Phenomenological Constraints on the Transport Properties of QCD Matter with Data-Driven Model Averaging
Name
PhysRevLett.126.242301.pdf
Description
Published version
Size
631.99 KB
Format
Adobe PDF
Checksum (MD5)
bbcbb449e1ea5a4806187380a9b0e203
Author(s)
Roland, Gunther
Chen, Y.
Date Issued
2021
Journal
Physical Review Letters
Publisher
American Physical Society (APS)
Citation
Roland, Gunther. 2021. "Phenomenological Constraints on the Transport Properties of QCD Matter with Data-Driven Model Averaging." Physical Review Letters, 126 (24).
Version
Final published version
Abstract
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150-350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma's final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
MIT Department
Massachusetts Institute of Technology. Laboratory for Nuclear Science
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1103/PHYSREVLETT.126.242301
