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In this article we present a general method to rigorously prove existence of strong solutions to a large class of autonomous semi-linear PDEs in a Hilbert space $H^{l}\subset H^{s}(\mathbb{R}^{m})$ ($s\geq1$) via computer-assisted proofs.…

Analysis of PDEs · Mathematics 2024-03-01 Matthieu Cadiot , Jean-Philippe Lessard , Jean-Christophe Nave

We present a high order, Fourier penalty method for the Maxwell's equations in the vicinity of perfect electric conductor boundary conditions. The approach relies on extending the smooth non-periodic domain of the equations to a periodic…

Numerical Analysis · Mathematics 2016-01-20 Ryan Galagusz , David Shirokoff , Jean-Christophe Nave

We generalize the closest point method (CPM) to solve surface partial differential equations with general boundary conditions. The proposed extrapolation method provides a unified framework for treating a broad class of inhomogeneous…

Numerical Analysis · Mathematics 2025-11-25 Tony Wong , Colin B. Macdonald , Byungjoon Lee

The paper develops a finite element method for partial differential equations posed on hypersurfaces in $\mathbb{R}^N$, $N=2,3$. The method uses traces of bulk finite element functions on a surface embedded in a volumetric domain. The bulk…

Numerical Analysis · Mathematics 2023-07-19 Alexey Y. Chernyshenko , Maxim A. Olshanskii

Neural networks have shown significant potential in solving partial differential equations (PDEs). While deep networks are capable of approximating complex functions, direct one-shot training often faces limitations in both accuracy and…

Numerical Analysis · Mathematics 2025-03-10 Mingxing Weng , Zhiping Mao , Jie Shen

In this paper, we develop an adaptive high-order surface finite element method (FEM) incorporating the spectral deferred correction method for chain contour discretization to solve polymeric self-consistent field equations on general curved…

Numerical Analysis · Mathematics 2021-08-03 Kai Jiang , Xin Wang , Jianggang Liu , Huayi Wei

This paper proposes a novel localized Fourier extension method for approximating non-periodic functions via domain segmentation. By partitioning the computational domain into subregions with uniform discretization scales, the method…

Numerical Analysis · Mathematics 2025-08-29 Zhenyu Zhao , Yanfei Wang

Neural operators improve conventional neural networks by expanding their capabilities of functional mappings between different function spaces to solve partial differential equations (PDEs). One of the most notable methods is the Fourier…

Machine Learning · Computer Science 2024-07-29 Xuanle Zhao , Yue Sun , Tielin Zhang , Bo Xu

The discretization of elliptic PDEs leads to large coupled systems of equations. Domain decomposition methods (DDMs) are one approach to the solution of these systems, and can split the problem in a way that allows for parallel computing.…

Numerical Analysis · Mathematics 2019-08-01 Ian May , Ronald D. Haynes , Steven J. Ruuth

For $\alpha\geq 2$, we investigate a class of Fourier extension operators on fractional surfaces $(\xi,|\xi|^\alpha)$. For the corresponding $\alpha$-Strichartz inequalities, by applying the missing mass method and bilinear restriction…

Classical Analysis and ODEs · Mathematics 2024-07-02 Boning Di , Dunyan Yan

Spectral methods are an important part of scientific computing's arsenal for solving partial differential equations (PDEs). However, their applicability and effectiveness depend crucially on the choice of basis functions used to expand the…

Numerical Analysis · Mathematics 2021-11-10 Brek Meuris , Saad Qadeer , Panos Stinis

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

The study of fractional order differential operators is receiving renewed attention in many scientific fields. In order to accommodate researchers doing work in these areas, there is a need for highly scalable numerical methods for solving…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-28 Max Carlson , Robert M. Kirby , Hari Sundar

We present a dimension-incremental method for function approximation in bounded orthonormal product bases to learn the solutions of various differential equations. Therefore, we decompose the source function of the differential equation…

Numerical Analysis · Mathematics 2025-05-20 Daniel Potts , Fabian Taubert

Partial Differential Equations (PDEs) describe phenomena ranging from turbulence and epidemics to quantum mechanics and financial markets. Despite recent advances in computational science, solving such PDEs for real-world applications…

Machine Learning · Computer Science 2025-05-19 Lothar Heimbach , Sebastian Kaltenbach , Petr Karnakov , Francis J. Alexander , Petros Koumoutsakos

We demonstrate an application of the spectral method as a numerical approximation for solving Hyperbolic PDEs. In this method a finite basis is used for approximating the solutions. In particular, we demonstrate a set of such solutions for…

Mathematical Physics · Physics 2008-11-26 P. Pedram , M. Mirzaei , S. S. Gousheh

Integration operational matrix methods based on Zernike polynomials are used to determine approximate solutions of a class of non-homogeneous partial differential equations (PDEs) of first and second order. Due to the nature of the Zernike…

Analysis of PDEs · Mathematics 2022-07-18 Kanti Bhushan Datta , Somantika Datta

An essential ingredient of a spectral method is the choice of suitable bases for test and trial spaces. On complex domains, these bases are harder to devise, necessitating the use of domain partitioning techniques such as the spectral…

Numerical Analysis · Mathematics 2021-11-17 Saad Qadeer , Ehssan Nazockdast , Boyce E. Griffith

We propose some multigrid methods for solving the algebraic systems resulting from finite element approximations of space fractional partial differential equations (SFPDEs). It is shown that our multigrid methods are optimal, which means…

Numerical Analysis · Mathematics 2018-07-27 Yingjun Jiang , Xuejun Xu

Numerical solutions of partial differential equations (PDEs) on manifolds continues to generate a lot of interest among scientists in the natural and applied sciences. On the other hand, recent developments of 3D scanning and computer…

Numerical Analysis · Mathematics 2016-01-08 E. O. Asante-Asamani , Lei Wang , Zeyun Yu