The Spectral Gap of Sparse Random Digraphs

TL;DR

This paper establishes an asymptotic upper bound for the second eigenvalue of transition matrices of simple random walks on sparse directed graphs, advancing understanding of spectral gaps in non-reversible Markov chains.

Contribution

It provides the first asymptotic analysis of the spectral gap for sparse non-reversible Markov chains with unknown stationary distributions, proving the Alon conjecture for directed regular graphs.

Findings

Derived an asymptotic upper bound for the second eigenvalue.

Proved the Alon conjecture for directed regular graphs.

Extended the trace method to analyze spectral properties.

Abstract

The second largest eigenvalue of a transition matrix $P$ has connections with many properties of the underlying Markov chain, and especially its convergence rate towards the stationary distribution. In this paper, we give an asymptotic upper bound for the second eigenvalue when $P$ is the transition matrix of the simple random walk over a random directed graph with given degree sequence. This is the first result concerning the asymptotic behavior of the spectral gap for sparse non-reversible Markov chains with an unknown stationary distribution. An immediate consequence of our result is a proof of the Alon conjecture for directed regular graphs. Our result is based on a variation of the trace method introduced by Bordenave (2015).