Transport Properties of QGP within a Bayesian Holographic QCD Model

TL;DR

This work addresses the nonperturbative transport properties of the quark-gluon plasma by marrying a five-dimensional Einstein–Maxwell–dilaton holographic model with Bayesian inference. The authors calibrate the holographic model to lattice thermodynamics, obtaining posterior distributions for the six EMD parameters and using them to compute the heavy-quark drag force, heavy-quark diffusion, jet quenching parameter, and the bulk and shear viscosities across finite temperature and chemical potential. The results show that diffusion nearly matches lattice QCD and ALICE data at high temperatures, while jet quenching and viscosity features capture the expected temperature dependence near the deconfinement transition, including a bulk-viscosity peak near Tc and a dip in η/s around 1.2 Tc when higher-derivative corrections are included. Overall, the Bayesian holographic approach provides a statistically controlled, nonperturbative framework for extracting QGP transport properties and offers a consistent backbone for embedding into phenomenological transport simulations for heavy-ion collisions.

Abstract

Using a holographic QCD model augmented by Bayesian inference, we calculate key transport coefficients of the quark-gluon plasma (QGP)$\text{-}$including the drag force, jet quenching parameter, heavy quark diffusion coefficient, and shear and bulk viscosities$\text{-}$at finite temperature and chemical potential. Posterior parameter distributions at the 68\% and 95\% confidence levels (CL), as well as the maximum a posteriori (MAP) estimates, are employed to quantify uncertainties. Our findings indicate that the diffusion coefficient within the Bayesian credible regions aligns with lattice QCD results for $T \sim 1.2T_c$ to $2T_c$, and is consistent with ALICE experimental measurements near $T_c$. The jet quenching parameter obtained from the Bayesian analysis agrees with RHIC and LHC data, while viscosity coefficients show compatibility with existing literature. These results demonstrate the efficacy of a Bayesian holographic approach in elucidating the nonperturbative transport properties of QCD matter.

Figures (13)

• Figure 1: In a 2+1 flavor system at zero chemical potential with the quark velocity set to $v = 0.3$, drag force as a function of temperature is examined. (a) The gray area represents the variation of drag force with temperature at the 95% CL; (b) the gray area represents the variation of drag force with temperature at the 68% CL. The red curve shows the variation of drag force with temperature at the MAP values.
• Figure 2: In a 2+1 flavor system at zero chemical potential and at the critical temperature $T_c = 0.128$ GeV, drag force as a function of velocity is investigated. (a) The gray area represents the variation of drag force with velocity at the 95% CL; (b) the gray area represents the variation of drag force with velocity at the 68% CL. The red curve shows the variation of drag force with velocity at the MAP values.
• Figure 3: Energy loss of the bottom quark ($m_b = 4.7 \enspace \rm GeV$) and charm quark ($m_c = 1.3 \enspace \rm GeV$) as a function of momentum $p$ (in GeV) at temperature $T=T_c$. (a) The gray area represents the relationship between energy loss and momentum at the 95% CL. (b) The gray area represents the relationship between energy loss and momentum at the 68% CL. The red and blue curve shows the results at the MAP values.
• Figure 4: Energy loss of the bottom quark ($m_b = 4.7 \enspace \rm GeV$) and charm quark ($m_c = 1.3 \enspace \rm GeV$) as a function of momentum $p$ (in GeV) at temperature $T=2T_c$. (a) The gray area represents the relationship between energy loss and momentum at the 95% CL. (b) The gray area represents the relationship between energy loss and momentum at the 68% CL. The red and blue curve shows the results at the MAP values.
• Figure 5: In the 2+1 flavor system at zero chemical potential, with the quark velocity set to $v = 0.3$, the variation of the scaled diffusion coefficient $D/D_{SYM}$ with temperature can be described as follows. (a) The gray area represents the variation of $D/D_{SYM}$ with temperature at the 95% CL ; (b) the gray area represents the variation of $D/D_{SYM}$ with temperature at the 68% CL. The red curve shows the variation of $D/D_{SYM}$ with temperature at the MAP values.