Lattice simulations of a 3D effective gluonic plasma theory produce the first reported momentum dependence of heavy quark drag and diffusion coefficients in a non-perturbative non-Abelian thermal medium.
A data-driven analysis for the temperature and momentum dependence of the heavy quark diffusion coefficient in relativistic heavy-ion collisions
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abstract
By applying a Bayesian model-to-data analysis, we estimate the temperature and momentum dependence of the heavy quark diffusion coefficient in an improved Langevin framework. The posterior range of the diffusion coefficient is obtained by performing a Markov chain Monte Carlo random walk and calibrating on the experimental data of $D$-meson $R_{\mathrm{AA}}$ and $v_2$ in three different collision systems at RHIC and the LHC: AuAu collisions at 200 GeV, PbPb collisions at 2.76 and 5.02 TeV. The spatial diffusion coefficient is found to be consistent with lattice QCD calculations and comparable with other models' estimation. We demonstrate the capability of our improved Langevin model to simultaneously describe the $R_{\mathrm{AA}}$ and $v_2$ at both RHIC and the LHC energies, as well as the higher order flow coefficient such as $D$-meson $v_3$. We show that by applying a Bayesian analysis, we are able to quantitatively and systematically study the heavy flavor dynamics in heavy-ion collisions.
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UNVERDICTED 5representative citing papers
First simultaneous Bayesian extraction of 2πT D_s and q-hat/T^3 from D-meson R_AA and v2 at 5.02 TeV, yielding a non-monotonic temperature dependence in their ratio that deviates from the expected value of 2.
Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.
Kolmogorov dynamics for heavy quarks in hot plasma shows significantly delayed large-momentum equilibration compared to Fokker-Planck with matched drag, due to rare low-momentum-loss events.
Charm quarks develop dynamical attractors in expanding QGP but with lattice-QCD diffusion coefficients require ~5 fm to relax, leading to O(1) deviations from equilibrium already at pT ~ 3 GeV and incomplete thermalization in small systems.
citing papers explorer
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Momentum Dependence of Heavy Quark Diffusion in a Thermal Gluonic Plasma on the Lattice
Lattice simulations of a 3D effective gluonic plasma theory produce the first reported momentum dependence of heavy quark drag and diffusion coefficients in a non-perturbative non-Abelian thermal medium.
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Bayesian Inference of Heavy-Quark Dissipation and Jet Transport Parameters from D-Meson observables in heavy-ion collisions at the LHC energies
First simultaneous Bayesian extraction of 2πT D_s and q-hat/T^3 from D-meson R_AA and v2 at 5.02 TeV, yielding a non-monotonic temperature dependence in their ratio that deviates from the expected value of 2.
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Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning
Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.
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Stochastic Dynamics of Heavy Quarks in Strongly Coupled Plasma
Kolmogorov dynamics for heavy quarks in hot plasma shows significantly delayed large-momentum equilibration compared to Fokker-Planck with matched drag, due to rare low-momentum-loss events.
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Non-equilibrium Dynamical Attractors and Thermalisation of Charm Quarks in Nuclear Collisions at the LHC Energy
Charm quarks develop dynamical attractors in expanding QGP but with lattice-QCD diffusion coefficients require ~5 fm to relax, leading to O(1) deviations from equilibrium already at pT ~ 3 GeV and incomplete thermalization in small systems.