Determination of the mean-field momentum-dependence using elliptic flow

被引:222
作者
Danielewicz, P [1 ]
机构
[1] Michigan State Univ, Natl Superconducting Cyclotron Lab, E Lansing, MI 48824 USA
[2] Michigan State Univ, Dept Phys & Astron, E Lansing, MI 48824 USA
基金
美国国家科学基金会;
关键词
reactions; transport theory; flow; optical potential; mean field; momentum dependence;
D O I
10.1016/S0375-9474(00)00083-X
中图分类号
O57 [原子核物理学、高能物理学];
学科分类号
070202 ;
摘要
Midrapidity nucleon elliptic how is studied within the Boltzmann-equation simulations of symmetric heavy-ion collisions. The simulations follow a lattice Hamiltonian extended to relativistic transport. It is demonstrated that in the peripheral heavy-ion collisions the high-momentum elliptic how is strongly sensitive to the momentum dependence of mean field at supranormal densities. The high transverse-momentum particles are directly and exclusively emitted from the high-density zone in the collisions, while remaining particles primarily continue along the beam axis. The elliptic flow was measured by the KaOS Collaboration as a function of the transverse momentum at a number of impact parameters in Bi + Bi collisions at 400, 700, and 1000 MeV/nucleon. The observed elliptic anisotropies in peripheral collisions, which quickly rise with momentum; can only be explained in simulations when assuming a strong momentum dependence of nucleonic mean field. This momentum dependence must strengthen with the rise of density above normal. The mean-field parametrizations, which describe the data in simulations with various success, are confronted with mean fields from microscopic nuclear-matter calculations. Two of the microscopic potentials in the comparisons have unacceptably weak momentum-dependencies at supranormal densities. The optical potentials from the Dirac-Brueckner-Hartree-Fock calculations, on the other hand, together with the UV14 + TNI potential from variational calculations, agree rather well within the region of sensitivity with the parametrized potentials that best describe the data. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:375 / 410
页数:36
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