Determining Fundamental Properties of Matter Created in Ultrarelativistic Heavy-Ion Collisions

TL;DR

This paper uses advanced statistical methods to extract the properties of quark-gluon plasma from heavy-ion collision data, providing detailed parameter estimates and correlations.

Contribution

It introduces a comprehensive Bayesian framework with Gaussian Process emulators to analyze multiple parameters and observables in heavy-ion collision models.

Findings

Full multi-dimensional posterior distributions obtained

Identified correlations between physical parameters

Extended analysis beyond previous studies

Abstract

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results from 100$A$ GeV + 100$A$ GeV Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC). By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables to model parameters. We obtain a full multi-dimensional posterior distribution for the model output given a large set of experimental observations, the methods developed here provide a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go far beyond previous studies in this field. The statistical tools, which are based upon Gaussian Process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.