Scaling limits of discrete optimal transport

P. Gladbach, E. Kopfer, J. Maas, ArXiv (2018).

Preprint | Published | English
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Abstract
We consider dynamical transport metrics for probability measures on discretisations of a bounded convex domain in ℝd. These metrics are natural discrete counterparts to the Kantorovich metric 𝕎2, defined using a Benamou-Brenier type formula. Under mild assumptions we prove an asymptotic upper bound for the discrete transport metric Wt in terms of 𝕎2, as the size of the mesh T tends to 0. However, we show that the corresponding lower bound may fail in general, even on certain one-dimensional and symmetric two-dimensional meshes. In addition, we show that the asymptotic lower bound holds under an isotropy assumption on the mesh, which turns out to be essentially necessary. This assumption is satisfied, e.g., for tilings by convex regular polygons, and it implies Gromov-Hausdorff convergence of the transport metric.
Publishing Year
Date Published
2018-11-05
Journal Title
ArXiv
Page
44
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Cite this

Gladbach P, Kopfer E, Maas J. Scaling limits of discrete optimal transport. ArXiv. 2018.
Gladbach, P., Kopfer, E., & Maas, J. (2018). Scaling limits of discrete optimal transport. ArXiv. ArXiv.
Gladbach, Peter, Eva Kopfer, and Jan Maas. “Scaling Limits of Discrete Optimal Transport.” ArXiv. ArXiv, 2018.
P. Gladbach, E. Kopfer, and J. Maas, “Scaling limits of discrete optimal transport,” ArXiv. ArXiv, 2018.
Gladbach P, Kopfer E, Maas J. 2018. Scaling limits of discrete optimal transport. ArXiv.
Gladbach, Peter, et al. “Scaling Limits of Discrete Optimal Transport.” ArXiv, ArXiv, 2018.

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