Journal
PHYSICAL REVIEW C
Volume 104, Issue 5, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevC.104.054904
Keywords
-
Categories
Funding
- SCOAP3
Ask authors/readers for more resources
The study reveals that the temperature dependence of the specific shear viscosity in the strongly coupled quark-gluon plasma created in ultrarelativistic heavy-ion collisions is weaker than previously thought. To reproduce additional observables, lower values of specific bulk viscosity and higher switching temperatures are preferred. The analysis benefits the most from using symmetric cumulants and nonlinear flow modes to constrain the temperature dependence of specific shear and bulk viscosities.
The transport properties of the strongly coupled quark-gluon plasma created in ultrarelativistic heavy-ion collisions are extracted by Bayesian parameter estimate methods with the latest collision beam energy data from the CERN Large Hadron Collider. This Bayesian analysis includes sophisticated flow harmonic observables for the first time. We found that the temperature dependence of specific shear viscosity appears weaker than in the previous studies. The results prefer a lower value of specific bulk viscosity and a higher switching temperature to reproduce additional observables. However, the improved statistical uncertainties both on the experimental data and hydrodynamic calculations with additional observables do not help to reduce the final credibility ranges much, indicating a need for improving the dynamical collision model before the hydrodynamic takes place. In addition, the sensitivities of experimental observables to the parameters in hydrodynamic model calculations are quantified. It is found that the analysis benefits most from the symmetric cumulants and nonlinear flow modes, which mostly reflect nonlinear hydrodynamic responses, in constraining the temperature dependence of the specific shear and bulk viscosities in addition to the previously used flow coefficients.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available