Analytic approach for the number statistics of non-Hermitian random matrices

Abstract

We introduce a powerful analytic method to study the statistics of the number ${\mathcal{N}}_{\text{A}}(\gamma )$ of eigenvalues inside any contour $\gamma \in \mathbb{C}$ for infinitely large non-Hermitian random matrices $\text{A}$. Our generic approach can be applied to different random matrix ensembles, even when the analytic expression for the joint distribution of eigenvalues is not known. We illustrate the method on the adjacency matrices of weighted random graphs with asymmetric couplings, for which standard random-matrix tools are inapplicable. The main outcome is an effective theory that determines the cumulant generating function of ${\mathcal{N}}_{\text{A}}$ via a path integral along $\gamma$, with the path probability distribution following from the solution of a self-consistent equation. We derive the expressions for the mean and the variance of ${\mathcal{N}}_{\text{A}}$ as well as for the rate function governing rare fluctuations of ${\mathcal{N}}_{\text{A}}(\gamma )$. All theoretical results are compared with direct diagonalization of finite random matrices, exhibiting an excellent agreement.

6 pages, 2 figures. SI as ancillary file

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Cited by in corpus (1)

• A smooth transition towards a Tracy-Widom distribution for the largest eigenvalue of interacting $k$-body fermionic Embedded Gaussian Ensembles