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arXiv 2103.05402math.PRmath-phmath.MPmath.STstat.TH
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Wigner矩阵线性eigenvalue统计量的定量CLT

Quantitative CLT for linear eigenvalue statistics of Wigner matrices

Zhigang Bao, Yukun He

摘要:

在这篇文章中,我们建立了一个接近最佳的收敛速度的线性特征值统计的Wigner矩阵的CLT,Kolmogorov-Smirnov距离。对于所有的检验函数$f\in C^5(\mathbb R)$,我们表明,收敛速度是$N^{-1/2+\varepsilon}$或$N^{-1+\varepsilon}$,取决于第一切比雪夫系数的$f$和第三时刻的对角矩阵条目。区分这两个速率的条件是必要和充分的。对于一般的检验函数类,我们进一步确定匹配的收敛速度的下界。此外,我们确定了一个明确的,非普遍的贡献,在线性特征值统计,这是负责慢速率$N^{-1/2+\varepsilon}$的非高斯合奏。通过去掉这个非普适部分,我们证明了移位线性特征值统计量对所有检验函数具有统一的收敛速度$N^{-1+\varepsilon}$。

英文摘要:

In this article, we establish a near-optimal convergence rate for the CLT of linear eigenvalue statistics of Wigner matrices, in Kolmogorov-Smirnov distance. For all test functions $f\in C^5(\mathbb R)$, we show that the convergence rate is either $N^{-1/2+\varepsilon}$ or $N^{-1+\varepsilon}$, depending on the first Chebyshev coefficient of $f$ and the third moment of the diagonal matrix entries. The condition that distinguishes these two rates is necessary and sufficient. For a general class of test functions, we further identify matching lower bounds for the convergence rates. In addition, we identify an explicit, non-universal contribution in the linear eigenvalue statistics, which is responsible for the slow rate $N^{-1/2+\varepsilon}$ for non-Gaussian ensembles. By removing this non-universal part, we show that the shifted linear eigenvalue statistics have the unified convergence rate $N^{-1+\varepsilon}$ for all test functions.

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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