Institut für Theoretische Physik 1, Universität Stuttgart, 70550 Stuttgart, Germany.
Phys Rev E. 2017 Nov;96(5-1):052217. doi: 10.1103/PhysRevE.96.052217. Epub 2017 Nov 21.
Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.
到目前为止,只有在泊松统计(P)、高斯正交系综(GOE)的统计或高斯酉系综(GUE)的统计之间的特定交叉中,随机矩阵理论才推导出了能级间距分布函数的解析公式。我们研究了这三种统计之间的任意交叉。为此,我们提出了一个依赖于两个参数的能级间距分布函数公式。将我们的公式在 P→GUE、P→GOE 和 GOE→GUE 这些特殊情况下的行为与随机矩阵理论的结果进行比较,我们证明了这些交叉得到了合理的描述。F. Schweiner 等人最近的研究[Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205]表明,立方半导体中磁激子的哈密顿量可以根据系统参数表现出所有三种统计。在依赖于激发能量和与立方价带结构相关的参数评估磁激子的数值结果,并将结果与所提出的公式进行比较,可以区分规则和混沌行为以及存在或破坏的反幺正对称性。增加两个参数之一,就会观察到并讨论不同交叉之间的跃迁,例如从 P→GOE 到 P→GUE 的交叉。