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This paper deals with the equation $-\Delta u+\mu u=f$ on high-dimensional spaces $\mathbb{R}^m$, where the right-hand side $f(x)=F(Tx)$ is composed of a separable function $F$ with an integrable Fourier transform on a space of a dimension…

Numerical Analysis · Mathematics 2024-11-19 Harry Yserentant

In this paper a fourth order finite difference ghost point method for the Poisson equation on regular Cartesian mesh is presented. The method can be considered the high order extension of the second ghost method introduced earlier by the…

Numerical Analysis · Mathematics 2024-05-24 Armando Coco , Giovanni Russo

In this work, we consider alternative discretizations for PDEs which use expansions involving integral operators to approximate spatial derivatives. These constructions use explicit information within the integral terms, but treat boundary…

Computational Physics · Physics 2024-11-12 Andrew J. Christlieb , Pierson T. Guthrey , William A. Sands , Mathialakan Thavappiragasm

The random feature method (RFM), a mesh-free machine learning-based framework, has emerged as a promising alternative for solving PDEs on complex domains. However, for large three-dimensional nonlinear problems, attaining high accuracy…

Numerical Analysis · Mathematics 2025-10-07 Longze Tan

Nonlocality brings many challenges to the implementation of finite element methods (FEM) for nonlocal problems, such as large number of queries and invoke operations on the meshes. Besides, the interactions are usually limited to Euclidean…

Numerical Analysis · Mathematics 2023-02-16 Gengjian Chen , Yuheng Ma , Jiwei Zhang

In this paper, we extend the Generalized Finite Difference Method (GFDM) on unknown compact submanifolds of the Euclidean domain, identified by randomly sampled data that (almost surely) lie on the interior of the manifolds. Theoretically,…

Numerical Analysis · Mathematics 2023-07-18 Shixiao W. Jiang , Rongji Li , Qile Yan , John Harlim

Symbolic regression with polynomial neural networks and polynomial neural ordinary differential equations (ODEs) are two recent and powerful approaches for equation recovery of many science and engineering problems. However, these methods…

Machine Learning · Computer Science 2023-08-28 Colby Fronk , Jaewoong Yun , Prashant Singh , Linda Petzold

In this paper we present a method to treat interface jump conditions for constant coefficients Poisson problems that allows the use of standard "black box" solvers, without compromising accuracy. The basic idea of the new approach is…

Numerical Analysis · Mathematics 2011-09-30 Alexandre Noll Marques , Jean-Christophe Nave , Rodolfo Ruben Rosales

The ion distribution around charged colloids in solution has been investigated intensely during the last decade. However, few theoretical approaches have included the influence of variation in the dielectric permittivity within the system,…

Soft Condensed Matter · Physics 2015-06-18 Florian Fahrenberger , Zhenli Xu , Christian Holm

A new and efficient neural-network and finite-difference hybrid method is developed for solving Poisson equation in a regular domain with jump discontinuities on embedded irregular interfaces. Since the solution has low regularity across…

Numerical Analysis · Mathematics 2023-06-13 Wei-Fan Hu , Te-Sheng Lin , Yu-Hau Tseng , Ming-Chih Lai

We present a novel general framework to deal with forward and backward components of the electromagnetic field in axially-invariant nonlinear optical systems, which include those having any type of linear or nonlinear transverse…

In this note, we develop Fourier approximation methods for the solutions of first-order nonlocal mean-field games (MFG) systems. Using Fourier expansion techniques, we approximate a given MFG system by a simpler one that is equivalent to a…

Analysis of PDEs · Mathematics 2019-01-21 Levon Nurbekyan , Joao Saude

We present a simple hierarchical communication scheme for distributed Fast Multipole Methods (FMMs) based on MPI neighborhood collectives and uniform trees. The method targets the common case of extending an existing high-performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-01 Srinath Kailasa

A novel method rooted in the classical Schwarz-Christoffel transformation from the disk is introduced, which allows for fast and accurate solution of potential field problems in possibly inhomogeneous and multiply connected domains: this is…

Numerical Analysis · Mathematics 2018-12-24 Stefano Costa

We consider the problem of simultaneously inferring the heterogeneous coefficient field for a Robin boundary condition on an inaccessible part of the boundary along with the shape of the boundary for the Poisson problem. Such a problem…

Optimization and Control · Mathematics 2022-01-05 Ruanui Nicholson , Matti Niskanen

We consider the isogeometric analysis for fractional PDEs involving the fractional Laplacian in two dimensions. An isogeometric collocation method is developed to discretize the fractional Laplacian and applied to the fractional Poisson…

Numerical Analysis · Mathematics 2020-05-12 Kailai Xu , Eric Darve

This paper applies the Recursive Projection Method (RPM) to the problem of finding the effective mechanical response of a periodic heterogeneous solid. Previous works apply the Fast Fourier Transform (FFT) in combination with various…

Computational Engineering, Finance, and Science · Computer Science 2020-03-18 Xiaoyao Peng , Dhriti Nepal , Kaushik Dayal

The Laplace transform method for solving of a wide class of initial value problems for fractional differential equations is introduced. The method is based on the Laplace transform of the Mittag-Leffler function in two parameters. To extend…

funct-an · Mathematics 2007-05-23 Igor Podlubny

This paper deals with simultaneously fast and in-place algorithms for formulae where the result has to be linearly accumulated: some output variables are also input variables, linked by a linear dependency. Fundamental examples include the…

Symbolic Computation · Computer Science 2025-11-07 Jean-Guillaume Dumas , Bruno Grenet

We consider fast kernel summations in high dimensions: given a large set of points in $d$ dimensions (with $d \gg 3$) and a pair-potential function (the {\em kernel} function), we compute a weighted sum of all pairwise kernel interactions…

Machine Learning · Computer Science 2015-02-16 William B. March , George Biros
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