English
Related papers

Related papers: Mass Transportation on Sub-Riemannian Manifolds

200 papers

The Brenier optimal map and the Knothe-Rosenblatt rearrangement are two instances of a transport map, that is to say a map sending one measure onto another. The main interest of the former is that it solves the Monge-Kantorovich optimal…

Optimization and Control · Mathematics 2012-09-26 Nicolas Bonnotte

Optimal transport plays a major role in the study of manifolds with Ricci curvature bounded below. Some results in this setting have been extended to super Ricci flows, revealing a unified approach to analysis on Ricci nonnegative manifolds…

Differential Geometry · Mathematics 2025-10-31 Marco Flaim , Erik Hupp

We consider the transfer operators of non-uniformly expanding maps for potentials of various regularity, and show that a specific property of potentials ("flatness") implies a Ruelle-Perron-Frobenius Theorem and a decay of the transfer…

Classical Analysis and ODEs · Mathematics 2022-07-14 Benoît Kloeckner

The optimal mass transportation was introduced by Monge some 200 years ago and is, today, the source of large number of results in analysis, geometry and convexity. Here I investigate a new, surprising link between optimal transformations…

Dynamical Systems · Mathematics 2010-10-19 Gershon Wolansky

Starting from a sequence of independent Wright-Fisher diffusion processes on $[0,1]$, we construct a class of reversible infinite dimensional diffusion processes on $\DD_\infty:= \{{\bf x}\in Let $M$ be a complete Riemnnian manifold and…

Probability · Mathematics 2007-12-20 Shizan Fang , Feng-Yu Wang , Bo Wu

The aim of this paper is to prove isoperimetric inequalities on submanifolds of the Euclidean space using mass transportation methods. We obtain a sharp ?weighted isoperimetric inequality? and a nonsharp classical inequality similar to the…

Differential Geometry · Mathematics 2016-11-25 Philippe Castillon

We provide a solution to the problem of optimal transport by Brownian martingales in general dimensions whenever the transport cost satisfies certain subharmonic properties in the target variable, as well as a stochastic version of the…

Analysis of PDEs · Mathematics 2020-10-07 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

Let $M$ be a complete connected Riemannian manifold. For $n \geq 0$, we endow the Wasserstein space $P^{(n)}_2(M) = P_2(\ldots P_2(M)\ldots)$, equipped with the Wasserstein distance $W_2$, with a variational structure that generalizes the…

Optimization and Control · Mathematics 2025-12-04 Christophe Vauthier

We study couplings $q^\bullet$ of two equivariant random measures $\lambda^\bullet$ and $\mu^\bullet$ on a Riemannian manifold $(M,d,m)$. Given a cost function we ask for minimizers of the mean transportation cost per volume. In case the…

Probability · Mathematics 2012-06-19 Martin Huesmann

We propose a new metric between probability measures on a compact metric space that mirrors the Riemannian manifold-like structure of quadratic optimal transport but includes entropic regularization. Its metric tensor is given by the…

Optimization and Control · Mathematics 2025-09-22 Hugo Lavenant , Jonas Luckhardt , Gilles Mordant , Bernhard Schmitzer , Luca Tamanini

We develop the theory of a metric, which we call the $\nu$-based Wasserstein metric and denote by $W_\nu$, on the set of probability measures $\mathcal P(X)$ on a domain $X \subseteq \mathbb{R}^m$. This metric is based on a slight…

Optimization and Control · Mathematics 2022-09-16 Luca Nenna , Brendan Pass

We discuss methods of Optimal Transportation Theory and its relations to problems in quantum mechanics. This essentially means that the cost function is some Hamiltonian $H(q,p)$ on a phase space (symplectic manifold), and the marginal…

Mathematical Physics · Physics 2018-08-20 Kurt Pagani

The Bregman-Wasserstein divergence is the optimal transport cost when the underlying cost function is given by a Bregman divergence, and arises naturally in fields such as statistics and machine learning. We establish fundamental properties…

Probability · Mathematics 2025-04-14 Amanjit Singh Kainth , Cale Rankin , Ting-Kam Leonard Wong

We introduce and study a simple model capturing the main features of unbalanced optimal transport. It is based on equipping the conical extension of the group of all diffeomorphisms with a natural metric, which allows a Riemannian…

Differential Geometry · Mathematics 2025-08-12 Boris Khesin , Klas Modin , Luke Volk

One of the central objects in the theory of optimal transport is the Brenier map: the unique monotone transformation which pushes forward an absolutely continuous probability law onto any other given law. A line of recent work has analyzed…

Probability · Mathematics 2024-09-18 Tudor Manole , Sivaraman Balakrishnan , Jonathan Niles-Weed , Larry Wasserman

We study Fokker--Planck equations with symmetric, positive definite mobility matrices capturing diffusion in heterogeneous environments. A weighted Wasserstein metric is introduced for which these equations are gradient flows. This metric…

Optimization and Control · Mathematics 2025-05-19 Hailiang Liu , Athanasios E. Tzavaras

The goal of this paper is to derive the so-called five gradients inequality for optimal transport theory for general cost functions on two class of differentiable manifolds: locally compact Lie groups and compact Riemannian manifolds.

Analysis of PDEs · Mathematics 2024-09-09 S. Di Marino , S. Murro , E. Radici

What is the optimal way to deform a projective hypersurface into another one? In this paper we will answer this question adopting the point of view of measure theory, introducing the optimal transport problem between complex algebraic…

Differential Geometry · Mathematics 2023-07-18 Paolo Antonini , Fabio Cavalletti , Antonio Lerario

This note exposes the differential topology and geometry underlying some of the basic phenomena of optimal transportation. It surveys basic questions concerning Monge maps and Kantorovich measures: existence and regularity of the former,…

Optimization and Control · Mathematics 2018-01-23 Robert J McCann

Riemannian optimization uses local methods to solve optimization problems whose constraint set is a smooth manifold. A linear step along some descent direction usually leaves the constraints, and hence retraction maps are used to…

Statistics Theory · Mathematics 2023-01-19 Alexander Heaton , Matthias Himmelmann