A data-driven analysis of the heavy quark transport coefficient

Abstract Using a Bayesian model-to-data analysis, we estimate the temperature dependence of the heavy quark diffusion coefficients by calibrating to the experimental data of D-meson RAA and v2 in AuAu collisions ( s N N = 200 GeV ) and PbPb collisions ( s N N = 2.76 TeV ) [G. Xie [STAR Collaboration], Nucl. Phys. A 956, 473 (2016); A. Andronic et al., Eur. Phys. J. C 76, no. 3, 107 (2016)]. The spatial diffusion coefficient D s 2 π T is found to be mostly constraint around ( 1.3 − 1.5 ) T c and is compatible with lattice QCD calculations. We demonstrate the capability of our improved Langevin model to simultaneously describe the RAA and v2 at both RHIC and the LHC energies, as well as the feasibility to apply a Bayesian analysis to quantitatively study the heavy flavor transport in heavy-ion collisions.