A new combinatorial approach for edge universality of Wigner matrices

TL;DR

This paper introduces a novel combinatorial method to prove edge universality of Wigner matrices with sub-Gaussian entries, avoiding symmetry assumptions and providing new insights into Tracy-Widom laws.

Contribution

The paper develops a new combinatorial encoding of contributing words for Wigner matrices, enabling proof of edge universality without symmetry assumptions, and offers a combinatorial perspective on Tracy-Widom laws.

Findings

Proves edge universality for Wigner matrices with sub-Gaussian entries.

Provides a combinatorial description of Tracy-Widom laws for GOE and GUE.

Introduces a new counting approach based on Dyck path-like objects.

Abstract

In this paper we introduce a new combinatorial approach to analyze the trace of large powers of Wigner matrices. Our approach is motivated from the paper by \citet{sosh}. However the counting approach is different. We start with classical word sentence approach similar to \citet{AZ05} and take the motivation from \citet{sinaisosh}, \citet{sosh} and \citet{peche2009universality} to encode the words to objects similar to Dyck paths. To be precise the map takes a word to a Dyck path with some edges removed from it. Using this new counting we prove edge universality for large Wigner matrices with sub-Gaussian entries. One novelty of this approach is unlike \citet{sinaisosh}, \citet{sosh} and \citet{peche2009universality} we do not need to assume the entries of the matrices are symmetrically distributed around $0$. The main technical contribution of this paper is two folded. Firstly we produce an encoding of the ``contributing words" (for definition one might look at Section \ref{sec:word}) of the Wigner matrix which retrieves the edge universality. Hence this is the best one can do. We hope this method will be applicable to many other scenarios in random matrices. Secondly in course of the paper we give a combinatorial description of the GOE Tracy Widom law. The explanation for GUE is very similar. This explanation might be important for the models where exact calculations are not available but some combinatorial structures are present.