On model emulation and closure tests for 3+1D relativistic heavy-ion collisions

TL;DR

This paper evaluates Gaussian Process emulators to improve the efficiency and accuracy of parameter extraction in complex heavy-ion collision simulations, aiding the understanding of Quark Gluon Plasma properties.

Contribution

It provides a comparative analysis of different Gaussian Process emulators specifically tailored for heavy-ion physics applications.

Findings

Identifies the most effective emulator for parameter extraction.

Demonstrates reduced uncertainty in Bayesian calibration.

Enhances computational efficiency in heavy-ion collision modeling.

Abstract

In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated in heavy-ion collisions. However, computational demands pose challenges, motivating using Gaussian Process emulators for efficient parameter extraction via Bayesian calibration. We conduct a comparative analysis of Gaussian Process emulators in heavy-ion physics to identify the most adept emulator for parameter extraction with minimal uncertainty. Our study contributes to advancing computational techniques in heavy-ion physics, enhancing our ability to interpret experimental data and understand QGP properties.