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Contraction in Wasserstein 1-distance with explicit rates is established for generalized Hamiltonian Monte Carlo with stochastic gradients under possibly nonconvex conditions. The algorithms considered include splitting schemes of kinetic…

Probability · Mathematics 2024-09-16 Martin Chak , Pierre Monmarché

We consider a Serrin-type problem in convex cones in the Euclidean space and motivated by recent rigidity results we study the quantitative stability issue for this problem. In particular, we prove both sharp Lipschitz estimates for an…

Analysis of PDEs · Mathematics 2023-09-06 Filomena Pacella , Giorgio Poggesi , Alberto Roncoroni

The theory of optimal transport of probability measures has wide-ranging applications across a number of different fields, including concentration of measure, machine learning, Markov chains, and economics. The generalisation of optimal…

Quantum Physics · Physics 2026-04-21 Emily Beatty

We introduce a non-quadratic generalization of the quantum mechanical optimal transport problem introduced in [De Palma and Trevisan, Ann. Henri Poincar\'e, {\bf 22} (2021), 3199-3234] where quantum channels realize the transport. Relying…

Mathematical Physics · Physics 2026-04-28 Gergely Bunth , József Pitrik , Tamás Titkos , Dániel Virosztek

We study the Wasserstein distance of order 1 between the empirical distribution and the marginal distribution of stationary $\alpha$-dependent sequences. We prove some moments inequalities of order p for any p $\ge$ 1, and we give some…

Probability · Mathematics 2015-03-03 Jérôme Dedecker , Florence Merlevède

We show that the Euclidean Wasserstein distance is contractive for inelastic homogeneous Boltzmann kinetic equations in the Maxwellian approximation and its associated Kac-like caricature. This property is as a generalization of the Tanaka…

Analysis of PDEs · Mathematics 2016-08-16 François Bolley , José Antonio Carrillo

We provide explicit formulaes for the first Kantorovich-Wasserstein distance between stationary measures for iterated function scheme on the unit interval. In particular, we consider two stationary measures with different configurations of…

Dynamical Systems · Mathematics 2018-07-30 Italo Cipriano

We theoretically analyze the properties of a geodesic random walk on the Euclidean $d$-sphere. Specifically, we prove that the random walk's transition kernel is Wasserstein contractive with a contraction rate which can be bounded from…

Statistics Theory · Mathematics 2024-10-15 Philip Schär , Thilo D. Stier

We obtain a general bound for the Wasserstein-2 distance in normal approximation for sums of locally dependent random variables. The proof is based on an asymptotic expansion for expectations of second-order differentiable functions of the…

Probability · Mathematics 2019-01-23 Xiao Fang

In this essay, we discuss the notion of optimal transport on geodesic measure spaces and the associated (2-)Wasserstein distance. We then examine displacement convexity of the entropy functional on the space of probability measures. In…

Metric Geometry · Mathematics 2012-04-17 Otis Chodosh

Let $M$ be a connected compact Riemannian manifold possibly with a boundary, let $V\in C^2(M)$ such that $\mu(\d x):=\e^{V(x)}\d x$ is a probability measure, where $\d x$ is the volume measure, and let $L=\Delta+\nabla V$. The exact…

Probability · Mathematics 2021-07-27 Feng-Yu Wang , Bingyao Wu

The subject of this paper is the estimation of a probability measure on ${\mathbb R}^d$ from data observed with an additive noise, under the Wasserstein metric of order $p$ (with $p\geq 1$). We assume that the distribution of the errors is…

Statistics Theory · Mathematics 2013-07-22 Jérôme Dedecker , Bertrand Michel

We study a new class of distances between Radon measures similar to those studied in a recent paper of Dolbeault-Nazaret-Savar\'e [DNS]. These distances (more correctly pseudo-distances because can assume the value $+\infty$) are defined…

Functional Analysis · Mathematics 2009-09-15 Stefano Lisini , Antonio Marigonda

Optimal transport and the Wasserstein distance $\mathcal{W}_p$ have recently seen a number of applications in the fields of statistics, machine learning, data science, and the physical sciences. These applications are however severely…

Statistics Theory · Mathematics 2024-05-24 Ruiyu Han , Cynthia Rush , Johannes Wiesel

We investigate here the optimal transportation problem on configuration space for the quadratic cost. It is shown that, as usual, provided that the corresponding Wasserstein is finite, there exists one unique optimal measure and that this…

Probability · Mathematics 2007-05-23 L. Decreusefond

We study the structure of the support of a doubling measure by analyzing its self-similarity properties, which we estimate using a variant of the $L^1$ Wasserstein distance. We show that measure satisfying certain self-similarity conditions…

Metric Geometry · Mathematics 2014-11-11 Jonas Azzam , Guy David , Tatiana Toro

We study a class of quadratic Wasserstein distances on spaces consisting of generalized dynamical systems on a von Neumann algebra. We emphasize how symmetry of such a Wasserstein distance arises, but also study the asymmetric case. This…

Operator Algebras · Mathematics 2024-11-05 Rocco Duvenhage

We obtain an estimate for the expected subspace robust Wasserstein distance between any probability measure on the unit ball of a separable Hilbert space, and its empirical distribution from $n$ i.i.d. samples.

Probability · Mathematics 2025-12-05 Dakshesh Vasan

In this article, exponential contraction in Wasserstein distance for heat semigroups of diffusion processes on Riemannian manifolds is established under curvature conditions where Ricci curvature is not necessarily required to be…

Differential Geometry · Mathematics 2020-01-20 Li-Juan Cheng , Anton Thalmaier , Shao-Qin Zhang

We prove $L^p$-Hardy inequalities with distance to the boundary for domains in the Heisenberg group ${\mathbb{H}}^n$, $n\geq 1$. Our results are based on a certain geometric condition. This is first implemented for the Euclidean distance in…

Analysis of PDEs · Mathematics 2026-03-24 Gerassimos Barbatis , Marianna Chatzakou , Achilles Tertikas