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Title: A data-driven analysis of the heavy quark transport coefficient

Journal Article · · Nuclear Physics. A
 [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)
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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.

Research Organization:
Duke Univ., Durham, NC (United States); Wayne State Univ., Detroit, MI (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
FG02-05ER41367; SC0013460
OSTI ID:
1502387
Journal Information:
Nuclear Physics. A, Vol. 967, Issue C; ISSN 0375-9474
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 8 works
Citation information provided by
Web of Science

References (20)

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emcee : The MCMC Hammer
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Figures / Tables (3)

Fig. 1(p. 3)figure Fig. 1
Fig. 2(p. 4)figure Fig. 2
Fig. 3(p. 4)figure Fig. 3

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Related Subjects

73 NUCLEAR PHYSICS AND RADIATION PHYSICS
heavy-ion collisions
heavy quarks
diffusion coefficient
Bayesian analysis