New constraints for QCD matter from improved Bayesian parameter estimation in heavy-ion collisions at LHC
Parkkila, J. E., Onnerstad, A., Taghavi, S. F., Mordasini, C., Bilandzic, A., Virta, M., & Kim, D. J. (2022). New constraints for QCD matter from improved Bayesian parameter estimation in heavy-ion collisions at LHC. Physics Letters B, 835, Article 137485. https://doi.org/10.1016/j.physletb.2022.137485
Published inPhysics Letters B
© 2022 The Author(s). Published by Elsevier B.V.
The transport properties of quark-gluon plasma created in relativistic heavy-ion collisions are quantified by an improved global Bayesian analysis using the CERN Large Hadron Collider Pb–Pb data at sNN=2.76 and 5.02 TeV. The results show that the uncertainty of the extracted transport coefficients is significantly reduced by including new sophisticated collective flow observables from two collision energies for the first time. This work reveals the stronger temperature dependence of specific shear viscosity, a lower value of specific bulk viscosity, and a higher hadronization switching temperature than in the previous studies. The sensitivity analysis confirms that the precision measurements of higher-order harmonic flow and their correlations are crucial in extracting accurate values of the transport properties.
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Related funder(s)Academy of Finland
Funding program(s)Centre of Excellence, AoF
Additional information about fundingWe acknowledge CSC – IT Center for Science in Espoo, Finland, for the allocation of the computational resources. This research was completed using ∼64 million CPU hours provided by CSC. Three of us (SFT,CM, and AB) have received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (Grant Agreement No. 759257). AO, CM, MV and DJK are supported by the Academy of Finland, the Centre of Excellence in Quark Matter (project 346324). ...
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