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HK: Fachverband Physik der Hadronen und Kerne

HK 34: Heavy-Ion Collisions and QCD Phases VIII

HK 34.4: Talk

Tuesday, March 12, 2024, 18:30–18:45, HBR 62: EG 18

Bayesian inference of quark-gluon plasma transport coefficients from transverse momentum spectra and flow observables — •Rafet Kavak for the ALICE Germany collaboration — GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Deutschland

Heavy-ion collisions provide a window into the properties of the quark-gluon plasma (QGP), a state of matter in which quarks and gluons are deconfined. Understanding the collective properties of the QGP is possible by comparing models of heavy-ion collisions to experimental measurements of the distribution of particles produced at the end of the collisions. Bayesian inference provides a rigorous statistical framework to constrain the properties of nuclear matter by systematically comparing models and measurements. In this talk, our latest analysis of the experimental data for transverse momentum spectra and flow observables of identified charged hadrons in Pb-Pb and Xe-Xe collisions at the LHC will be presented. Our Bayesian framework is used to constrain transport coefficients of the QGP, such as shear and bulk viscosities, initialization time, and kinetic and chemical freezeout temperatures.

This work is funded via the DFG ISOQUANT Collaborative Research Center (SFB 1225).

Keywords: Bayesian parameter estimation