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Related papers: Approximation by amplitude and frequency operators

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We study the interpolation analogue of the Hermite-Pad\'e type I approximation problem. We provide its determinant solution and we write down the corresponding integrable discrete system as an admissible reduction of Hirota's discrete…

Exactly Solvable and Integrable Systems · Physics 2023-01-06 Adam Doliwa

This paper aims at developing new shape functions adapted to smooth vanishing coefficients for scalar wave equation. It proposes the numerical analysis of their interpolation properties. The interpolation is local but high order convergence…

Numerical Analysis · Mathematics 2019-08-16 Lise-Marie Imbert-Gerard

We consider nodal-based Lagrangian interpolations for the finite element approximation of the Maxwell eigenvalue problem. The first approach introduced is a standard Galerkin method on Powell-Sabin meshes, which has recently been shown to…

Numerical Analysis · Mathematics 2023-04-04 Daniele Boffi , Ramon Codina , Önder Türk

Multipoint polynomial evaluation and interpolation are fundamental for modern symbolic and numerical computing. The known algorithms solve both problems over any field of constants in nearly linear arithmetic time, but the cost grows to…

Numerical Analysis · Mathematics 2017-04-19 Victor Y. Pan

High-frequency issues have been remarkably challenges in numerical methods for partial differential equations. In this paper, a learning based numerical method (LbNM) is proposed for Helmholtz equation with high frequency. The main novelty…

Numerical Analysis · Mathematics 2024-01-18 Yu Chen , Jin Cheng , Tingyue Li , Yun Miao

First, an abstract scheme of constructing biorthogonal rational systems related to some interpolation problems is proposed. We also present a modification of the famous step-by-step process of solving the Nevanlinna-Pick problems for…

Classical Analysis and ODEs · Mathematics 2008-06-28 Maxim S. Derevyagin , Alexei S. Zhedanov

We describe an extension of the Taylor method for the numerical solution of ODEs that uses Pad\'e approximants to obtain extremely precise numerical results. The accuracy of the results is essentially limited only by the computer time and…

Computational Physics · Physics 2022-05-04 Paolo Amore

We describe how to solve simultaneous Pad\'e approximations over a power series ring $K[[x]]$ for a field $K$ using $O~(n^{\omega - 1} d)$ operations in $K$, where $d$ is the sought precision and $n$ is the number of power series to…

Symbolic Computation · Computer Science 2016-05-24 Johan S. R. Nielsen , Arne Storjohann

We give a complete characterization of limiting interpolation spa\-ces for the real method of interpolation using extrapolation theory. For this purpose the usual tools (e.g., Boyd indices or the boundedness of Hardy type operators) are not…

Functional Analysis · Mathematics 2018-09-05 Sergey V. Astashkin , Konstantin V. Lykov , Mario Milman

A fast full-wave simulation technique is presented for the analysis of large irregular planar arrays of identical 3-D metallic antennas. The solution method relies on the Macro Basis Functions (MBF) approach and an interpolatory technique…

Instrumentation and Methods for Astrophysics · Physics 2018-05-09 Ha Bui-Van , Jens Abraham , Michel Arts , Quentin Gueuning , Christopher Raucy , David Gonzalez-Ovejero , Eloy de Lera Acedo , Christophe Craeye

We present a novel barycentric interpolation algorithm designed for analytic functions $f\in\mathcal{A}(E)$ defined on the complex plane. The algorithm, which encompasses both polynomial and rational interpolation, is tailored to handle…

Numerical Analysis · Mathematics 2024-07-23 Kelong Zhao , shuhuang Xiang

We propose a numerical method to approximate the scattering amplitudes for the elasticity system with a non-constant matrix potential in dimensions $d=2$ and $3$. This requires to approximate first the scattering field, for some incident…

Numerical Analysis · Mathematics 2021-07-27 Juan A. Barceló , Carlos Castro

Reliable approximations for correlation functions at intermediate and strong coupling remain hard to obtain for general quantum field theories. Perturbative expansions are often asymptotic or have a finite radius of convergence, which…

High Energy Physics - Lattice · Physics 2026-05-11 Yuanran Zhu , Efekan Kökcü , Chao Yang

We propose a method for the treatment of two--point boundary value problems given by nonlinear ordinary differential equations. The approach leads to sequences of roots of Hankel determinants that converge rapidly towards the unknown…

Mathematical Physics · Physics 2007-05-29 Paolo Amore , Francisco M. Fernandez

Operator convex functions defined on the positive half-line play a prominent role in the theory of quantum information, where they are used to define quantum $f$-divergences. Such functions admit integral representations in terms of…

Optimization and Control · Mathematics 2023-05-23 Oisín Faust , Hamza Fawzi

Deterministic neural operators perform well on many PDEs but can struggle with the approximation of high-frequency wave phenomena, where strong input-to-output sensitivity makes operator learning challenging, and spectral bias blurs…

Machine Learning · Computer Science 2026-02-05 Yicheng Zou , Samuel Lanthaler , Hossein Salahshoor

For $m,n \in \mathbb{N}$, $m\geq 1$ and a given function $f : \mathbb{R}^m\longrightarrow \mathbb{R}$ the polynomial interpolation problem (PIP) is to determine a \emph{generic node set} $P \subseteq \mathbb{R}^m$ and the coefficients of…

Numerical Analysis · Mathematics 2017-10-31 M. Hecht , B. L. Cheeseman , K. B. Hoffmann , I. F. Sbalzarini

Let $f$ belong to the Hardy space $H^2(\mathbb{D})$ of the unit disc, and $e_a$ the normalized Szeg\"o (reproducing) kernel of $H^2(\mathbb{D}).$ It is well known that, due to the reproducing kernel property, for any distinct $n$ points…

Complex Variables · Mathematics 2026-04-28 Tao Qian , Yunni Wu , Wei Qu , Yanbo Wang

Machine learning approaches relying on such criteria as adversarial robustness or multi-agent settings have raised the need for solving game-theoretic equilibrium problems. Of particular relevance to these applications are methods targeting…

Machine Learning · Computer Science 2023-10-27 Xufeng Cai , Ahmet Alacaoglu , Jelena Diakonikolas

The use of neural networks to approximate partial differential equations (PDEs) has gained significant attention in recent years. However, the approximation of PDEs with localised phenomena, e.g., sharp gradients and singularities, remains…

Numerical Analysis · Mathematics 2025-01-30 Santiago Badia , Wei Li , Alberto F. Martín
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