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We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the…

High Energy Physics - Lattice · Physics 2009-06-09 Cayetano Di Bartolo , Lorenzo Leal

We study the problem of compression for the purpose of similarity identification, where similarity is measured by the mean square Euclidean distance between vectors. While the asymptotical fundamental limits of the problem - the minimal…

Information Theory · Computer Science 2014-05-13 Fabian Steiner , Steffen Dempfle , Amir Ingber , Tsachy Weissman

Geometric properties of $N$ random points distributed independently and uniformly on the unit sphere $\mathbb{S}^{d}\subset\mathbb{R}^{d+1}$ with respect to surface area measure are obtained and several related conjectures are posed. In…

We propose a method of solving partial differential equations on the $n$-dimen\-sional unit sphere with methods based on the continuous wavelet transform derived from approximate identities.

Mathematical Physics · Physics 2021-09-06 {Ilona Iglewska-Nowak , Piotr Stefaniak

We present in this paper new multiscale transforms on the sphere, namely the isotropic undecimated wavelet transform, the pyramidal wavelet transform, the ridgelet transform and the curvelet transform. All of these transforms can be…

Astrophysics · Physics 2016-08-30 Jean-Luc Starck , Yassir Moudden , Pierrick Abrial , Mai Nguyen

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required…

Numerical Analysis · Mathematics 2017-10-10 Abdul-Lateef Haji-Ali , Fabio Nobile , Raúl Tempone , Sören Wolfers

This work presents the construction of a novel spherical wavelet basis designed for incomplete spherical datasets, i.e. datasets which are missing in a particular region of the sphere. The eigenfunctions of the Slepian spatial-spectral…

Information Theory · Computer Science 2023-04-24 Patrick J. Roddy , Jason D. McEwen

In [1], the author considered the problem of the optimal approximation of symmetric surfaces by biquadratic B\'ezier patches. Unfortunately, the results therein are incorrect, which is shown in this paper by considering the optimal…

Numerical Analysis · Mathematics 2023-03-09 Aleš Vavpetič , Emil Žagar

In this paper, the numerical approximation of isometric deformations of thin elastic shells is discussed. To this end, for a thin shell represented by a parametrized surface, it is shown how to transform the stored elastic energy for an…

Numerical Analysis · Mathematics 2022-07-01 Martin Rumpf , Stefan Simon , Christoph Smoch

This paper proves joint convergence of the approximation error for several stochastic integrals with respect to local Brownian semimartingales, for nonequidistant and random grids. The conditions needed for convergence are that the Lebesgue…

Probability · Mathematics 2013-09-24 Carl Lindberg , Holger Rootzén

We obtain discrete mixture representations for parametric families of probability distributions on Euclidean spheres, such as the von Mises--Fisher, the Watson and the angular Gaussian families. In addition to several special results we…

Probability · Mathematics 2023-02-22 Ludwig Baringhaus , Rudolf Grübel

Many statistical and machine learning approaches rely on pairwise distances between data points. The choice of distance metric has a fundamental impact on performance of these procedures, raising questions about how to appropriately…

Statistics Theory · Mathematics 2020-04-20 Didong Li , David B Dunson

Wavelets are widely used in various disciplines to analyse signals both in space and scale. Whilst many fields measure data on manifolds (i.e., the sphere), often data are only observed on a partial region of the manifold. Wavelets are a…

Information Theory · Computer Science 2023-04-24 Patrick J. Roddy

This paper presents a new approach to the estimation of the deformation of an isotropic Gaussian random field on $\mathbb{R}^2$ based on dense observations of a single realization of the deformed random field. Under this framework we…

Statistics Theory · Mathematics 2008-12-18 Ethan B. Anderes , Michael L. Stein

In this exploratory article, we present a constructive method for scattering points on the surface of $d$ dimensional spheres which we believe is new and of interest. Indeed, the problem of uniformly distributing points on spheres is an…

Number Theory · Mathematics 2016-10-24 Béla Bajnok , Steven B. Damelin , Jenny Li , Gary L. Mullen

In this paper we formulate a weighted version of minimum problem (1.4) on the sphere and we show that, for $K\le L$, if $\set{\phi_k}^K_{k=1}$ consists of the spherical functions with degree less than $N$ we can localize the points…

Classical Analysis and ODEs · Mathematics 2008-08-11 Margit Pap

This work is concerned with the study of asymptotic properties of nonparametric density estimates in the framework of circular data. The estimation procedure here applied is based on wavelet thresholding methods: the wavelets used are the…

Statistics Theory · Mathematics 2016-03-16 Claudio Durastanti

Excitation of surface-plasmon resonances of closely spaced nanometallic structures is a key technique used in nanoplasmonics to control light on subwavelength scales and generate highly confined electric-field hotspots. In this paper we…

Optics · Physics 2018-07-05 Ory Schnitzer

In this paper we introduce a polynomial frame on the unit sphere $\sph$ of $\mathbb{R}^d$, for which every distribution has a wavelet-type decomposition. More importantly, we prove that many function spaces on the sphere $\sph$, such as…

Classical Analysis and ODEs · Mathematics 2007-05-23 Feng Dai

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets of node and edge types subject to edge length and…

Computational Geometry · Computer Science 2021-02-03 Andreas M. Tillmann , Leif Kobbelt
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