| Issue |
EPJ Web Conf.
Volume 171, 2018
17th International Conference on Strangeness in Quark Matter (SQM 2017)
|
|
|---|---|---|
| Article Number | 18001 | |
| Number of page(s) | 4 | |
| Section | Open and Hidden Heavy-Flavour (parallel session) | |
| DOI | https://doi.org/10.1051/epjconf/201817118001 | |
| Published online | 02 February 2018 | |
https://doi.org/10.1051/epjconf/201817118001
A data-drive analysis for heavy quark diffusion coefficient
1
Department of Physics, Duke University, Durham, NC 27708, USA
2
SUBATECH, UMR 6457, IMT Atlantique, Universit de Nantes, IN2P3/CNRS, Nantes, France
3
Department of Physics and Astronomy, Wayne State University, Detroit, MI, 48201
* e-mail: yx59@phy.duke.edu
Published online: 2 February 2018
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 Tc 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 RAA and v2 in three different systems at RHIC and the LHC.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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