Lazy random walks and optimal transport on graphs

TL;DR

This paper introduces a method to construct displacement interpolations on discrete graphs using Schrödinger problems and random walks, enabling stochastic calculus on graphs and advancing optimal transport theory in discrete settings.

Contribution

It presents a novel approach to define displacement interpolations on graphs via Schrödinger problems, connecting stochastic processes with optimal transport on discrete structures.

Findings

Established convergence of the proposed interpolation method.

Derived new results on optimal transport on graphs.

Linked stochastic calculus with optimal transport in discrete spaces.

Abstract

This paper is about the construction of displacement interpolations on a discrete metric graph. Our approach is based on the approximation of any optimal transport problem whose cost function is a distance on a discrete graph by a sequence of Schr\"odinger problems associated with random walks whose jump frequencies tend down to zero. Displacement interpolations are defined as the limit of the time-marginal flows of the solutions to the Schr\"odinger problems. This allows to work with these interpolations by doing stochastic calculus on the approximating random walks which are regular objects, and then to pass to the limit in a slowing down procedure. The main convergence results are based on Gamma-convergence of entropy minimization problems. As a by-product, we obtain new results about optimal transport on graphs.