Asymptotic distribution of singular values of powers of random matrices

preprint2010arXivOpen access

Abstract

Let xx be a complex random variable such that ${\E {x}=0}$, ${\E |x|^2=1}$, ${\E |x|^{4} < \infty}$. Let xijx_{ij}, i,j∈{1,2,...}i,j \in \{1,2,...\} be independet copies of xx. Let ${\Xb=(N^{-1/2}x_{ij})}$, 1≤i,j≤N1\leq i,j \leq N be a random matrix. Writing $\Xb^*$ for the adjoint matrix of $\Xb$, consider the product $\Xb^m{\Xb^*}^m$ with some m∈{1,2,...}m \in \{1,2,...\}. The matrix $\Xb^m{\Xb^*}^m$ is Hermitian positive semi-definite. Let λ1,λ2,...,λNλ_1,λ_2,...,λ_N be eigenvalues of $\Xb^m{\Xb^*}^m$ (or squared singular values of the matrix $\Xb^m$). In this paper we find the asymptotic distribution function \[ G^{(m)}(x)=\lim_{N\to\infty}\E{F_N^{(m)}(x)} \] of the empirical distribution function FN(m)(x)=N−1∑k=1NI{λk≤x}, {F_N^{(m)}(x)} = N^{-1} \sum_{k=1}^N {\mathbb{I}{\{λ_k \leq x\}}}, where I{A}\mathbb{I} \{A\} stands for the indicator function of event AA. The moments of G(m)G^{(m)} satisfy Mp(m)=∫RxpdG(m)(x)=1mp+1(mp+pp). M^{(m)}_p=\int_{\mathbb{R}}{x^p dG^{(m)}(x)}=\frac{1}{mp+1}\binom{mp+p}{p}. In Free Probability Theory Mp(m)M^{(m)}_p are known as Fuss--Catalan numbers. With m=1m=1 our result turns to a well known result of Marchenko--Pastur 1967.

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