On the spectral radius of the ratio of Girko matrices

TL;DR

This paper proves that the spectral radius of the ratio of two independent Girko matrices, when scaled by the square root of the dimension, converges to a universal heavy-tailed distribution as the dimension grows large.

Contribution

It establishes the universality of the spectral radius distribution for the ratio of Girko matrices, extending known results from the Gaussian case to a broader heavy-tailed setting.

Findings

Spectral radius converges to a universal heavy-tailed distribution.

Invariance under inversion relates edge and bulk spectra.

Universality is more accessible in the ratio model than in single Girko matrices.

Abstract

Girko matrices have independent and identically distributed entries of mean zero and unit variance. In this note, we consider the random matrix model formed by the ratio of two independent Girko matrices, its entries are dependent and heavy-tailed. Our main message is that divided by the square root of the dimension, the spectral radius of the ratio converges in distribution, when the dimension tends to infinity, to a universal heavy-tailed distribution. We provide a mathematical proof of this high-dimensional phenomenon, under a fourth moment matching with a Gaussian case known as the complex Ginibre ensemble. In this Gaussian case, the model is known as the spherical ensemble, and its spectrum is a determinantal planar Coulomb gas. Its image by the inverse stereographic projection is a rotationally invariant gas on the two-sphere. A crucial observation is the invariance in law of the model under inversion, related to its spherical symmetry, and that makes, in a sense, edge and bulk equivalent. Our approach involves Girko Hermitization, local law estimates for Wigner matrices, lower bound estimates on the smallest singular value, and convergence of kernels of determinantal point processes. The universality of the high-dimensional fluctuation of the spectral radius of the ratio of Girko matrices turns out to be remarkably more accessible mathematically than for a single Girko matrix!