Eigenvector statistics in non-Hermitian random matrix ensembles

Details Eigenvector statistics in non-Hermitian random matrix ensembles Eigenvector statistics in non-Hermitian random matrix ensembles

1998-09-04

arxiv.org/abs/cond-mat/9809090v1

Phys. Rev. Lett. 81, 3367-3370 (1998)

Physics

Condensed Matter

Disordered Systems and Neural Networks

4 pages, no figures

Scientific paper

10.1103/PhysRevLett.81.3367

We study statistical properties of the eigenvectors of non-Hermitian random matrices, concentrating on Ginibre's complex Gaussian ensemble, in which the real and imaginary parts of each element of an N x N matrix, J, are independent random variables. Calculating ensemble averages based on the quantity $< L_\alpha | L_\beta > < R_\beta | R_\alpha >$, where $< L_\alpha |$ and $| R_\beta >$ are left and right eigenvectors of J, we show for large N that eigenvectors associated with a pair of eigenvalues are highly correlated if the two eigenvalues lie close in the complex plane. We examine consequences of these correlations that are likely to be important in physical applications.

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