"Spectrally gapped" random walks on networks: a Mean First Passage Time formula

TL;DR

This paper presents an explicit, matrix-inversion-free formula for calculating the Mean First Passage Time of a random walk between nodes in directed, weighted networks, relying only on transition probabilities.

Contribution

It introduces a novel approximate formula for MFPT that depends on the spectral gap and is applicable to directed weighted networks without matrix inversion.

Findings

The formula accurately predicts MFPT in various network instances.

It performs well away from high sparsity regimes.

The approach leverages spectral properties of the transition matrix.

Abstract

We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and it takes as only input the transition probabilities into the target node. It is derived from the calculation of the average resolvent of a deformed ensemble of random sub-stochastic matrices $H=\langle H\rangle +\delta H$, with $\langle H\rangle$ rank-$1$ and non-negative. The accuracy of the formula depends on the spectral gap of the reduced transition matrix, and it is tested numerically on several instances of (weighted) networks away from the high sparsity regime, with an excellent agreement.