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This paper investigates the failure of certain metric measure spaces to be infinitesimally Hilbertian or quasi-Riemannian manifolds, by constructing examples arising from a manifold $M$ endowed with a Riemannian metric $g$ that is possibly…

Differential Geometry · Mathematics 2026-03-31 Vanessa Ryborz

The geometric approach to optimal transport and information theory has triggered the interpretation of probability densities as an infinite-dimensional Riemannian manifold. The most studied Riemannian structures are Otto's metric, yielding…

Analysis of PDEs · Mathematics 2018-07-20 Martin Bauer , Sarang Joshi , Klas Modin

In prior work \cite{AD} of Lars Andersson and Bruce K. Driver, the path space with finite interval over a compact Riemannian manifold is approximated by finite dimensional manifolds $H_{x,\P} (M)$ consisting of piecewise geodesic paths…

Probability · Mathematics 2018-12-06 Bo Wu

A recurring obstacle in the study of Wasserstein gradient flow is the lack of convexity of the square Wasserstein metric. In this paper, we develop a class of transport metrics that have better convexity properties and use these metrics to…

Analysis of PDEs · Mathematics 2014-06-06 Katy Craig

The geodesic orbit property is useful and interesting in itself, and it plays a key role in Riemannian geometry. It implies homogeneity and has important classes of Riemannian manifolds as special cases. Those classes include weakly…

Differential Geometry · Mathematics 2023-07-18 Zhiqi Chen , Yuri Nikolayevsky , Joseph A. Wolf , Shaoxiang Zhang

A consistent approach to the description of integral coordinate invariant functionals of the metric on manifolds ${\cal M}_{\alpha}$ with conical defects (or singularities) of the topology $C_{\alpha}\times\Sigma$ is developed. According to…

High Energy Physics - Theory · Physics 2016-09-06 D. V. Fursaev , S. N. Solodukhin

We consider a generalization of Riemannian geometry that naturally arises in the framework of control theory. Let $X$ and $Y$ be two smooth vector fields on a two-dimensional manifold $M$. If $X$ and $Y$ are everywhere linearly independent,…

Optimization and Control · Mathematics 2007-05-23 Andrei A. Agrachev , Ugo Boscain , Mario Sigalotti

Two pseudo-Riemannian metrics are called projectively equivalent if their unparametrized geodesics coincide. The degree of mobility of a metric is the dimension of the space of metrics that are projectively equivalent to it. We give a…

Differential Geometry · Mathematics 2017-11-28 Vladimir S. Matveev , Stefan Rosemann

We consider geometries on the space of Riemannian metrics conformally equivalent to the widely studied Ebin L^2 metric. Among these we characterize a distinguished metric that can be regarded as a generalization of Calabi's metric on the…

Differential Geometry · Mathematics 2013-05-09 Brian Clarke , Yanir A. Rubinstein

The paper is devoted to the geometry of transportation cost spaces and their generalizations introduced by Melleray, Petrov, and Vershik (2008). Transportation cost spaces are also known as Arens-Eells, Lipschitz-free, or Wasserstein $1$…

Functional Analysis · Mathematics 2020-07-17 Sofiya Ostrovska , Mikhail Ostrovskii

We introduce the Langevin deformation for the R\'enyi entropy on the $L^2$-Wasserstein space over $\mathbb{R}^n$ or a Riemannian manifold, which interpolates between the porous medium equation and the Benamou-Brenier geodesic flow on the…

Probability · Mathematics 2024-10-29 Rong Lei , Songzi Li , Xiang-Dong Li

We study the optimal transport problem in sub-Riemannian manifolds where the cost function is given by the square of the sub-Riemannian distance. Under appropriate assumptions, we generalize Brenier-McCann's Theorem proving existence and…

Optimization and Control · Mathematics 2009-10-15 Alessio Figalli , Ludovic Rifford

One field of fluid dynamics concerns the search for variational principles. So far, the Hamiltonian view and Riemannian geometry has been applied to find geodesics for hydrodynamic systems. Compared to Riemannian geometry sub-Riemannian…

Fluid Dynamics · Physics 2022-03-08 Annette Müller , Peter Névir

We prove two rigidity theorems for maps between Riemannian manifolds. First, we prove that a Lipschitz map $f:M\to N$ between two oriented Riemannian manifolds, whose differential is almost everywhere an orientation-preserving isometry, is…

Differential Geometry · Mathematics 2019-01-23 Raz Kupferman , Cy Maor , Asaf Shachar

The space of full-ranked one-forms on a smooth, orientable, compact manifold (possibly with boundary) is metrically incomplete with respect to the induced geodesic distance of the generalized Ebin metric. We show a distance equality between…

Differential Geometry · Mathematics 2023-08-01 Nicola Cavallucci , Zhe Su

We describe the isometry group of $L^2(\Omega, M)$ for Riemannian manifolds $M$ of dimension at least two with irreducible universal cover. We establish a rigidity result for the isometries of these spaces: any isometry arises from an…

Metric Geometry · Mathematics 2025-04-10 David Lenze

We investigate the space of Hermitian metrics on a fixed complex vector bundle. This infinite-dimensional space has appeared in the study of Hermitian-Einstein structures, where a special L2-type Riemannian metric is introduced. We compute…

Differential Geometry · Mathematics 2025-09-03 Jinwei Gao

In this paper, a Riemannian geometry of noncommutative super surfaces is developed which generalizes [4] to the super case. The notions of metric and connections on such noncommutative super surfaces are introduced and it is shown that the…

Differential Geometry · Mathematics 2022-12-29 Yong Wang , Tong Wu

We formulate an approach to the geometry of Riemann-Cartan spaces provided with nonholonomic distributions defined by generic off-diagonal and nonsymmetric metrics inducing effective nonlinear and affine connections. Such geometries can be…

General Relativity and Quantum Cosmology · Physics 2008-12-19 Sergiu I. Vacaru

Laplacian-based methods are popular for the dimensionality reduction of data lying in $\mathbb{R}^N$. Several theoretical results for these algorithms depend on the fact that the Euclidean distance locally approximates the geodesic distance…

Machine Learning · Computer Science 2025-09-24 Liane Xu , Amit Singer