Bayesian Parameter Estimation of Relativistic Heavy Ion Collisions Simulation with Viscous Anisotropic Hydrodynamics Modeling

State-of-the-art hydrodynamic simulation models for relativistic heavy ion collisions are only applicable after 1 fm/c or so after the collision due to large pressure gradients that are present at the early times. As a solution, pre-hydrodynamic stage which models the early stage evolution as a conformal, weekly interacting gas is usually used before the hydrodynamic stage. The transition from pre-hydrodynamic to the hydrodynamic stage is discontinuous and introduce a considerable theoretical ambiguity to the model. Recently a novel hydrodynamic model, Viscous Anisotropic Hydrodynamics (VAH) which can handle large pressure anisotropies has been introduced as a promising solution. VAH is applicable at very early times of the collision and it smoothly matches to conventional second-order viscous hydrodynamics at late times. In this work we present a Bayesian parameter estimation study for VAH model using the experimental data for Pb-Pb collisions at LHC ($\mathrm{s}\sqrt{NN}$=2.76 TeV). We find that the VAH model can fit the experimental data well and we also present the novel physics insights based on the model parameters inferred from the experimental data using Bayesian statistical methods.