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2024年10月30日

Anisotropic flow of Pb+Pb √sNN=5.02 TeV from a multi-phase transport model

  • Anisotropic flow is an important observable in the study of the quark-gluon plasma that is expected to be formed in heavy-ion collisions. With a multiphase transport (AMPT) model we investigate the elliptic (v2), triangular (v3), and quadrangular (v4) flow of charged particles in Pb+Pb collisions at √sNN=5.02 TeV. We then compare our flow results with the published ALICE flow results. We find our AMPT simulated results are consistent with ALICE experimental data.
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Get Citation
Zhao Feng, Guang-Ming Huang and Feng Liu. Anisotropic flow of Pb+Pb √sNN=5.02 TeV from a multi-phase transport model[J]. Chinese Physics C, 2017, 41(2): 024001. doi: 10.1088/1674-1137/41/2/024001
Zhao Feng, Guang-Ming Huang and Feng Liu. Anisotropic flow of Pb+Pb √sNN=5.02 TeV from a multi-phase transport model[J]. Chinese Physics C, 2017, 41(2): 024001.  doi: 10.1088/1674-1137/41/2/024001 shu
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Received: 2016-07-11
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    Supported by National Natural Science Foundation of China (11221504, 11420101004) and MOST of China 973 (2015CB856901)

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Anisotropic flow of Pb+Pb √sNN=5.02 TeV from a multi-phase transport model

    Corresponding author: Zhao Feng,
    Corresponding author: Guang-Ming Huang,
    Corresponding author: Feng Liu,
  • 1. Key Laboratory of Quark and Lepton Physics(MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China
Fund Project:  Supported by National Natural Science Foundation of China (11221504, 11420101004) and MOST of China 973 (2015CB856901)

Abstract: Anisotropic flow is an important observable in the study of the quark-gluon plasma that is expected to be formed in heavy-ion collisions. With a multiphase transport (AMPT) model we investigate the elliptic (v2), triangular (v3), and quadrangular (v4) flow of charged particles in Pb+Pb collisions at √sNN=5.02 TeV. We then compare our flow results with the published ALICE flow results. We find our AMPT simulated results are consistent with ALICE experimental data.

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