Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma with additional flow harmonic observables
Parkkila, J. E., Önnerstad, A., & Kim, D. J. (2021). Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma with additional flow harmonic observables. Physical Review C, 104(5), Article 054904. https://doi.org/10.1103/PhysRevC.104.054904
Julkaistu sarjassa
Physical Review CPäivämäärä
2021Tekijänoikeudet
© Authors, 2021
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.
...
Julkaisija
American Physical SocietyISSN Hae Julkaisufoorumista
2469-9985Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/102267709
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We acknowledge CSC-IT Center for Science in Espoo, Finland, for the allocation of the computational resources.Lisenssi
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