Bayesian model mixing for longitudinal dynamics of relativistic heavy-ion collisions

In this talk, we present a generalized parameterization of the longitudinal profiles in the 3D Monte Carlo (MC) Glauber model that incorporates both ``tilted'' and ``shifted'' scenarios using the Bayesian model-mixing technique [1]. Local energy and momentum conservation impose constraints on the parameters related to the modification [2]. We perform a Bayesian analysis of RHIC BES data using a (3+1)D framework that combines our modified 3D MC Glauber model with the hydrodynamic model MUSIC and the hadronic transport model UrQMD. We will demonstrate how rapidity-dependent flow observables, namely v_1,2(η), impose constraints on the energy and net baryon distributions in the initial state model. Our analysis will also employ a non-parametric approach for constraining the QGP-specific shear and bulk viscosities as functions of temperature T and chemical potential μ_B.

1. Piotr Bozek and Iwona Wyskiel. “Directed flow in ultrarelativistic heavy-ion collisions”. In: Phys. Rev. C 81 (2010), p. 054902. doi: 10 . 1103 / PhysRevC.81.054902. arXiv: 1002.4999 [nucl-th].

2. Chun Shen and Sahr Alzhrani. “Collision-geometry-based 3D initial condition for relativistic heavy-ion collisions”. In: Phys. Rev. C 102.1 (2020), p. 014909. doi: 10 . 1103 / PhysRevC . 102 . 014909. arXiv: 2003 . 05852 [nucl-th].