• DOI:10.1103/PhysRevC.94.024907
• Corpus ID: 119206079

Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous characterization of the initial state and quark-gluon plasma medium

@article{Bernhard2016ApplyingBP,
  title={Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous characterization of the initial state and quark-gluon plasma medium},
  author={Jonah Bernhard and J. Scott Moreland and Steffen A. Bass and Jia Liu and Ulrich Heinz},
  journal={Physical Review C},
  year={2016},
  volume={94},
  pages={024907}
}

• J. Bernhard, J. Moreland, +2 authors U. Heinz
• Published 12 May 2016
• Physics
• Physical Review C

We quantitatively estimate properties of the quark-gluon plasma created in ultrarelativistic heavy-ion collisions utilizing Bayesian statistics and a multiparameter model-to-data comparison. The study is performed using a recently developed parametric initial condition model, TRENTo, which interpolates among a general class of particle production schemes, and a modern hybrid model which couples viscous hydrodynamics to a hadronic cascade. We calibrate the model to multiplicity, transverse momentum, and flow data and report constraints on the parametrized initial conditions and the temperature-dependent transport coefficients of the quark-gluon plasma. We show that initial entropy deposition is consistent with a saturation-based picture, extract a relation between the minimum value and slope of the temperature-dependent specific shear viscosity, and find a clear signal for a nonzero bulk viscosity.