Bayesian analysis of heavy ion collisions with the heavy ion computational framework Trajectum

TL;DR

This paper introduces Trajectum, a comprehensive Bayesian framework for analyzing heavy ion collision data, incorporating an expanded initial state, hydrodynamics, and a Gaussian Emulator for efficient parameter estimation.

Contribution

The paper presents a novel 20-parameter model for heavy ion collisions with an emulator for Bayesian inference, enabling detailed comparison with experimental data.

Findings

Successful Gaussian Emulator for the 20-parameter model

Bayesian posterior estimates for model parameters

Consistent comparison with experimental PbPb and pPb collision data

Abstract

We introduce a model for heavy ion collisions named Trajectum, which includes an expanded initial stage with a variable free streaming velocity $v_{\rm fs}$ and a hydrodynamic stage with three varying second order transport coefficients. We describe how to obtain a Gaussian Emulator for this 20-parameter model and show results for key observables. This emulator can be used to obtain Bayesian posterior estimates on the parameters, which we test by an elaborate closure test as well as a convergence study. Lastly, we employ the optimal values of the parameters found in [1] to perform a detailed comparison to experimental data from PbPb and $p$Pb collisions. This includes both observables that have been used to obtain these values as well as wider transverse momentum ranges and new observables such as correlations of event-plane angles.