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

Abstract

The quality of data taken at RHIC and LHC as well as the success and sophistication of computational models for the description of ultra-relativistic heavy-ion collisions have advanced to a level that allows for the quantitative extraction of the transport properties of the Quark-Gluon-Plasma. However, the complexity of this task as well as the computational effort associated with it can only be overcome by developing novel methodologies: in this paper we outline such an analysis based on Bayesian Statistics and systematically compare an event-by-event heavy-ion collision model to data from the Large Hadron Collider. We simultaneously probe multiple model parameters including fundamental quark-gluon plasma properties such as the temperature-dependence of the specific shear viscosity $\eta /s$, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. The method is universal and easily extensible to other data and collision models.

arXiv commentproceedings for Quark Matter 2017

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• Exploring QCD matter in extreme conditions with Machine Learning
• Transport coefficients for the hot quark-gluon plasma at finite chemical potential ${\mu }_B$
• Temperature dependence of $\eta /s$ of strongly interacting matter: effects of the equation of state and the parametric form of $(\eta /s)(T)$
• Predictions for multiplicities and flow harmonics in 5.44 TeV Xe+Xe collisions at the CERN Large Hadron Collider
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• The quest for the quark-gluon plasma from the perspective of dynamical models of relativistic heavy-ion collisions
• Holography in Quark-Gluon Plasma and Neutron Stars