Linearized Boltzmann-Langevin model for heavy quark transport in hot and dense QCD matter

被引：90

作者：

Ke, Weiyao ^{[1
]}

Xu, Yingru ^{[1
]}

Bass, Steffen A. ^{[1
]}

机构：

[1] Duke Univ, Dept Phys, Durham, NC 27708 USA

来源：

PHYSICAL REVIEW C | 2018年 / 98卷 / 06期

基金：

美国国家科学基金会;

关键词：

RADIATIVE ENERGY-LOSS; NUCLEAR MODIFICATION FACTOR; COLLISIONS; MESON;

D O I：

10.1103/PhysRevC.98.064901

中图分类号：

O57 [原子核物理学、高能物理学];

学科分类号：

070202 ;

摘要：

In relativistic heavy-ion collisions, the production of heavy quarks at large transverse momenta is strongly suppressed compared to proton-proton collisions. In addition, an unexpectedly large azimuthal anisotropy was observed for the emission of charmed hadrons in noncentral collisions. Both observations pose challenges to the theoretical understanding of the coupling between heavy quarks and the quark-gluon plasma produced in these collisions. Transport models for the evolution of heavy quarks in a QCD medium offer the opportunity to study these effects; two of the most successful approaches are based on the linearized Boltzmann transport equation and the Langevin equation. In this work, we develop a hybrid transport model that combines the strengths of both of these approaches: Heavy quarks scatter with medium partons using matrix-elements calculated in perturbative QCD, while between these discrete hard scatterings they evolve using a Langevin equation with empirical transport coefficients to capture the nonperturbative soft part of the interaction. With the hybrid transport model coupled to a state-of-the-art event-by-event bulk evolution model based on 2+1D relativistic viscous fluid dynamics, we study the azimuthal anisotropy and nuclear modification factor of heavy quarks in Pb+Pb collisions at root s = 5.02 TeV. The parameters related to heavy-flavor transport are calibrated using a Bayesian analysis comparing them to available D-meson and B-meson data at the Large Hadron Collider. Using the calibrated model, we study the implications on heavy-flavor transport properties and predict observables.

引用

页数：15

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