Burda Zdzisław, Jurkiewicz Jerzy, Nowak Maciej A, Papp Gabor, Zahed Ismail
Marian Smoluchowski Institute of Physics, Jagiellonian University, 30-059 Kraków, Reymonta 4, Poland.
Phys Rev E Stat Nonlin Soft Matter Phys. 2007 May;75(5 Pt 1):051126. doi: 10.1103/PhysRevE.75.051126. Epub 2007 May 30.
We compare eigenvalue densities of Wigner random matrices whose elements are independent identically distributed random numbers with a Lévy distribution and maximally random matrices with a rotationally invariant measure exhibiting a power law spectrum given by stable laws of free random variables. We compute the eigenvalue density of Wigner-Lévy matrices using (and correcting) the method by Bouchaud and Cizeau, and of free random Lévy (FRL) rotationally invariant matrices by adapting results of free probability calculus. We compare the two types of eigenvalue spectra. Both ensembles are spectrally stable with respect to the matrix addition. The discussed ensemble of FRL matrices is maximally random in the sense that it maximizes Shannon's entropy. We find a perfect agreement between the numerically sampled spectra and the analytical results already for matrices of dimension N=100 . The numerical spectra show very weak dependence on the matrix size N as can be noticed by comparing spectra for N=400 . After a pertinent rescaling, spectra of Wigner-Lévy matrices and of symmetric FRL matrices have the same tail behavior. As we discuss towards the end of the paper the correlations of large eigenvalues in the two ensembles are, however, different. We illustrate the relation between the two types of stability and show that the addition of many randomly rotated Wigner-Lévy matrices leads by a matrix central limit theorem to FRL spectra, providing an explicit realization of the maximal randomness principle.
我们比较了维格纳随机矩阵的特征值密度,其元素是具有 Lévy 分布的独立同分布随机数,以及具有旋转不变测度的最大随机矩阵,该矩阵呈现出由自由随机变量的稳定定律给出的幂律谱。我们使用(并修正)Bouchaud 和 Cizeau 的方法计算维格纳 - Lévy 矩阵的特征值密度,并通过改编自由概率计算的结果来计算自由随机 Lévy(FRL)旋转不变矩阵的特征值密度。我们比较了这两种类型的特征值谱。这两个系综对于矩阵加法在谱上都是稳定的。所讨论的 FRL 矩阵系综在最大化香农熵的意义上是最大随机的。我们发现,对于维度(N = 100)的矩阵,数值采样谱与解析结果已经完全吻合。通过比较(N = 400)时的谱可以注意到,数值谱对矩阵大小(N)的依赖性非常弱。经过适当的重新缩放后,维格纳 - Lévy 矩阵和对称 FRL 矩阵的谱具有相同的尾部行为。然而,正如我们在论文结尾所讨论的,这两个系综中大特征值的相关性是不同的。我们说明了这两种稳定性之间的关系,并表明通过矩阵中心极限定理,添加许多随机旋转的维格纳 - Lévy 矩阵会导致 FRL 谱,从而提供了最大随机性原理的明确实现。