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We present two algorithms for constructing orthonormal bases of rational function vectors with respect to a discrete inner product, and discuss how to use them for a rational approximation problem. Building on the pencil-based formulation…

Numerical Analysis · Mathematics 2026-01-21 Robbe Vermeiren

This paper deals with the kernel-based approximation of a multivariate periodic function by interpolation at the points of an integration lattice -- a setting that, as pointed out by Zeng, Leung, Hickernell (MCQMC2004, 2006) and Zeng,…

Numerical Analysis · Mathematics 2022-01-25 Vesa Kaarnioja , Yoshihito Kazashi , Frances Y. Kuo , Fabio Nobile , Ian H. Sloan

In this paper we consider an orthonormal basis, generated by a tensor product of Fourier basis functions, half period cosine basis functions, and the Chebyshev basis functions. We deal with the approximation problem in high dimensions…

Numerical Analysis · Mathematics 2024-04-26 Daniel Potts , Pascal Schröter

Performing Bayesian inference on large spatio-temporal models requires extracting inverse elements of large sparse precision matrices for marginal variances, as well as estimating model hyperparameters. Although direct matrix factorizations…

Computation · Statistics 2026-03-17 Abylay Zhumekenov , Elias T. Krainski , Håvard Rue

Multiperforated plates exhibit high gradients and a loss of regularity concentrated in a boundary layer for which a direct numerical simulation becomes very expensive. For elliptic equations the solution at some distance of the boundary is…

Analysis of PDEs · Mathematics 2024-08-22 Kersten Schmidt , Sven Pfaff

In this article, we study dyadic coarsening operators in univariate spline spaces and in tensor-product spline spaces over uniform grids. Our construction is strongly motivated by the work of Bartels, Golub, and Samavati (2006), Some…

Numerical Analysis · Mathematics 2025-11-06 Marcelo Actis , Silvano Figueroa , Eduardo M. Garau

This is a survey on discrete linear operators which, besides approximating in Jackson or near-best order, possess some interpolatory property at some nodes. Such operators can be useful in numerical analysis.

Classical Analysis and ODEs · Mathematics 2007-05-23 J. Szabados

The paper deals with second order parabolic equations on bounded domains with Dirichlet conditions in arbitrary Euclidean spaces. Their interest comes from being models for describing reaction-diffusion processes in several frameworks. A…

Analysis of PDEs · Mathematics 2018-09-10 Irene Benedetti , Luisa Malaguti , Valentina Taddei

Computations with Barvinok's short rational generating functions are traditionally being performed in the dual space, to avoid the combinatorial complexity of inclusion--exclusion formulas for the intersecting proper faces of cones. We…

Combinatorics · Mathematics 2017-01-03 Matthias Köppe , Sven Verdoolaege

A standard technique in infinite dimensional holomorphy, which produced several useful results, uses the Borel transform to represent linear functionals on certain spaces of multilinear operators between Banach spaces as multilinear…

Functional Analysis · Mathematics 2020-06-08 Geraldo Botelho , Raquel Wood

We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. Especially, we apply domain functionals to study the capacities of condensers $(G,E)$…

Numerical Analysis · Mathematics 2021-12-07 Mohamed M. S. Nasser , Oona Rainio , Matti Vuorinen

Evaluating the action of a matrix function on a vector, that is $x=f(\mathcal M)v$, is an ubiquitous task in applications. When $\mathcal M$ is large, one usually relies on Krylov projection methods. In this paper, we provide effective…

Numerical Analysis · Mathematics 2020-07-31 Stefano Massei , Leonardo Robol

A one-to-one continuous function from a triangle to itself is defined that has both interesting number theoretic and analytic properties. This function is shown to be a natural generalization of the classical Minkowski ?(x) function. It is…

Number Theory · Mathematics 2007-05-23 Olga R. Beaver , Thomas Garrity

By closely following a construction by Ganelius, we construct Faber rational functions that allow us to derive tight and explicit bounds on Zolotarev numbers. We use our results to bound the singular values of matrices, including…

Complex Variables · Mathematics 2020-05-11 Daniel Rubin , Alex Townsend , Heather Wilber

Chebyshev spectral methods are widely used in numerical computations. When the underlying function has a singularity, it has been observed by L. N. Trefethen in 2011 that its Chebyshev interpolants exhibit an error localization property,…

Numerical Analysis · Mathematics 2023-06-09 Haiyong Wang

In this article, we use the inverse function theorem for Banach spaces to interpolate a given real analytic spacelike curve $a$ in Lorentz-Minkowski space $\mathbb{L}^3$ to another real analytic spacelike curve $c$, which is ``close" enough…

Differential Geometry · Mathematics 2024-07-19 Rukmini Dey , Rahul Kumar Singh

We construct two bounded functional calculi for sectorial operators on Banach spaces, which enhance the functional calculus for analytic Besov functions, by extending the class of functions, generalizing and sharpening estimates, and…

Functional Analysis · Mathematics 2021-08-03 Charles Batty , Alexander Gomilko , Yuri Tomilov

We consider bivariate polynomials orthogonal on the bicircle with respect to a positive linear functional. The lexicographical and reverse lexicographical orderings are used to order the monomials. Recurrence formulas are derived between…

Classical Analysis and ODEs · Mathematics 2007-05-23 Jeffrey S. Geronimo , Hugo Woerdeman

Reducing a set of diverse bulk-optic-based optical components to a single ultrathin and compact element that enables the same complex functionality has become an emerging research area, propelling further integration and miniaturization in…

Optics · Physics 2019-04-15 Fei Ding , Yiting Chen , Yuanqing Yang , Sergey I. Bozhevolnyi

Real-world machine learning applications may require functions that are fast-to-evaluate and interpretable. In particular, guaranteed monotonicity of the learned function can be critical to user trust. We propose meeting these goals for…

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