Random matrices with independent entries: beyond non-crossing partitions

TL;DR

This paper extends the understanding of spectral distributions of random matrices with independent entries, generalizing beyond non-crossing partitions and unifying various existing results with new combinatorial insights.

Contribution

It introduces a unifying framework for the limiting spectral distribution of symmetric matrices with independent entries, expanding the combinatorial structures involved.

Findings

Limiting spectral distribution exists under suitable conditions.

Moments described by larger partition sets beyond non-crossing pair-partitions.

Results encompass and extend multiple existing random matrix models.

Abstract

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals the number of non-crossing pair-partitions of the set $\{1, 2, \ldots, 2k\}$. There are several extensions of this result in the literature. In this paper we consider a unifying extension which also yields additional results. Suppose $W_n$ is an $n\times n$ symmetric matrix where the entries are independently distributed. We show that under suitable assumptions on the entries, the limiting spectral distribution exists in probability or almost surely. The moments of the limit can be described through a set of partitions which in general is larger than the set of non-crossing pair-partitions. This set gives rise to interesting enumerative combinatorial problems. Several existing limiting spectral distribution results follow from our results. These include results on the standard Wigner matrix, the adjacency matrix of a sparse homogeneous Erd\H{o}s-R\'{e}nyi graph, heavy tailed Wigner matrix, some banded Wigner matrices, and Wigner matrices with variance profile. Some new results on these models and their extensions also follow from our main results.