Unconditional convergence for discretizations of dynamical optimal transport
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Abstract:
The dynamical formulation of optimal transport, also known as Benamou–Brenier formulation or computational fluid dynamics formulation, amounts to writing the optimal transport problem as the optimization of a convex functional under a PDE constraint, and can handle a priori a vast class of cost functions and geometries. Several discretizations of this problem have been proposed, leading to computations on flat spaces as well as Riemannian manifolds, with extensions to mean field games and gradient flows in the Wasserstein space.
In this paper, we provide a framework which guarantees convergence under mesh refinement of the solutions of the space-time discretized problems to the one of the infinite-dimensional problem for quadratic optimal transport. The convergence holds without condition on the ratio between spatial and temporal step sizes, and can handle arbitrary positive measures as input, while the underlying space can be a Riemannian manifold. Both the finite volume discretization proposed by Gladbach, Kopfer, and Maas, as well as the discretization over triangulations of surfaces studied by the present author in collaboration with Claici, Chien, and Solomon, fit in this framework.
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Additional Information
- Hugo Lavenant
- Affiliation: Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2
- MR Author ID: 1238856
- ORCID: 0000-0002-2597-1124
- Email: hugo.lavenant@unibocconi.it
- Received by editor(s): September 17, 2019
- Received by editor(s) in revised form: April 7, 2020, and May 22, 2020
- Published electronically: October 23, 2020
- Additional Notes: The author acknowledges the support of ANR MAGA (ANR-16-CE40-0014).
- © Copyright 2020 American Mathematical Society
- Journal: Math. Comp. 90 (2021), 739-786
- MSC (2010): Primary 65K10; Secondary 49M25, 35A15
- DOI: https://doi.org/10.1090/mcom/3567
- MathSciNet review: 4194161