Singular Values Distribution of Squares of Elliptic Random Matrices and Type B Narayana Polynomials

被引:0
作者
Nikita Alexeev
Alexander Tikhomirov
机构
[1] St. Petersburg State University,Chebyshev Laboratory
[2] George Washington University,undefined
[3] Department of Mathematics,undefined
[4] Komi Science Center of Ural Division of RAS,undefined
[5] Syktyvkar State University,undefined
来源
Journal of Theoretical Probability | 2017年 / 30卷
关键词
Random matrices; Elliptic law; Singular values ; Fuss–Catalan numbers; Narayana numbers; Type B; 60F05; 15B52;
D O I
暂无
中图分类号
学科分类号
摘要
We consider Gaussian elliptic random matrices X of a size N×N\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N \times N$$\end{document} with parameter ρ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho $$\end{document}, i.e., matrices whose pairs of entries (Xij,Xji)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(X_{ij}, X_{ji})$$\end{document} are mutually independent Gaussian vectors with EXij=0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbb {E}\,X_{ij} = 0$$\end{document}, EXij2=1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbb {E}\,X^2_{ij} = 1$$\end{document} and EXijXji=ρ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbb {E}\,X_{ij} X_{ji} = \rho $$\end{document}. We are interested in the asymptotic distribution of eigenvalues of the matrix W=1N2X2X∗2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$W =\frac{1}{N^2} X^2 X^{*2}$$\end{document}. We show that this distribution is determined by its moments, and we provide a recurrence relation for these moments. We prove that the (symmetrized) asymptotic distribution is determined by its free cumulants, which are Narayana polynomials of type B: c2n=∑k=0nnk2ρ2k.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{aligned} c_{2n} = \sum _{k=0}^n {\left( {\begin{array}{c}n\\ k\end{array}}\right) }^2 \rho ^{2k}. \end{aligned}$$\end{document}
引用
收藏
页码:1170 / 1190
页数:20
相关论文
共 41 条
[1]  
Akemann G(2013)Products of rectangular random matrices: singular values and progressive scattering Phys. Rev. E 88 052118-132
[2]  
Ipsen JR(2010)Asymptotic distribution of singular values of powers of random matrices Lith. Math. J. 50 121-507
[3]  
Kieburg M(2010)On the singular spectrum of powers and products of random matrices Dokl. Math. 82 505-13
[4]  
Alexeev N(2012)Product of free random variables and k-divisible noncrossing partitions Electron. Commun. Probab. 17 1-37
[5]  
Götze F(2011)Free Bessel laws Can. J. Math. 63 3-2303
[6]  
Tikhomirov A(2003)Non-crossing cumulants of type B Trans. Am. Math. Soc. 355 2263-651
[7]  
Alexeev N(2014)Eigenvalue statistics for product complex Wishart matrices J. Phys. A Math. Theor. 47 345202-102
[8]  
Götze F(1985)The elliptic law Teoriya Veroyatnostei i ee Primeneniya 30 640-320
[9]  
Tikhomirov A(2006)The strong elliptic law. Twenty years later. Part I Random Oper. Stoch. Equ. 14 59-3738
[10]  
Arizmendi O(2014)Limit distributions of random matrices Adv. Math. 263 253-536