Non-Gaussian Non-Hermitean Random Matrix Theory: phase transitions and addition formalism

TL;DR

This paper extends non-Hermitian random matrix theory to non-Gaussian distributions using hermitization, revealing phase transitions in eigenvalue distributions and developing an addition formalism for free non-Hermitian variables.

Contribution

It introduces a general formalism for non-Hermitian non-Gaussian matrices, including phase transition analysis and a non-Hermitian central limit theorem.

Findings

Eigenvalue distribution shapes are either disks or annuli.

Phase transition from disk to annular eigenvalue distribution.

Development of addition formalism for free non-Hermitian variables.

Abstract

We apply the recently introduced method of hermitization to study in the large $N$ limit non-hermitean random matrices that are drawn from a large class of circularly symmetric non-Gaussian probability distributions, thus extending the recent Gaussian non-hermitean literature. We develop the general formalism for calculating the Green's function and averaged density of eigenvalues, which may be thought of as the non-hermitean analog of the method due to Br\`ezin, Itzykson, Parisi and Zuber for analyzing hermitean non-Gaussian random matrices. We obtain an explicit algebraic equation for the integrated density of eigenvalues. A somewhat surprising result of that equation is that the shape of the eigenvalue distribution in the complex plane is either a disk or an annulus. As a concrete example, we analyze the quartic ensemble and study the phase transition from a disk shaped eigenvalue distribution to an annular distribution. Finally, we apply the method of hermitization to develop the addition formalism for free non-hermitean random variables. We use this formalism to state and prove a non-abelian non-hermitean version of the central limit theorem.