Mean eigenvector self-overlap in the real and complex elliptic Ginibre ensembles at strong and weak non-Hermiticity

TL;DR

This paper derives exact formulas for the mean eigenvector overlap in elliptic Ginibre ensembles, analyzing its behavior under strong and weak non-Hermiticity regimes for finite and large matrix sizes.

Contribution

It provides the first finite-N exact expressions for eigenvector overlaps in elliptic Ginibre ensembles and explores their asymptotic behavior in different non-Hermiticity limits.

Findings

Exact finite-N formulas for eigenvector overlaps.

Asymptotic analysis in strong and weak non-Hermiticity regimes.

Insights into eigenvector behavior in non-Hermitian random matrices.

Abstract

We study the mean diagonal overlap of left and right eigenvectors associated with complex eigenvalues in $N\times N$ non-Hermitian random Gaussian matrices. In well known works by Chalker and Mehlig the expectation of this (self-)overlap was computed for the complex Ginibre ensemble as $N\to \infty$. In the present work, we consider the same quantity in the real and complex elliptic Ginibre ensembles characterized by correlations between off-diagonal entries controlled by a parameter $\tau\in[0,1]$, with $\tau=1$ corresponding to the Hermitian limit. We derive exact expressions for the mean diagonal overlap in both ensembles at any finite $N$, for any eigenvalue off the real axis. We further investigate several scaling regimes as $N\rightarrow \infty$, both in the limit of strong non-Hermiticity keeping a fixed $\tau\in[0,1)$ and in the weak non-Hermiticity limit, with $\tau$ approaching unity in such a way that $N(1-\tau)$ remains finite.