Applying Bayesian parameter estimation to relativistic heavy-ion collisions: Simultaneous characterization of the initial state and quark-gluon plasma medium Article Swipe
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· 2016
· Open Access
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· DOI: https://doi.org/10.1103/physrevc.94.024907
· OA: W2354504395
We quantitatively estimate properties of the quark-gluon plasma created in\nultra-relativistic heavy-ion collisions utilizing Bayesian statistics and a\nmulti-parameter model-to-data comparison. The study is performed using a\nrecently developed parametric initial condition model, TRENTO, which\ninterpolates among a general class of particle production schemes, and a modern\nhybrid model which couples viscous hydrodynamics to a hadronic cascade. We\ncalibrate the model to multiplicity, transverse momentum, and flow data and\nreport constraints on the parametrized initial conditions and the\ntemperature-dependent transport coefficients of the quark-gluon plasma. We show\nthat initial entropy deposition is consistent with a saturation-based picture,\nextract a relation between the minimum value and slope of the\ntemperature-dependent specific shear viscosity, and find a clear signal for a\nnonzero bulk viscosity.\n
