Analysis of hadron yield data within hadron resonance gas model with multi-component eigenvolume corrections

TL;DR

This paper investigates how different assumptions about eigenvolume interactions in the hadron resonance gas model affect the extraction of chemical freeze-out parameters from heavy-ion collision data, revealing high sensitivity and potential instability in thermal fits.

Contribution

It demonstrates the significant impact of eigenvolume modeling on HRG thermodynamics and highlights the instability of thermal fits when including light nuclei yields.

Findings

Large sensitivity of thermal fit parameters to eigenvolume assumptions.

Including light nuclei yields increases fit instability.

Modeling eigenvolume interactions is crucial for accurate HRG thermodynamics.

Abstract

We analyze the sensitivity of thermal fits to heavy-ion hadron yield data of ALICE and NA49 collaborations to the systematic uncertainties in the hadron resonance gas (HRG) model related to the modeling of the eigenvolume interactions. We find a surprisingly large sensitivity in extraction of chemical freeze-out parameters to the assumptions regarding eigenvolumes of different hadrons. We additionally study the effect of including yields of light nuclei into the thermal fits to LHC data and find even larger sensitivity to the modeling of their eigenvolumes. The inclusion of light nuclei yields, thus, may lead to further destabilization of thermal fits. Our results show that modeling of eigenvolume interactions plays a crucial role in thermodynamics of HRG and that conclusions based on a non-interacting HRG are not unique.