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Gradient flow formulation of diffusion equations in the Wasserstein space over a Metric graph

Matthias Erbar, Dominik Forkert, Jan Maas, Delio Mugnolo

2022Networks and Heterogeneous Media10 citationsDOIOpen Access PDF

Abstract

<p style='text-indent:20px;'>This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou–Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport. Secondly, in the spirit of Jordan–Kinderlehrer–Otto, we show that McKean–Vlasov equations can be formulated as gradient flow of the free energy in the Wasserstein space of probability measures. The proofs of these results are based on careful regularisation arguments to circumvent some of the difficulties arising in metric graphs, namely, branching of geodesics and the failure of semi-convexity of entropy functionals in the Wasserstein space.</p>

Topics & Concepts

Wasserstein metricBalanced flowGeodesicMathematicsConvexityMetric spaceMathematical proofEquivalence (formal languages)Probability measureSpace (punctuation)Metric (unit)Entropy (arrow of time)Applied mathematicsMathematical analysisPure mathematicsComputer scienceGeometryPhysicsFinancial economicsOperating systemEconomicsOperations managementQuantum mechanicsGeometric Analysis and Curvature FlowsGeometry and complex manifoldsTopological and Geometric Data Analysis