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Title: 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 R AA and v 2 in AuAu collisions ($$\sqrt{s}$$NN = 200 GeV) and PbPb collisions ($$\sqrt{s}$$NN = 2.76 TeV) [1]. The spatial diffusion coefficient D s2πT is found to be mostly constraint around (1.3 1.5)T c and is compatible with lattice QCD calculations. Here we demonstrate the capability of our improved Langevin model to simultaneously describe the R AA and v 2 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.

Authors:
 [1];  [2];  [1];  [3];  [1]
  1. Duke Univ., Durham, NC (United States)
  2. Duke Univ., Durham, NC (United States); Univ. de Nantes, Nantes cedex (France)
  3. Wayne State Univ., Detroit, MI (United States)
Publication Date:
Research Org.:
Duke Univ., Durham, NC (United States); Wayne State Univ., Detroit, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1502387
Grant/Contract Number:  
[FG02-05ER41367; SC0013460]
Resource Type:
Accepted Manuscript
Journal Name:
Nuclear Physics. A
Additional Journal Information:
[ Journal Volume: 967; Journal Issue: C]; Journal ID: ISSN 0375-9474
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; heavy-ion collisions; heavy quarks; diffusion coefficient; Bayesian analysis

Citation Formats

Xu, Yingru, Nahrgang, Marlene, Bernhard, Jonah E., Cao, Shanshan, and Bass, Steffen A. A data-driven analysis of the heavy quark transport coefficient. United States: N. p., 2017. Web. doi:10.1016/j.nuclphysa.2017.05.035.
Xu, Yingru, Nahrgang, Marlene, Bernhard, Jonah E., Cao, Shanshan, & Bass, Steffen A. A data-driven analysis of the heavy quark transport coefficient. United States. doi:10.1016/j.nuclphysa.2017.05.035.
Xu, Yingru, Nahrgang, Marlene, Bernhard, Jonah E., Cao, Shanshan, and Bass, Steffen A. Mon . "A data-driven analysis of the heavy quark transport coefficient". United States. doi:10.1016/j.nuclphysa.2017.05.035. https://www.osti.gov/servlets/purl/1502387.
@article{osti_1502387,
title = {A data-driven analysis of the heavy quark transport coefficient},
author = {Xu, Yingru and Nahrgang, Marlene and Bernhard, Jonah E. and Cao, Shanshan and Bass, Steffen A.},
abstractNote = {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 ($\sqrt{s}$NN = 200 GeV) and PbPb collisions ($\sqrt{s}$NN = 2.76 TeV) [1]. The spatial diffusion coefficient Ds2πT is found to be mostly constraint around (1.3 1.5)Tc and is compatible with lattice QCD calculations. Here 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.},
doi = {10.1016/j.nuclphysa.2017.05.035},
journal = {Nuclear Physics. A},
number = [C],
volume = [967],
place = {United States},
year = {2017},
month = {9}
}

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Figures / Tables:

Fig. 1 Fig. 1: (Color online) GP emulators prediction of 200 input samples randomly selected from the posterior distribution, and full Langevin calculation as taking the distribution median as parameters, compared with experimental data from STAR and ALICE [1].

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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.