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Related papers: Isometric Rigidity of compact Wasserstein spaces

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Let $G$ be a group of homeomorphisms of a topological space $X$. $G$ is $\textit{(properly) isometrizable}$ if there exists a $G$-invariant (proper) gauge structure on $X$. $G$ is $\textit{equiregular}$ if for every $x \in X$ and every open…

General Topology · Mathematics 2021-05-19 Fredric D. Ancel

We show the contractibility of spaces of invariant Riemannian metrics of positive scalar curvature on compact connected manifolds of dimension at least two, with and without boundary and equipped with compact Lie group actions. On manifolds…

Differential Geometry · Mathematics 2025-06-23 Christian Baer , Bernhard Hanke

In this paper we study isometries of quantum Wasserstein distances and divergences on the quantum bit state space. We describe isometries with respect to the symmetric quantum Wasserstein divergence $d_{sym}$, the divergence induced by all…

Mathematical Physics · Physics 2025-03-31 Richárd Simon , Dániel Virosztek

Goodness-of-fit tests based on the empirical Wasserstein distance are proposed for simple and composite null hypotheses involving general multivariate distributions. For group families, the procedure is to be implemented after preliminary…

Methodology · Statistics 2021-01-28 Marc Hallin , Gilles Mordant , Johan Segers

Gromov--Wasserstein (GW) distances compare graphs, shapes, and point clouds through internal distances, without requiring a common coordinate system. This invariance is powerful, but discrete GW is a nonconvex quadratic optimal transport…

Machine Learning · Computer Science 2026-05-15 Ao Xu , Tieru Wu

We study the space of Riemannian metrics over a compact manifold equipped with the Ebin metric. We characterize its self-isometries and prove that two such spaces are isometric if and only if their underlying manifolds are diffeomorphic.

Metric Geometry · Mathematics 2025-12-09 David Lenze

Persistence diagrams are objects that play a central role in topological data analysis. In the present article, we investigate the local and global geometric properties of spaces of persistence diagrams. In order to do this, we construct a…

Metric Geometry · Mathematics 2024-08-09 Mauricio Che , Fernando Galaz-García , Luis Guijarro , Ingrid Amaranta Membrillo Solis

The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning. In this work, we consider the fundamental question of how quickly the…

Probability · Mathematics 2017-07-04 Jonathan Weed , Francis Bach

Using elementary comparison geometry, we prove: Let $(M,g)$ be a simply-connected complete Riemannian manifold of dimension $\ge 3$. Suppose that the sectional curvature $K$ satisfies $ -1-s(r) \le K \le -1$, where $r$ denotes distance to a…

Differential Geometry · Mathematics 2008-01-03 Harish Seshadri

The Bergman $p$-analytic content ($1\leq p<\infty $) of a planar domain $\Omega $ measures the $L^{p}(\Omega )$-distance between $\overline{z}$ and the Bergman space $A^{p}(\Omega )$ of holomorphic functions. It has a natural analogue in…

Classical Analysis and ODEs · Mathematics 2019-01-18 Stephen J. Gardiner , Marius Ghergu , Tomas Sjödin

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

We consider the Monge-Kantorovich problem between two random measuress. More precisely, given probability measures $\mathbb{P}_1,\mathbb{P}_2\in\mathcal{P}(\mathcal{P}(M))$ on the space $\mathcal{P}(M)$ of probability measures on a smooth…

Probability · Mathematics 2024-10-10 Pedram Emami , Brendan Pass

We consider structured approximation of measures in Wasserstein space $\mathrm{W}_p(\mathbb{R}^d)$ for $p\in[1,\infty)$ using general measure approximants compactly supported on Voronoi regions derived from a scaled Voronoi partition of…

Machine Learning · Statistics 2024-07-26 Keaton Hamm , Varun Khurana

In this paper we use a diffeo-geometric framework based on manifolds that are locally modeled on "convenient" vector spaces to study the geometry of some infinite dimensional spaces. Given a finite dimensional symplectic manifold…

Differential Geometry · Mathematics 2009-11-03 Brian Lee

Let $(X, d)$ be a compact metric space and let $\mathcal{M}(X)$ denote the space of all finite signed Borel measures on $X$. Define $I \colon \mathcal{M}(X) \to \R$ by \[ I(\mu) = \int_X \int_X d(x,y) d\mu(x) d\mu(y), \] and set $M(X) =…

Metric Geometry · Mathematics 2008-09-05 Peter Nickolas , Reinhard Wolf

Optimal transportation theory and the related $p$-Wasserstein distance ($W_p$, $p\geq 1$) are widely-applied in statistics and machine learning. In spite of their popularity, inference based on these tools has some issues. For instance, it…

Statistics Theory · Mathematics 2024-03-01 Yiming Ma , Hang Liu , Davide La Vecchia , Metthieu Lerasle

This work discovers a novel link between probability theory (of stable random fields) and von Neumann algebras. It is established that the group measure space construction corresponding to a minimal representation is an invariant of a…

Probability · Mathematics 2024-07-08 Parthanil Roy

We prove the existence of a quantum isometry groups for new classes of metric spaces: (i) geodesic metrics for compact connected Riemannian manifolds (possibly with boundary) and (ii) metric spaces admitting a uniformly distributed…

Quantum Algebra · Mathematics 2020-10-28 Alexandru Chirvasitu , Debashish Goswami

We investigate contraction of the Wasserstein distances on $\mathbb{R}^d$ under Gaussian smoothing. It is well known that the heat semigroup is exponentially contractive with respect to the Wasserstein distances on manifolds of positive…

Probability · Mathematics 2020-12-15 Hong-Bin Chen , Jonathan Niles-Weed

As part of a programme to classify quasi-Einstein metrics $(M,g,X)$ on closed manifolds and near-horizon geometries of extreme black holes, we study such spaces when the vector field $X$ is divergence-free but not identically zero. This…

Differential Geometry · Mathematics 2023-07-04 Eric Bahuaud , Sharmila Gunasekaran , Hari K Kunduri , Eric Woolgar