Pfaffian structure of the eigenvector overlap for the symplectic Ginibre ensemble

TL;DR

This paper investigates the eigenvector overlaps in the symplectic Ginibre ensemble, deriving Pfaffian formulas, analyzing scaling limits, and exploring the effects of boundary conditions and weight perturbations on eigenvector statistics.

Contribution

It provides a detailed Pfaffian structure and skew-orthogonal polynomial analysis for the eigenvector overlaps, extending results to real line conditioning and large matrix limits.

Findings

Derived Pfaffian formulas for eigenvector overlaps.

Analyzed bulk and edge scaling limits of eigenvalue correlations.

Identified effects of weight perturbations on eigenvector statistics.

Abstract

We study the integrable structure and scaling limits of the conditioned eigenvector overlap of the symplectic Ginibre ensemble of Gaussian non-Hermitian random matrices with independent quaternion elements. The average of the overlap matrix elements constructed from left and right eigenvectors, conditioned to $x$, are derived in terms of a Pfaffian determinant. Regarded as a two-dimensional Coulomb gas with the Neumann boundary condition along the real axis, it contains a kernel of skew-orthogonal polynomials with respect to the weight function $\omega^{(\mathrm{over})}(z)=|z-\overline{x}|^2(1+|z-x|^2)e^{-2|z|^2}$, including a non-trivial insertion of a point charge. The mean off-diagonal overlap is related to the diagonal (self-)overlap by a transposition, in analogy to the complex Ginibre ensemble. For $x$ conditioned to the real line, extending previous results at $x=0$, we determine the skew-orthogonal polynomials and their skew-kernel with respect to $\omega^{(\mathrm{over})}(z)$. This is done in two steps and involves a Christoffel perturbation of the weight $\omega^{(\mathrm{over})}(z)=|z-\overline{x}|^2\omega^{(\mathrm{pre})}(z)$, by computing first the corresponding quantities for the unperturbed weight $\omega^{(\mathrm{pre})}(z)$. Its kernel is shown to satisfy a differential equation at finite matrix size $N$. This allows us to take different large-$N$ limits, where we distinguish bulk and edge regime along the real axis. The limiting mean diagonal overlaps and corresponding eigenvalue correlation functions of the point processes with respect to $\omega^{(\mathrm{over})}(z)$ are determined. We also examine the effect on the planar orthogonal polynomials when changing the variance in $\omega^{(\mathrm{pre})}(z)$, as this appears in the eigenvector statistics of the complex Ginibre ensemble.