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Tuning Monte Carlo Models to Reproduce Cosmic Radiation Interacting with the Earth's Atmosphere.
- Source :
- Atmosphere; Jun2023, Vol. 14 Issue 6, p1028, 12p
- Publication Year :
- 2023
-
Abstract
- In this work, we performed a comparative study between HIJING, Sibyll, and QGSJET model-based event generators. Such Monte Carlo (MC) models are used to simulate the interaction and propagation of high-energy cosmic radiation (e.g., coming from the sun) with the Earth's atmosphere. The global event observables selected for the study were the transverse momentum ( p T ) spectra and rapidity density distributions of strange particles ( K S 0 , Λ , and Ξ − ). This study was performed in the STAR and CMS fiducial phase spaces by simulating the strange particles in p p collisions at s = 200 GeV, 900 GeV, and 7 TeV, and the simulations were then compared to the experimental measurements. It was observed that none of the discussed model-based event generators ultimately predicted the experimental results, except QGSJET, which generally agrees reasonably with the data. However, QGSJET does not produce Ξ particles; therefore, it does not provide any predictions for Ξ. The other two models reproduced the data only in a limited rapidity or transverse momentum region while mainly underpredicting the data in the rest of the areas. These cosmic radiation simulation models are capable of covering the mid-rapidity regions of density distributions. Utilizing model-based observations, some fundamental parameters can be re-tuned and extrapolations to the highest energies can be investigated. Furthermore, these observations can provide valuable insights that could potentially constrain and improve perturbative- and non-perturbative-based QCD event generators, thereby facilitating a better understanding of the underlying physics. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20734433
- Volume :
- 14
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Atmosphere
- Publication Type :
- Academic Journal
- Accession number :
- 164581043
- Full Text :
- https://doi.org/10.3390/atmos14061028