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We propose a new strong Riemannian metric on the manifold of (parametrized) embedded curves of regularity $H^s$, $s\in(3/2,2)$. We highlight its close relationship to the (generalized) tangent-point energies and employ it to show that this…

Differential Geometry · Mathematics 2025-12-17 Elias Döhrer , Philipp Reiter , Henrik Schumacher

It is often easier to study pseudo-Riemannian manifolds by presenting them as surfaces in some ambient space. We propose an algorithm for construction of explicit isometric embeddings of pseudo-Riemannian manifolds with symmetries into an…

General Relativity and Quantum Cosmology · Physics 2023-07-04 A. A. Sheykin , M. V. Markov , S. A. Paston

In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degrees of complexity that aim to recover man…

Machine Learning · Statistics 2013-06-03 Dominique Perraul-Joncas , Marina Meila

Graph generation is a fundamental task with wide applications in modeling complex systems. Although existing methods align the spectrum or degree profile of the target graph, they often ignore the geometry induced by eigenvectors and the…

Machine Learning · Computer Science 2025-10-06 Xikun Huang , Tianyu Ruan , Chihao Zhang , Shihua Zhang

We introduce and study a conformal heat flow of harmonic maps defined by an evolution equation for a pair consisting of a map and a conformal factor of metric on the two-dimensional domain. This flow is designed to postpone finite time…

Differential Geometry · Mathematics 2024-06-07 Woongbae Park

The problem of recovering the configuration of points from their partial pairwise distances, referred to as the Euclidean Distance Matrix Completion (EDMC) problem, arises in a broad range of applications, including sensor network…

Optimization and Control · Mathematics 2026-05-07 Chandler Smith , HanQin Cai , Abiy Tasissa

As a generalization of anti-invariant Riemannian submersions, we introduce anti-invariant Riemannian maps from almost Hermitian manifolds to Riemannian manifolds. We give examples and investigate the geometry of foliations which are arisen…

Differential Geometry · Mathematics 2012-10-02 Bayram Sahin

The paper establishes a series of gradient estimates for positive solutions to the heat equation on a manifold $M$ evolving under the Ricci flow, coupled with the harmonic map flow between $M$ and a second manifold $N$. We prove Li-Yau type…

Differential Geometry · Mathematics 2016-08-10 Mihai Băileşteanu

Motivated by a question of Tsai-Tsui-Wang, we consider the rigidity of map from manifolds with positive Ricci curvature to manifolds with positive sectional curvature. We show that if the Ricci curvature of the domain dominates that of the…

Differential Geometry · Mathematics 2024-11-25 Man-Chun Lee , Jingbo Wan

Using the interpretation of the half-Laplacian on $S^1$ as the Dirichlet-to-Neumann operator for the Laplace equation on the ball $B$, we devise a classical approach to the heat flow for half-harmonic maps from $S^1$ to a closed target…

Differential Geometry · Mathematics 2024-05-22 Michael Struwe

Biharmonic and conformal-biharmonic maps are two fourth-order generalizations of the well-studied notion of harmonic maps in Riemannian geometry. In this article we consider maps into the Euclidean sphere and investigate a geometric…

Differential Geometry · Mathematics 2026-03-09 Volker Branding

We address the problem of estimating topological features from data in high dimensional Euclidean spaces under the manifold assumption. Our approach is based on the computation of persistent homology of the space of data points endowed with…

Machine Learning · Statistics 2023-01-23 Ximena Fernández , Eugenio Borghini , Gabriel Mindlin , Pablo Groisman

We propose a general framework to extend Flow Matching to homogeneous spaces, i.e. quotients of Lie groups. Our approach reformulates the problem as a flow matching task on the underlying Lie group by lifting the data distributions. This…

Machine Learning · Computer Science 2026-03-27 Francesco Ruscelli

In this paper, we establish the uniqueness of heat flow of harmonic maps into (N, h) that have sufficiently small renormalized energies, provided that N is either a unit sphere $S^{k-1}$ or a compact Riemannian homogeneous manifold without…

Analysis of PDEs · Mathematics 2016-11-11 Tao Huang , Changyou Wang

In this paper we find a criterion for the Gauss map of an immersed smooth submanifold in some Lie group with left invariant metric to be harmonic. Using the obtained expression we prove some necessary and sufficient conditions for the…

Differential Geometry · Mathematics 2012-02-29 Eugene V. Petrov

We consider the fundamental task of optimising a real-valued function defined in a potentially high-dimensional Euclidean space, such as the loss function in many machine-learning tasks or the logarithm of the probability distribution in…

Machine Learning · Statistics 2024-03-20 Marcelo Hartmann , Bernardo Williams , Hanlin Yu , Mark Girolami , Alessandro Barp , Arto Klami

In this paper, we introduce metallic maps between metallic Riemannian manifolds, provide an example and obtain certain conditions for such maps to be totally geodesic. We also give a sufficient condition for a map between metallic…

Differential Geometry · Mathematics 2020-03-10 Mehmet Akif Akyol

Motivated by geometry processing for surfaces with non-trivial topology, we study discrete harmonic maps between closed surfaces of genus at least two. Harmonic maps provide a natural framework for comparing surfaces by minimizing…

Numerical Analysis · Mathematics 2025-09-03 Zhipeng Zhu , Wai Yeung Lam , Lok Ming Lui

Consensus algorithms are popular distributed algorithms for computing aggregate quantities, such as averages, in ad-hoc wireless networks. However, existing algorithms mostly address the case where the measurements lie in a Euclidean space.…

Dynamical Systems · Mathematics 2012-02-02 Roberto Tron , Bijan Afsari , René Vidal

In many robot motion planning problems, task objectives and physical constraints induce non-Euclidean geometry on the configuration space, yet many planners operate using Euclidean distances that ignore this structure. We address the…

Robotics · Computer Science 2026-05-15 Phone Thiha Kyaw , Jonathan Kelly