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We introduce an interpolation--regression operator for polynomial approximation on the unit sphere $\mathbb{S}^2$ from discrete samples. The approximant is a spherical polynomial of degree $r$ which interpolates the data on a prescribed…

Numerical Analysis · Mathematics 2026-05-14 Francesco Dell'Accio , Federico Nudo , Teresa E. Pérez , Miguel A. Piñar

In this paper, we collect the basic theory and the most important applications of a novel technique that has shown to be suitable for scattered data interpolation, quadrature, bio-imaging reconstruction. The method relies on polynomial…

Numerical Analysis · Mathematics 2022-04-05 Stefano De Marchi , Giacomo Elefante , Elisa Francomano , Francesco Marchetti

We prove lower bounds on the error incurred when approximating any oscillating function using piecewise polynomial spaces. The estimates are explicit in the polynomial degree and have optimal dependence on the meshwidth and frequency when…

Numerical Analysis · Mathematics 2024-12-05 Jeffrey Galkowski

In this paper we study Strichartz estimates for dispersive equations which are defined by radially symmetric pseudo-differential operators, and of which initial data belongs to spaces of Sobolev type defined in spherical coordinates. We…

Analysis of PDEs · Mathematics 2012-12-06 Yonggeun Cho , Sanghyuk Lee

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

We consider polynomial approximation over the interval $[-1,1]$ by regularized weighted discrete least squares methods with $\ell_2-$ or $\ell_1-$regularization, respectively. As the set of nodes we use Gauss quadrature points (which are…

Numerical Analysis · Mathematics 2019-08-27 Congpei An , Hao-Ning Wu

In this paper, we introduce a new operator, $\mathcal{S}$, which is closely related to the restriction problem for spheres in $\mathbb{F}_q^d$, the $d$-dimensional vector space over the finite field $\mathbb{F}_q$ with $q$ elements. The…

Classical Analysis and ODEs · Mathematics 2025-02-19 Hunseok Kang , Doowon Koh

Subspaces obtained by the orthogonal projection of locally supported square-integrable vector fields onto the Hardy spaces $H_+(\mathbb{S})$ and $H_-(\mathbb{S})$, respectively, play a role in various inverse potential field problems since…

Numerical Analysis · Mathematics 2023-07-06 Christian Gerhards , Xinpeng Huang

This paper develops a fully discrete soft thresholding polynomial approximation over a general region, named Lasso hyperinterpolation. This approximation is an $\ell_1$-regularized discrete least squares approximation under the same…

Numerical Analysis · Mathematics 2021-08-31 Congpei An , Hao-Ning Wu

In this paper we extend the Shepard-Bernoulli operators introduced in [6] to the bivariate case. These new interpolation operators are realized by using local support basis functions introduced in [23] instead of classical Shepard basis…

Numerical Analysis · Mathematics 2014-06-24 F. Dell'Accio , F. Di Tommaso

We consider computing eigenspaces of an elliptic self-adjoint operator depending on a countable number of parameters in an affine fashion. The eigenspaces of interest are assumed to be isolated in the sense that the corresponding…

Numerical Analysis · Mathematics 2021-03-16 Luka Grubišić , Harri Hakula , Mikael Laaksonen

We show that the symmetry operators for the quantum superintegrable system on the 3-sphere with generic 4-parameter potential form a closed quadratic algebra with 6 linearly independent generators that closes at order 6 (as differential…

Mathematical Physics · Physics 2011-05-31 Ernie G. Kalnins , Willard Miller , Sarah Post

We present a method for constructing superoscillatory functions the superoscillatory part of which approximates a given polynomial with arbitrarily small error in a fixed interval. These functions are obtained as the product of the…

Mathematical Physics · Physics 2015-04-21 Ioannis Chremmos , George Fikioris

Spherical $t$-designs are finite point sets on the unit sphere that enable exact integration of polynomials of degree at most $t$ via equal-weight quadrature. This concept has recently been extended to spherical $t$-design curves by the use…

Combinatorics · Mathematics 2025-03-05 Martin Ehler

Spherical $t$-designs on $\mathbb{S}^{d}\subset\mathbb{R}^{d+1}$ provide $N$ nodes for an equal weight numerical integration rule which is exact for all spherical polynomials of degree at most $t$. This paper considers the generation of…

Numerical Analysis · Mathematics 2017-09-07 Robert S. Womersley

Lattice rules and polynomial lattice rules are quadrature rules for approximating integrals over the $s$-dimensional unit cube. Since no explicit constructions of such quadrature methods are known for dimensions $s > 2$, one usually has to…

Numerical Analysis · Mathematics 2014-04-23 Josef Dick , Peter Kritzer , Gunther Leobacher , Friedrich Pillichshammer

We propose a high-precision numerical quadrature framework based on local Fourier extension (LFE) approximations. The method constructs, on each subinterval, a truncated-SVD stabilized local Fourier continuation of the integrand on an…

Numerical Analysis · Mathematics 2026-03-17 Xinran Liu , Zhenyu Zhao , Benxue Gong

A high-order quadrature algorithm is presented for computing integrals over curved surfaces and volumes whose geometry is implicitly defined by the level sets of (one or more) multivariate polynomials. The algorithm recasts the implicitly…

Numerical Analysis · Mathematics 2021-11-24 Robert I. Saye

The paper discusses the construction of high dimensional spatial discretizations for arbitrary multivariate trigonometric polynomials, where the frequency support of the trigonometric polynomial is known. We suggest a construction based on…

Numerical Analysis · Mathematics 2017-11-20 Lutz Kämmerer

Designing scalable estimation algorithms is a core challenge in modern statistics. Here we introduce a framework to address this challenge based on parallel approximants, which yields estimators with provable properties that operate on the…

Methodology · Statistics 2023-08-04 Aritra Chakravorty , William S. Cleveland , Patrick J. Wolfe
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