Assessing the ultra-central flow puzzle in the Bayesian era

ORAL

Abstract

An outstanding problem in heavy-ion collisions is the inability for models to accurately describe ultra-central experimental flow data, despite that being precisely the regime where a hydrodynamic description is most applicable. We reassess the status of this puzzle by computing the flow in ultra-central collisions obtained from multiple recent Bayesian models that were tuned to various observables in different collision systems at typical centralities. While central data can now be described with better accuracy than in previous calculations, tension with experimental observation remains and worsens as one goes to ultra-central collisions. Tuning the model parameters cannot remove this tension without destroying the fit at other centralities. Our results show that the ultra-central flow puzzle cannot be resolved by state-of-the-art simulations, suggesting that modifications are needed in the standard modeling of heavy-ion collisions.

*This work has been supported by the Sao Paulo Research Foundation (FAPESP) under projects 2017/05685-2 (all), 2021/04924-9 (A.V.G.), 2020/12795-1 (M.N.F.), 2016/24029-6, 2018/24720-6, 2021/08465-9 (M.L.), and 2018/01245-0 (T.N.dS.). D.D.C., G.S.D, M.L. and J.T. thank CNPq for financial support. J.N. is partially supported by the U.S. Department of Energy, Office of Science, Office for Nuclear Physics under Award No. DE-SC0021301. G.S.D. acknowledges financial support from the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), process No. E-26/202.747/2018. M.H. was supported in part by the National Science Foundation (NSF) within the framework of the MUSES collaboration, under grant number OAC-2103680.

Publication: https://arxiv.org/abs/2203.17011

Presenters

  • Maurício T Hippert

    • University of Illinois at Urbana-Champaign

Authors

  • Maurício T Hippert

    • University of Illinois at Urbana-Champaign
  • André Veiga Giannini

    • Campinas State University
  • Mauricio Narciso Ferreira

    • Campinas State University
  • David Dobrigkeit Chinellato

    • Campinas State University
  • Gabriel S Denicol

    • Fluminense Federal University
  • Matthew Luzum

    • University of Sao Paulo
  • Jorge Noronha

    • University of Illinois at Urbana-Champaign
  • Tiago Nunes da Silva

    • Santa Catarina Federal University
  • Jun Takahashi

    • Campinas State University