2008
DOI: 10.1137/08071346x
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Eulerian Calculus for the Displacement Convexity in the Wasserstein Distance

Abstract: In this paper we give a new proof of the (strong) displacement convexity of a class of integral functionals dened on a compact Riemannian manifold satisfying a lower Ricci curvature bound. Our approach does not rely on existence and regularity results for optimal transport maps on Riemannian manifolds, but it is based on the Eulerian point of view recently introduced by and on the metric characterization of the gradient ows generated by the functionals in the Wasserstein space.

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Cited by 114 publications
(172 citation statements)
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“…We expect that one can prove Proposition 16 using the Eulerian approach and a density argument, along the lines of [5], but we do not pursue this here.…”
Section: Convexity Of the L − -Entropymentioning
confidence: 99%
See 3 more Smart Citations
“…We expect that one can prove Proposition 16 using the Eulerian approach and a density argument, along the lines of [5], but we do not pursue this here.…”
Section: Convexity Of the L − -Entropymentioning
confidence: 99%
“…These proofs can then be considered as formal proofs of the analogous statements on the space of all probability measures P (M). The rigorous proofs of the statements on P (M) are usually done by the Lagrangian approach, but one can also use the density of P ∞ (M) in P (M) [5,20]. Most of the calculations in this section can be extracted from [19] and [20].…”
Section: Otto Calculusmentioning
confidence: 99%
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“…Displacement convexity on Riemannian manifolds for internal energy (under Ricci curvature bounds) was predicted by Otto and Villani [21] and proved by Cordero-Erausquin, McCann, and Schmuckenschläger in [8]. Recently Otto and Westdickenberg [22] have introduced techniques that were further developed by Daneri and Savare [11] to show geodesic convexity of functionals on manifolds using a purely local, Eulerian framework. The connection between bounds on displacement convexity and bounds on Ricci curvature has found important applications, see papers by Lott and Villani [16], Sturm and von Renesse [25], Sturm [24,23] and references therein.…”
Section: Introductionmentioning
confidence: 99%