Limiting eigenvalue distribution of random matrices of Ihara zeta function of long-range percolation graphs

TL;DR

This paper studies the eigenvalue distribution of random matrices derived from Ihara zeta functions of long-range percolation graphs, showing convergence to a measure related to the graph's degree distribution, connecting to the Wigner semi-circle law.

Contribution

It introduces a new ensemble of random matrices from Ihara zeta functions of long-range percolation graphs and analyzes their eigenvalue distribution in the large size limit.

Findings

Eigenvalue distribution converges to a measure depending on the average vertex degree.

In the limit of large degree, the distribution approaches a shifted Wigner semi-circle.

Results relate to properties of the Ihara zeta function and the graph Riemann Hypothesis.

Abstract

We consider the ensemble of $N\times N$ real random symmetric matrices $H_N^{(R)}$ obtained from the determinant form of the Ihara zeta function associated to random graphs $\Gamma_N^{(R)}$ of the long-range percolation radius model with the edge probability determined by a function $\phi(t)$. We show that the normalized eigenvalue counting function of $H_N^{( R)}$ weakly converges in average as $N,R\to\infty$, $R=o(N)$ to a unique measure that depends on the limiting average vertex degree of $\Gamma_N^{(R)}$ given by $\phi_1 = \int \phi(t) dt$. This measure converges in the limit of infinite $\phi_1$ to a shift of the Wigner semi-circle distribution. We discuss relations of these results with the properties of the Ihara zeta function and weak versions of the graph theory Riemann Hypothesis.