Chemical freeze-out systematics of thermal model analysis using hadron yield ratios

TL;DR

This paper introduces a graph theory-based framework to systematically estimate uncertainties in chemical freeze-out parameters derived from thermal model analyses of hadron yield ratios in heavy-ion collisions.

Contribution

It presents a novel method to generate all independent hadron yield ratio sets for more accurate uncertainty estimation in thermal model parameters.

Findings

Large number of independent ratio sets (up to 10^8) identified.

Systematic uncertainties in freeze-out parameters quantified.

Comparison with previous results shows improved uncertainty estimates.

Abstract

We provide a framework to estimate the systematic uncertainties in chemical freeze-out parameters extracted from $\chi^2$ analysis of thermal model, using hadron multiplicity ratios in relativistic heavy-ion collision experiments. Using a well known technique of graph theory, we construct all possible sets of independent ratios from available hadron yields and perform $\chi^2$ minimization on each set. We show that even for ten hadron yields, one obtains a large number ($10^8$) of independent sets which results in a distribution of extracted freeze-out parameters. We analyze these distributions and compare our results for chemical freeze-out parameters and associated systematic uncertainties with previous results available in the literature.