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A data-drive analysis for heavy quark diffusion coefficient
2018
EPJ Web of Conferences
We apply a Bayesian model-to-data analysis on an improved Langevin framework to estimate the temperature and momentum dependence of the heavy quark diffusion coefficient in the quark-gluon plasma (QGP). The spatial diffusion coefficient is found to have a minimum around 1-3 near T c in the zero momentum limit, and has a non-trivial momentum dependence. With the estimated diffusion coefficient, our improved Langevin model is able to simultaneously describe the D-meson R AA and v 2 in three different systems at RHIC and the LHC. ⋆
doi:10.1051/epjconf/201817118001
fatcat:tsp4zcnuorew5h5w7xywgoxfsa