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arXiv 0709.0036math.PR
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非中心随机矩阵的循环律

Circular law for non-central random matrices

Djalil Chafai

摘要:

设$(X_{jk})_{j,k\geq 1}$是i.i.d.的无限数组。复杂随机变量,均值为0,方差为1。令$\la_{n,1},...,\la_{n,n}$是$(\frac{1}{\sqrt{n}}X_{jk})_{1\leq j,k\leq n}$的特征值。强循环律定理指出,在概率为1的情况下,经验谱分布$\frac{1}{n}(\de_{\la_{n,1}}+...+\de_{\la_{n,n}})$弱收敛为单位圆$\{z\in\dC;|z|\leq1\}$上的均匀律$n\to\infty$。在这个简短的说明中,我们提供了一个基本的参数,允许添加一个确定性矩阵$M$到$(X_{jk})_{1\leq j,k\leq n}$,如果$\mathrm{Tr}(MM^*)=O(n^2)$和$\mathrm{rank}(M)=O(n^\al)$与$\al<1$。方便的是,这个论证类似于维格纳定理和马琴科-帕斯托尔定理的非中心版本。

英文摘要:

Let $(X_{jk})_{j,k\geq 1}$ be an infinite array of i.i.d. complex random variables, with mean 0 and variance 1. Let $\la_{n,1},...,\la_{n,n}$ be the eigenvalues of $(\frac{1}{\sqrt{n}}X_{jk})_{1\leq j,k\leq n}$. The strong circular law theorem states that with probability one, the empirical spectral distribution $\frac{1}{n}(\de_{\la_{n,1}}+...+\de_{\la_{n,n}})$ converges weakly as $n\to\infty$ to the uniform law over the unit disc $\{z\in\dC;|z|\leq1\}$. In this short note, we provide an elementary argument that allows to add a deterministic matrix $M$ to $(X_{jk})_{1\leq j,k\leq n}$ provided that $\mathrm{Tr}(MM^*)=O(n^2)$ and $\mathrm{rank}(M)=O(n^\al)$ with $\al<1$. Conveniently, the argument is similar to the one used for the non-central version of Wigner's and Marchenko-Pastur theorems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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