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We prove a new version of Egorov's theorem formulated in the Schr\"{o}dinger picture of quantum mechanics, using the $p$-Wasserstein metric applied to the Husimi functions of quantum states. The special case $p=1$ corresponds to a…

Quantum Physics · Physics 2025-09-10 Jordan Cotler , Felipe Hernández

The Monge-Kantorovich transportation problem involves optimizing with respect to a given a cost function. Uniqueness is a fundamental open question about which little is known when the cost function is smooth and the landscapes containing…

Probability · Mathematics 2010-08-27 Najma Ahmad , Hwa Kil Kim , Robert J. McCann

We consider dynamical transport metrics for probability measures on discretisations of a bounded convex domain in $\mathbb{R}^d$. These metrics are natural discrete counterparts to the Kantorovich metric $\mathbb{W}_2$, defined using a…

Analysis of PDEs · Mathematics 2020-01-30 Peter Gladbach , Eva Kopfer , Jan Maas

We investigate the stability of the Wasserstein distance, a metric structure on the space of probability measures arising from the theory of optimal transport, under metric ultralimits. We first show that if $(X_{i},d_{i})_{i\in\mathbb{N}}$…

Metric Geometry · Mathematics 2023-03-09 Andrew Warren

We show that the Hellinger-Kantorovich distance can be expressed as the metric infimal convolution of the Hellinger and the Wasserstein distances, as conjectured by Liero, Mielke, and Savar\'e. To prove it, we study with the tools of…

Metric Geometry · Mathematics 2025-03-18 Nicolò De Ponti , Giacomo Enrico Sodini , Luca Tamanini

We prove the upper semicontinuity of the measure theoretic entropy for the geodesic flow on complete Riemannian manifolds without focal points and bounded sectional curvature. We then study the relationship between the escape of mass…

Dynamical Systems · Mathematics 2018-04-26 Anibal Velozo

Let $A \subset \mathbb{R}^d$, $d\ge 2$, be a compact convex set and let $\mu = \varrho_0 dx$ be a probability measure on $A$ equivalent to the restriction of Lebesgue measure. Let $\nu = \varrho_1 dx$ be a probability measure on $B_r :=…

Differential Geometry · Mathematics 2008-05-12 Vladimir I. Bogachev , Alexander V. Kolesnikov

Let $\mu_N$ be the empirical measure associated to a $N$-sample of a given probability distribution $\mu$ on $\mathbb{R}^d$. We are interested in the rate of convergence of $\mu_N$ to $\mu$, when measured in the Wasserstein distance of…

Probability · Mathematics 2013-12-10 Nicolas Fournier , Arnaud Guillin

Given a function $F$ transforming a probability measure $\mu$ into another one $F(\mu)$, we study the existence and regularity of a transport representation of it. That is, we ask whether we can represent the image $F(\mu)$ of the input…

Functional Analysis · Mathematics 2026-04-21 Hugo Lavenant , Giuseppe Savaré

In this paper, we prove a structure theorem for discrete optimal transportation plans. We show that, given any pair of discrete probability measures and a cost function, there exists an optimal transportation plan that can be expressed as…

Optimization and Control · Mathematics 2021-04-28 Gennaro Auricchio , Marco Veneroni

We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative and finite Radon measures in general topological spaces. They arise quite naturally by relaxing the marginal constraints typical of Optimal…

Optimization and Control · Mathematics 2018-10-16 Matthias Liero , Alexander Mielke , Giuseppe Savaré

We introduce dynamic and static formulations that formally extend unbalanced optimal transport from the space of positive densities to the space of Riemannian metrics. The first construction is based on a dynamic variational formulation in…

Differential Geometry · Mathematics 2026-05-27 Martin Bauer , Peter W. Michor , François-Xavier Vialard

We formulate a class of velocity-free finite-particle methods for mass transport problems based on a time-discrete incremental variational principle that combines entropy and the cost of particle transport, as measured by the Wasserstein…

Computational Physics · Physics 2023-05-10 Anna Pandolfi , Laurent Stainier , Michael Ortiz

Given two probability measures $\mu$ and $\nu$ we consider a mass transportation mapping $T$ satisfying 1) $T$ sends $\mu$ to $\nu$, 2) $T$ has the form $T = \phi \frac{\nabla \phi}{|\nabla \phi|}$, where $\phi$ is a function with convex…

Functional Analysis · Mathematics 2013-06-27 Alexander V. Kolesnikov

We consider Monge-Kantorovich optimal transport problems on $\mathbb{R}^d$, $d\ge 1$, with a convex cost function given by the cumulant generating function of a probability measure. Examples include the Wasserstein-2 transport whose cost…

Probability · Mathematics 2017-08-29 Soumik Pal

In this article we study generalization of the classical Talagrand transport-entropy inequality in which the Wasserstein distance is replaced by the entropic transportation cost. This class of inequalities has been introduced in the recent…

Probability · Mathematics 2019-07-02 Giovanni Conforti , Luigia Ripani

We introduce Wasserstein-like dynamical transport distances between vector-valued densities on the real line. The mobility function from the scalar theory is replaced by a mobility matrix, that is subject to positivity and concavity…

Analysis of PDEs · Mathematics 2016-01-18 Jonathan Zinsl , Daniel Matthes

This short note gives a proof of the triangle inequality based on the Kantorovich duality formula for the Wasserstein distances of exponent $p\in[1,+\infty)$ in the case of a general Polish space. In particular it avoids the "glueing of…

Optimization and Control · Mathematics 2023-08-08 François Golse

This brief note aims to introduce the recent paradigm of distributional robustness in the field of shape and topology optimization. Acknowledging that the probability law of uncertain physical data is rarely known beyond a rough…

Optimization and Control · Mathematics 2023-01-13 Charles Dapogny , Franck Iutzeler , Andrea Meda , Boris Thibert

We introduce and study a variant of the Wasserstein distance on the space of probability measures, specially designed to deal with measures whose support has a dendritic, or treelike structure with a particular direction of orientation. Our…

Optimization and Control · Mathematics 2020-11-18 Young-Heon Kim , Brendan Pass , David J. Schneider
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