Signatures of α-clustering in O16 by using a multiphase transport model

Yi-An Li (李逸安), Song Zhang (张松), and Yu-Gang Ma (马余刚)
Phys. Rev. C 102, 054907 – Published 11 November 2020

Abstract

α-clustered structures in light nuclei could be studied through “snapshots” taken by relativistic heavy-ion collisions. A multiphase transport model is employed to simulate the initial structure of collision nuclei and the proceeding collisions at center of mass energy sNN=6.37 TeV. This initial structure can finally be reflected in the subsequent observations, such as elliptic flow (v2), triangular flow (v3), and quadrangular flow (v4). Three sets of the collision systems are chosen to illustrate that the system scan is a good way to identify the exotic α-clustered nuclear structure: case I, O16 nucleus (with or without α-cluster) + ordinary nuclei (always in Woods-Saxon distribution) in most central collisions; case II, O16 nucleus (with or without α-cluster) + Au197 nucleus collisions for centrality dependence; and case III, symmetric collision systems [namely, B10 + B10, C12 + C12, O16 + O16 (with or without α-cluster), Ne20 + Ne20, and Ca40 + Ca40] in most central collisions. Our calculations propose that relativistic heavy-ion collision experiments at sNN=6.37 TeV are promised to distinguish the tetrahedral structure of O16 from the Woods-Saxon one and shed light on the system scan projects in experiments.

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  • Received 29 May 2020
  • Accepted 19 October 2020

DOI:https://doi.org/10.1103/PhysRevC.102.054907

©2020 American Physical Society

Physics Subject Headings (PhySH)

Nuclear Physics

Authors & Affiliations

Yi-An Li (李逸安)1,2,3, Song Zhang (张松)2,*, and Yu-Gang Ma (马余刚)2,1,†

  • 1Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Fudan University, Shanghai 200433, China
  • 3School of Nuclear Sciences and Technology, University of Chinese Academy of Sciences, Beijing 100049, China

  • *song_zhang@fudan.edu.cn
  • mayugang@fudan.edu.cn

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Vol. 102, Iss. 5 — November 2020

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