Statistical Model Predictions for p+p and Pb+Pb Collisions at LHC

TL;DR

This paper uses the statistical thermal model to predict particle ratios and yields in p+p and Pb+Pb collisions at LHC, analyzing sensitivity to thermodynamic parameters and strangeness suppression mechanisms.

Contribution

It extends the statistical thermal model to LHC energies, providing predictions for particle production and exploring strangeness suppression effects in high-energy collisions.

Findings

Predicted particle ratios for heavy-ion collisions at LHC.

Identified key ratios sensitive to temperature and chemical potential.

Discussed the impact of strangeness suppression on particle yields.

Abstract

Particle production in p+p and central Pb+Pb collisions at LHC is discussed in the context of the statistical thermal model. For heavy-ion collisions, predictions of various particle ratios are presented. The sensitivity of several ratios on the temperature and the baryon chemical potential is studied in detail, and some of them, which are particularly appropriate to determine the chemical freeze-out point experimentally, are indicated. Considering elementary interactions on the other hand, we focus on strangeness production and its possible suppression. Extrapolating the thermal parameters to LHC energy, we present predictions of the statistical model for particle yields in p+p collisions. We quantify the strangeness suppression by the correlation volume parameter and discuss its influence on particle production. We propose observables that can provide deeper insight into the mechanism of strangeness production and suppression at LHC.