English
Related papers

Related papers: On Unit Spherical Euclidean Distance Matrices Whic…

200 papers

A recent generalization of the Erd\H{o}s Unit Distance Problem, proposed by Palsson, Senger and Sheffer, asks for the maximum number of unit distance paths with a given number of vertices in the plane and in $3$-space. Studying a variant of…

Combinatorics · Mathematics 2023-01-23 Nora Frankl , Dora Woodruff

Consider an arrangement of $n$ congruent zones on the $d$-dimensional unit sphere $S^{d-1}$, where a zone is the intersection of an origin symmetric Euclidean plank with $S^{d-1}$. We prove that, for sufficiently large $n$, it is possible…

Metric Geometry · Mathematics 2026-04-13 A. Bezdek , F. Fodor , V. Vígh , T. Zarnócz

This paper proposes two algorithms for estimating square Wasserstein distance matrices from a small number of entries. These matrices are used to compute manifold learning embeddings like multidimensional scaling (MDS) or Isomap, but…

Machine Learning · Statistics 2026-05-20 Muhammad Rana , Abiy Tasissa , HanQin Cai , Yakov Gavriyelov , Keaton Hamm

The discrete Fr{\'e}chet distance is a measure of similarity between point sequences which permits to abstract differences of resolution between the two curves, approximating the original Fr{\'e}chet distance between curves. Such distance…

Computational Geometry · Computer Science 2018-06-05 Jérémy Barbay

We study configurations of points on the unit sphere that minimize potential energy for a broad class of potential functions (viewed as functions of the squared Euclidean distance between points). Call a configuration sharp if there are m…

Metric Geometry · Mathematics 2012-03-15 Henry Cohn , Abhinav Kumar

An $L$-spherical code is a set of Euclidean unit vectors whose pairwise inner products belong to the set $L$. We show, for a fixed $\alpha,\beta>0$, that the size of any $[-1,-\beta]\cup\{\alpha\}$-spherical code is at most linear in the…

Combinatorics · Mathematics 2016-02-26 Boris Bukh

We discuss a scenario of ``the path to physics at the Planck scale'' where todays theory of the interactions of elementary particles, the so called Standard Model (SM), emerges as a low energy effective theory describing the long distance…

High Energy Physics - Theory · Physics 2007-05-23 F. Jegerlehner

It is shown that given a set of $N$ points in the plane or on the sphere, there is a subset of size $\gtrsim N^{1/3}/\log N$ with all pairwise distances between points distinct.

Combinatorics · Mathematics 2014-04-08 Marcos Charalambides

We discuss umbral calculus as a method of systematically discretizing linear differential equations while preserving their point symmetries as well as generalized symmetries. The method is then applied to the Schr\"{o}dinger equation in…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Decio Levi , Piergiulio Tempesta , Pavel Winternitz

Invariant integrals of functions and forms over $q$ - deformed Euclidean space and spheres in $N$ dimensions are defined and shown to be positive definite, compatible with the star - structure and to satisfy a cyclic property involving the…

q-alg · Mathematics 2009-10-28 Harold Steinacker

The electric dipole moments (EDMs) of the neutron and the electron are reviewed within the framework of the supersymmetric standard model (SSM) based on grand unified theories coupled to N=1 supergravity. Taking into account one-loop and…

High Energy Physics - Phenomenology · Physics 2007-05-23 Mayumi Aoki , Tomoko Kadoyoshi , Akio Sugamoto , Noriyuki Oshimo

Dynamical dark matter (DDM) is a new framework for dark-matter physics in which the dark sector comprises an ensemble of individual component fields which collectively conspire to act in ways that transcend those normally associated with…

High Energy Physics - Phenomenology · Physics 2013-05-30 Keith R. Dienes , Shufang Su , Brooks Thomas

We consider the moduli spaces $\mathcal{M}_d(\ell)$ of a closed linkage with $n$ links and prescribed lengths $\ell\in \mathbb{R}^n$ in $d$-dimensional Euclidean space. For $d>3$ these spaces are no longer manifolds generically, but they…

Algebraic Topology · Mathematics 2016-03-09 Dirk Schuetz

Alternative novel measures of the distance between any two partitions of a n-set are proposed and compared, together with a main existing one, namely 'partition-distance' D(.,.). The comparison achieves by checking their restriction to…

Discrete Mathematics · Computer Science 2011-06-24 Giovanni Rossi

Geometrical objects with integral sides have attracted mathematicians for ages. For example, the problem to prove or to disprove the existence of a perfect box, that is, a rectangular parallelepiped with all edges, face diagonals and space…

Combinatorics · Mathematics 2019-11-12 Sascha Kurz , Reinhard Laue

We develop several methods, based on the geometric relationship between the eigenspaces of a matrix and its adjoint, for determining whether a square matrix having distinct eigenvalues is unitarily equivalent to a complex symmetric matrix.…

Functional Analysis · Mathematics 2010-03-16 Stephan Ramon Garcia , Levon Balayan

Consider a set $P$ of $n$ points in $\mathbb{R}^d$. In the discrete median line segment problem, the objective is to find a line segment bounded by a pair of points in $P$ such that the sum of the Euclidean distances from $P$ to the line…

Computational Geometry · Computer Science 2022-02-16 Ovidiu Daescu , Ka Yaw Teo

This paper is concerned with a structural analysis of euclidean field theories on the euclidean sphere. In the first section we give proposal for axioms for a euclidean field theory on a sphere in terms of C*-algebras. Then, in the second…

High Energy Physics - Theory · Physics 2007-05-23 Dirk Schlingemann

We consider the unitary group $\U$ of complex, separable, infinite-dimensional Hilbert space as a discrete group. It is proved that, whenever $\U$ acts by isometries on a metric space, every orbit is bounded. Equivalently, $\U$ is not the…

Functional Analysis · Mathematics 2007-05-23 Eric Ricard , Christian Rosendal

Deep distance metric learning (DDML), which is proposed to learn image similarity metrics in an end-to-end manner based on the convolution neural network, has achieved encouraging results in many computer vision tasks.$L2$-normalization in…

Computer Vision and Pattern Recognition · Computer Science 2018-03-29 Xuefei Zhe , Shifeng Chen , Hong Yan
‹ Prev 1 8 9 10 Next ›