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Related papers: Distance matrices and isometric embeddings

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Graph embeddings deal with injective maps from a given simple, undirected graph $G=(V,E)$ into a metric space, such as $\mathbb{R}^n$ with the Euclidean metric. This concept is widely studied in computer science, see \cite{ge1}, but also…

Combinatorics · Mathematics 2022-05-04 Dominic van der Zypen

The distance matrix of a connected graph is the symmetric matrix with columns and rows indexed by the vertices and entries that are the pairwise distances between the corresponding vertices. We give a construction for graphs which differ in…

Combinatorics · Mathematics 2016-06-23 Kristin Heysse

Nontrivial isometric embeddings for flat metrics (i.e., those which are not just planes in the ambient space) can serve as useful tools in the description of gravity in the embedding gravity approach. Such embeddings can additionally be…

General Relativity and Quantum Cosmology · Physics 2021-12-21 S. A. Paston , T. I. Zaitseva

We develop a new class of distances for objects including lines, hyperplanes, and trajectories, based on the distance to a set of landmarks. These distances easily and interpretably map objects to a Euclidean space, are simple to compute,…

Computational Geometry · Computer Science 2019-06-13 Jeff M. Phillips , Pingfan Tang

Although recovering an Euclidean distance matrix from noisy observations is a common problem in practice, how well this could be done remains largely unknown. To fill in this void, we study a simple distance matrix estimate based upon the…

Machine Learning · Statistics 2014-09-18 Luwan Zhang , Grace Wahba , Ming Yuan

In this note, we summarize known results and open questions on the existence of isometric embeddings between different Schatten classes as well as obtain a new non-embeddability result using a novel method. We also provide a brief overview…

Functional Analysis · Mathematics 2026-05-04 Arup Chattopadhyay , Chandan Pradhan , Anna Skripka

The practically important classes of equal-input and of monotone Markov matrices are revisited, with special focus on embeddability, infinite divisibility, and mutual relations. Several uniqueness results for the classic Markov embedding…

Probability · Mathematics 2022-09-27 Michael Baake , Jeremy Sumner

A proof of the isometric embedding of a given two-metric in E^3 of class C^1. The method uses the theory of first order partial differential equations. The curvature of the metric plays no role in the proof.

Differential Geometry · Mathematics 2017-12-19 Edgar Kann

We show how the Riemannian distance on $\mathbb{S}^n_{++}$, the cone of $n\times n$ real symmetric or complex Hermitian positive definite matrices, may be used to naturally define a distance between two such matrices of different…

Numerical Analysis · Mathematics 2018-06-06 Lek-Heng Lim , Rodolphe Sepulchre , Ke Ye

In this article, we study holomorphic isometric embeddings between bounded symmetric domains. In particular, we show the total geodesy of any holomorphic isometric embedding between reducible bounded symmetric domains with the same rank.

Complex Variables · Mathematics 2018-03-29 Shan Tai Chan

In this paper, we give a characterization of distance matrices of distance-regular graphs to be invertible.

Combinatorics · Mathematics 2020-08-26 Hui Zhou , Rongquan Feng

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

The generalized distance matrix of a graph is the matrix whose entries depend only on the pairwise distances between vertices, and the generalized distance spectrum is the set of eigenvalues of this matrix. This framework generalizes many…

Combinatorics · Mathematics 2020-07-14 Lee DeVille

We consider two disjoint sets of points. If at least one of the sets can be embedded into an Euclidean space, then we provide sufficient conditions for the two sets to be jointly embedded in one Euclidean space. In this joint Euclidean…

General Mathematics · Mathematics 2023-09-06 N. Alexia Raharinirina , Konstantin Fackeldey , Marcus Weber

We propose a new embedding method for a single vector and for a pair of vectors. This embedding method enables: a) efficient classification and regression of functions of single vectors; b) efficient approximation of distance functions; and…

Machine Learning · Computer Science 2016-08-09 Ofir Pele , Yakir Ben-Aliz

Suppose that there exists a discrete subset $X$ of a complete, connected, $n$-dimensional Riemannian manifold $M$ such that the Riemannian distances between points of $X$ correspond to the Euclidean distances of a net in $\mathbb{R}^{n}$.…

Metric Geometry · Mathematics 2025-06-04 Matan Eilat

A finite set of unlabelled points in Euclidean space is the simplest representation of many real objects from mineral rocks to sculptures. Since most solid objects are rigid, their natural equivalence is rigid motion or isometry maintaining…

Metric Geometry · Mathematics 2023-03-27 Vitaliy Kurlin

We consider mappings satisfying an upper bound for the distortion of families of curves. We establish lower bounds for the distortion of distances under such mappings. As applications, we obtain theorems on the discreteness of the limit…

Complex Variables · Mathematics 2024-11-07 Evgeny Sevost'yanov , Denys Romash , Nataliya Ilkevych

We study the differential geometric properties of the manifold of non-singular symmetric real matrices endowed with the trace metric; in case of positive definite matrices we describe the full group of isometries

Differential Geometry · Mathematics 2018-07-04 Alberto Dolcetti , Donato Pertici

We extend the results of B. Minemyer by showing that any indefinite metric polyhedron (either compact or not) with the vertex degree bounded from above admits an isometric simplicial embedding into a Minkowski space of the lowest possible…

Metric Geometry · Mathematics 2016-12-30 Pavel Galashin , Vladimir Zolotov