Toward a deeper understanding of how experiments constrain the underlying physics of heavy-ion collisions

Abstract

Recent work has provided the means to rigorously determine properties of super-hadronic matter from experimental data through the application of broad scale modeling of high-energy nuclear collisions within a Bayesian framework. These studies have provided unprecedented statistical inferences about the physics underlying nuclear collisions by virtue of simultaneously considering a wide range of model parameters and experimental observables. Notably, this approach has been used to constrain both the QCD equation of state and the shear viscosity above the quark-hadron transition. Although the inferences themselves have a clear meaning, the complex nature of the relationships between model parameters and observables have remained relatively obscure. We present here a novel extension of the standard Bayesian Markov Chain Monte Carlo approach that allows for the quantitative determination of how inferences of model parameters are driven by experimental measurements and their uncertainties. This technique is then applied in the context of heavy ion collisions in order to explore previous results in greater depth. The resulting relationships are useful for identifying model weaknesses, prioritizing future experimental measurements, and most importantly: developing an intuition for the role that different observables play in constraining our understanding of the underlying physics.2

Determination of Quark-Gluon-Plasma Parameters from a Global Bayesian Analysis

“…This effectively removes most practical barriers and enables parameter calibration through standard techniques such as MCMC. Emulators have been successfully used to study a wide range of physical systems, including galaxy formation [19] and heavy-ion collisions [20,21,22,8,9].…”

“…in cosmology, particle physics and climate sciences. In relativistic heavy-ion physics they are fairly novel, having been pioneered by the MADAI collaboration [28,20,22,8]. One application of particular note is the extraction of the QCD equation of state probed in relativistic heavy-ion collisions using these techniques [21].…”

Constraining simultaneously nuclear symmetry energy and neutron-proton effective mass splitting with nucleus giant resonances using a dynamical approach

“…Analogously, for a given slope parameter L, a larger isovector effective mass m * v leads to a smaller centroid energy E −1 and a smaller electric dipole polarizability α D . The rigorous tool to treat such a problem of multiple experimental results with multiple parameters is the Bayesian framework [66][67][68][69], which is beyond the scope of the present study. On the other hand, we found both E −1 and α D are linearly correlated with L and m * v , and the corresponding relations based on our transport calculations turns out to be…”

Effective kinetic description of event-by-event pre-equilibrium dynamics in high-energy heavy-ion collisions

“…Sophisticated multistage models, in which the QGP evolution is described by viscous relativistic hydrodynamics, have been remarkably successful in describing the soft hadronic observables measured in heavy-ion collisions [1][2][3][4][5]. Comprehensive model-to-data comparisons have been made to quantify systematically the constraints provided by measurements on the transport coefficient of the QGP, and to understand the impact of different observables on these constraints [6][7][8].…”