arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2401.03249math-phmath.MP
收藏

实椭圆系综实特征值的条件数:边缘处的弱非正规性

Condition numbers for real eigenvalues of real elliptic ensemble: weak non-normality at the edge

Wojciech Tarnowski

AI总结:

本文在几乎 Hermite 且接近谱边缘的双重标度区域下,推导了实椭圆系综中实特征值与其条件数平方的联合概率密度函数的渐近表达式,并得到 Scorer 函数的单参数变形。

摘要:

特征值 $λ_i$ 对矩阵元素扰动的敏感性由特征值条件数控制,其定义为 $κ_i = \sqrt{\left< L_i | L_i\right> \left< R_i|R_i \right> }$,其中 $\left<L_i\right|$ 和 $\left|R_i\right>$ 是特征值 $λ_i$ 的左、右特征向量。在随机矩阵理论中,特征值条件数的平方也称为特征向量自重叠。在这项工作中,我们在几乎 Hermite 且接近谱边缘的双重标度区域下,计算了实椭圆系综的实特征值与相应特征值条件数平方的联合概率密度函数的渐近行为。作为副产品,我们还计算了 Scorer 函数的单参数变形。

英文摘要:

Sensitivity of an eigenvalue $λ_i$ to the perturbation of matrix elements is controlled by the eigenvalue condition number defined as $κ_i = \sqrt{\left< L_i | L_i\right> \left< R_i|R_i \right> }$, where $\left<L_i\right|$ and $\left|R_i\right>$ are left and right eigenvectors to the eigenvalue $λ_i$. In Random Matrix Theory the squared eigenvalue condition number is also known as the eigenvector self-overlap. In this work we calculate the asymptotics of the joint probability density function of the real eigenvalue and the square of the corresponding eigenvalue condition number for the real elliptic ensemble in the double scaling regime of almost Hermiticity and close to the edge of the spectrum. As a byproduct, we also calculate the one-parameter deformation of the Scorer's function.

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。

↑