Thermo-coalescence model for Light Nuclei production in Relativistic Heavy-Ion Collisions

TL;DR

This paper introduces a hybrid thermo-coalescence model combining thermal nucleon production and coalescence to describe light nuclei formation in heavy-ion collisions, validated against LHC data.

Contribution

It develops a novel combined approach for light nuclei production, integrating thermal and coalescence models with Bayesian parameter estimation.

Findings

Successfully fits proton and deuteron $p_{T}$ spectra

Provides estimates for deuteron yields and coalescence parameters

Connects the model with conventional coalescence approaches

Abstract

We employ a hybrid approach to describe the light nuclei production mechanism where the nucleons are assumed to be thermally produced, and are allowed to form light nuclei using a coalescence prescription. In this approach, we first fit transverse momentum ($p_{T}$) distribution of nucleons using hydro-inspired boost-invariant blast-wave model. The extracted parameters are then used to describe the deuteron $p_{T}$ spectra, along with two additional parameters that characterize the coalescence prescription employed in this study. We refer this combined approach as ``thermo-coalescence model'' and it is designed to study the deuteron production and describe the experimental measurements. In this work, we analyze the measured $p_{T}$ distribution of protons and deuterons from Pb-Pb collisions at the ALICE Collaboration at LHC. We also evaluate the $p_{T}$-integrated deuteron yields using this approach and compare with experimental measurements. A Bayesian inference framework is employed to determine the best-fit parameters of the thermo-coalescence model. Finally, we estimate the traditionally used experimental coalescence parameter ($B_{A}$) within our framework in order to establish a connection between our model and the conventional coalescence approach commonly used to relate experimental data with theoretical descriptions of light nuclei production.