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We prove two injectivity theorems for the geodesic ray transform on two-dimensional, complete, simply connected Riemannian manifolds with non-positive Gaussian curvature, also known as Cartan-Hadamard manifolds. The first theorem is…

Differential Geometry · Mathematics 2016-12-15 Jere Lehtonen

We study the following problem: given an Einstein metric on a manifold, characterize and study all Einstein metrics which are pointwise projective to the given one. By definition, two metrics are said to be pointwise projectively related if…

Metric Geometry · Mathematics 2007-05-23 Zhongmin Shen

We prove that knowing the length of geodesics joining points on the boundary of a two-dimensional, compact, simple Riemannian manifold with boundary, we can determine uniquely the Riemannian metric up to the natural obstruction.

Analysis of PDEs · Mathematics 2007-05-23 L. Pestov , G. Uhlmann

Given a Lorentzian manifold, the light ray transform of a function is its integrals along null geodesics. This paper is concerned with the injectivity of the light ray transform on functions and tensors, up to the natural gauge for the…

Analysis of PDEs · Mathematics 2023-05-10 Ali Feizmohammadi , Joonas Ilmavirta , Lauri Oksanen

This paper, a culmination of the authors' theory of the RT-equations, accomplishes the following: (i) We discover there is a true (geometric) regularity associated with every affine connection, its ``essential regularity'', the highest…

General Relativity and Quantum Cosmology · Physics 2026-05-29 Moritz Reintjes , Blake Temple

Effects of geometric constraints on a steady flow potential are described by an elliptic-hyperbolic generalization of the harmonic map equations. Sufficient conditions are given for global triviality.

Mathematical Physics · Physics 2007-05-23 Thomas H. Otway

We study a class of design problems in solid mechanics, leading to a variation on the classical question of equi-dimensional embeddability of Riemannian manifolds. In this general new context, we derive a necessary and sufficient existence…

Analysis of PDEs · Mathematics 2016-04-13 Amit Acharya , Marta Lewicka , Mohammad Reza Pakzad

A Hessian manifold $(M,D,g)$ is a manifold $M$ with a flat connection $D$ and a Riemannian or pseudo-Riemannian metric $g$ that is locally of the form $D^2 f$ for some function $f$. On a Hessian manifold $(M,D,g)$, we define a hybrid…

Differential Geometry · Mathematics 2026-04-14 Arnaud Chéritat , Guillaume Tahar

We show that compact Riemannian manifolds, regarded as metric spaces with their global geodesic distance, cannot contain a number of rigid structures such as (a) arbitrarily large regular simplices or (b) arbitrarily long sequences of…

Metric Geometry · Mathematics 2021-01-06 Alexandru Chirvasitu

We propose a geometrical approach to the investigation of Hamiltonian systems on (Pseudo) Riemannian manifolds. A new geometrical criterion of instability and chaos is proposed. This approach is more generic than well known reduction to the…

Astrophysics · Physics 2007-05-23 A. A. Kocharyan

In this article, the ray tracing method is studied beyond the classical geometrical theory. The trajectories are here regarded as geodesics in a Riemannian manifold, whose metric and topological properties are those induced by the…

Mathematical Physics · Physics 2013-07-24 Enrico De Micheli , Giovanni Alberto Viano

The main purpose of this article is to introduce a comprehensive, unified theory of the geometry of all connections. We show that one can study a connection via a certain, closely associated second-order differential equation. One of the…

Differential Geometry · Mathematics 2011-07-13 L. Del Riego , Phillip. E. Parker

We consider the mixed ray transform of tensor fields on a three-dimensional compact simple Riemannian manifold with boundary. We prove the injectivity of the transform, up to natural obstructions, and establish stability estimates for the…

Differential Geometry · Mathematics 2020-08-19 Maarten V. de Hoop , Teemu Saksala , Gunther Uhlmann , Jian Zhai

The concept of sharpness has been successfully applied to traditional architectures like MLPs and CNNs to predict their generalization. For transformers, however, recent work reported weak correlation between flatness and generalization. We…

Machine Learning · Computer Science 2025-05-09 Marvin F. da Silva , Felix Dangel , Sageev Oore

We study the question of stability of the global and partial anisotropic Calder\'on inverse problems for the class of Painlev\'e-Liouville Riemannian manifolds, that is compact $n$-dimensional manifolds with boundary $(M,g)$, where…

Analysis of PDEs · Mathematics 2026-02-17 Thierry Daudé , Niky Kamran , François Nicoleau

Let $\Sigma$ be a Riemannian manifold with strictly convex spherical boundary. Assuming absence of conjugate points and that the trapped set is hyperbolic, we show that $\Sigma$ can be isometrically embedded into a closed Riemannian…

Differential Geometry · Mathematics 2023-04-03 Dong Chen , Alena Erchenko , Andrey Gogolev

This is a survey of our research on geometric structures of projective embeddings and includes some topics of our talks in several symposia during 1990-99. We clarify our main problem, which is to construct a kind of geometric composition…

Algebraic Geometry · Mathematics 2007-05-23 Takeshi Usa

Suppose we are given a compact Riemannian manifold (Q,g)with completely integrable geodesic flow. Let G be a compact connected Lie group acting freely on Q by isometries. The natural question arises: will the geodesic flow on Q/G equipped…

Mathematical Physics · Physics 2007-05-23 Bozidar Jovanovic

We consider Calderon's inverse problem with partial data in dimensions $n \geq 3$. If the inaccessible part of the boundary satisfies a (conformal) flatness condition in one direction, we show that this problem reduces to the invertibility…

Analysis of PDEs · Mathematics 2016-01-20 Carlos E. Kenig , Mikko Salo

Modern machine learning increasingly leverages the insight that high-dimensional data often lie near low-dimensional, non-linear manifolds, an idea known as the manifold hypothesis. By explicitly modeling the geometric structure of data…

Machine Learning · Computer Science 2026-03-02 Willem Diepeveen , Deanna Needell
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