models, we present results from the EPOS-LHC, Pythia, QGSJETII-04, and Sibyll models, as they are widely used and able to achieve good agreement with experimental data. Up to about 1.3 GeV/c, EPOS-LHC and Sibyll show a good prediction of the data, while Pythia, QGSJETII-04 underestimate the data over the entire energy range.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.22323/1.465.0084
Primary Topic
Dark Matter and Cosmic Phenomena
Type
article
Field-Weighted Citation Impact
0.00

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article

Production of $K^{\pm}$ charged particles spectra with cosmic ray models simulation

A. Haj Ismail
Dark Matter and Cosmic Phenomena
article

Production of $K^{\pm}$ charged particles spectra with cosmic ray models simulation

A. Haj Ismail
article en

Abstract

The purpose of this analysis is to conduct a simulation study and evaluate the performance of a few hadronic interaction models in the production of $K^{\pm}$ charged particles measured by the ALICE experiment in proton-proton collisions at $\sqrt s$ = 900 GeV using modified Hagedorn function with embedded transverse flow velocity. Simulation models in this analysis are widely used to describe the propagation of cosmic air showers in the atmosphere. Among the employed hadronic interaction models, we present results from the EPOS-LHC, Pythia, QGSJETII-04, and Sibyll models, as they are widely used and able to achieve good agreement with experimental data. Up to about 1.3 GeV/c, EPOS-LHC and Sibyll show a good prediction of the data, while Pythia, QGSJETII-04 underestimate the data over the entire energy range.

Ajman University
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Dark Matter and Cosmic Phenomena
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