arXivDaily arXiv每日学术速递 周一至周五更新
arXiv math/0502400math.PR
收藏

非厄米特随机矩阵系综的高斯涨落

Gaussian fluctuations for non-Hermitian random matrix ensembles

B. Rider, Jack W. Silverstein

摘要:

考虑一个$N\times N$非厄米特矩阵的系综,其中所有元素都是独立同分布的复随机变量,平均值为零,绝对均方值为1。如果入口分布也具有有界密度和有限的$(4+ε)$矩,则Z. D. Bai [Ann. 25(1997)494- 529]已经表明,系综满足循环定律:在以因子$1/\sqrt{N}$缩放并令$N\to \infty$之后,本征值的经验测度弱地收敛到复平面中单位圆盘上的一致测度。本文研究了一类更严格的非厄米特矩阵的循环律的涨落,对于这类矩阵,高阶矩满足增长条件。主要结果是$X_N(f)=\sum_{k=1}^Nf(λ_k)$型线性统计量的中心极限定理,其中$λ_1,λ_2,...,λ_N$表示系综特征值,检验函数$f$在适当的区域上是解析的.证明的灵感来自白和Silverstein [安。32(2004)533- 605],其中建立了随机样本协方差阵的类似结果。

英文摘要:

Consider an ensemble of $N\times N$ non-Hermitian matrices in which all entries are independent identically distributed complex random variables of mean zero and absolute mean-square one. If the entry distributions also possess bounded densities and finite $(4+ε)$ moments, then Z. D. Bai [Ann. Probab. 25 (1997) 494--529] has shown the ensemble to satisfy the circular law: after scaling by a factor of $1/\sqrt{N}$ and letting $N\to \infty$, the empirical measure of the eigenvalues converges weakly to the uniform measure on the unit disk in the complex plane. In this note, we investigate fluctuations from the circular law in a more restrictive class of non-Hermitian matrices for which higher moments of the entries obey a growth condition. The main result is a central limit theorem for linear statistics of type $X_N(f)=\sum_{k=1}^Nf(λ_k)$ where $λ_1,λ_2,...,λ_N$ denote the ensemble eigenvalues and the test function $f$ is analytic on an appropriate domain. The proof is inspired by Bai and Silverstein [Ann. Probab. 32 (2004) 533--605], where the analogous result for random sample covariance matrices is established.

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。

↑