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Related papers: Local approximation operators on box meshes

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A mesh-free numerical method for solving linear elliptic PDE's using the local kernel theory that was developed for manifold learning is proposed. In particular, this novel approach exploits the local kernel theory which allows one to…

Numerical Analysis · Mathematics 2019-07-02 Faheem Gilani , John Harlim

The best polynomial approximation and Chebyshev approximation are both important in numerical analysis. In tradition, the best approximation is regarded as more better than the Chebyshev approximation, because it is usually considered in…

Numerical Analysis · Mathematics 2021-11-17 Xiaolong Zhang

For various Hilbert spaces of analytic functions on the unit disk, we characterize when a function $f$ has optimal polynomial approximants given by truncations of a single power series. We also introduce a generalized notion of optimal…

Functional Analysis · Mathematics 2023-07-11 Christopher Felder

The purpose of this article is to study operators whose kernel share some key features of Bergman kernels from complex analysis, and are approximate projectors. It turns out that they must be associated with a rich set of geometric data, on…

Complex Variables · Mathematics 2024-07-10 Yannick Guedes Bonthonneau

We study approximation properties of weighted $L^2$-orthogonal projectors onto spaces of polynomials of bounded degree in the Euclidean unit ball, where the weight is of the generalized Gegenbauer form $x \mapsto (1-\|x\|^2)^\alpha$,…

Classical Analysis and ODEs · Mathematics 2017-05-23 Leonardo E. Figueroa

Present work contains a method to obtain Jackson and Stechkin type inequalities of approximation by integral functions of finite degree (IFFD) in some variable exponent Lebesgue space of real functions defined on $\boldsymbol{R}:=\left(…

Functional Analysis · Mathematics 2022-08-30 Ramazan Akgün

In this paper, we investigate the approximation problem for functions in Gaussian Sobolev spaces $W^s_p(\mathbb{R}^d, \gamma)$ of smoothness $s > 0$, where the approximation error is measured in the Gaussian Lebesgue space…

Functional Analysis · Mathematics 2026-04-21 Van Kien Nguyen

This paper reviews the state of the art and discusses recent developments in the field of adaptive isogeometric analysis, with special focus on the mathematical theory. This includes an overview of available spline technologies for the…

Numerical Analysis · Mathematics 2022-11-18 Annalisa Buffa , Gregor Gantner , Carlotta Giannelli , Dirk Praetorius , Rafael Vázquez

An important observation in compressed sensing is that the $\ell_0$ minimizer of an underdetermined linear system is equal to the $\ell_1$ minimizer when there exists a sparse solution vector and a certain restricted isometry property…

Numerical Analysis · Mathematics 2020-06-23 Yuji Nakatsukasa , Alex Townsend

We study the local statistics of orthogonal polynomial ensembles near a hard edge, subject to a multiplicative deformation of the measure. Probabilistically, this deformation corresponds to a position-dependent conditional thinning of the…

Mathematical Physics · Physics 2026-02-23 Leslie Molag , Guilherme L. F. Silva , Lun Zhang

We design quasi-interpolation operators based on piecewise polynomial weight functions of degree less than or equal to $p$ that map into the space of continuous piecewise polynomials of degree less than or equal to $p+1$. We show that the…

Numerical Analysis · Mathematics 2024-04-23 Thomas Führer , Manuel A. Sánchez

Trimming consists of cutting away parts of a geometric domain, without reconstructing a global parametrization (meshing). It is a widely used operation in computer aided design, which generates meshes that are unfitted with the described…

Numerical Analysis · Mathematics 2022-08-10 Annalisa Buffa , Ondine Chanon , Rafael Vázquez

We revisit the definition of transverse frames and tetrad choices with regards to its application to numerically generated spacetimes, in particular those from the merger of binary black holes. We introduce the concept of local and…

General Relativity and Quantum Cosmology · Physics 2021-08-25 Nicole Rosato , Hiroyuki Nakano , Carlos O. Lousto

We study the problem of approximating the Ising model partition function with complex parameters on bounded degree graphs. We establish a deterministic polynomial-time approximation scheme for the partition function when the interactions…

Quantum Physics · Physics 2019-07-12 Ryan L. Mann , Michael J. Bremner

The characterisation of small low conducting inclusions in an otherwise uniform background from low-frequency electrical field measurements has important applications in medical imaging using electrical impedance tomography as well as in…

Numerical Analysis · Mathematics 2022-06-24 A. A. S. Amad , P. D. Ledger , T. Betcke , D. Praetorius

Optimal packing of objects in containers is a critical problem in various real-life and industrial applications. This paper investigates the two-dimensional packing of convex polygons without rotations, where only translations are allowed.…

Computational Geometry · Computer Science 2023-08-17 Adam Kurpisz , Silvan Suter

This article is the second one of three successive articles of the authors on the matrix-weighted Besov-type and Triebel--Lizorkin-type spaces. In this article, we obtain the sharp boundedness of almost diagonal operators on matrix-weighted…

Functional Analysis · Mathematics 2024-08-22 Fan Bu , Tuomas Hytönen , Dachun Yang , Wen Yuan

We prove local inverse-type estimates for the four non-local boundary integral operators associated with the Laplace operator on a bounded d-dimensional Lipschitz domain Omega for d >= 2 with piecewise smooth boundary. For piecewise…

Numerical Analysis · Mathematics 2017-12-04 Markus Aurada , Michael Feischl , Thomas Führer , Michael Karkulik , Jens Markus Melenk , Dirk Praetorius

We study some properties of smoothing kernels and their local expression as they appear in the construction of Colombeau-type generalized function algebras which are diffeomorphism invariant.

Functional Analysis · Mathematics 2016-04-12 Eduard A. Nigsch

We consider the sparse polynomial approximation of a multivariate function on a tensor product domain from samples of both the function and its gradient. When only function samples are prescribed, weighted $\ell^1$ minimization has recently…

Numerical Analysis · Mathematics 2019-02-22 Ben Adcock , Yi Sui
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