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We adopt the integral definition of the fractional Laplace operator and study an optimal control problem on Lipschitz domains that involves a fractional elliptic partial differential equation (PDE) as state equation and a control variable…

Numerical Analysis · Mathematics 2024-02-14 Francisco Bersetche , Francisco Fuica , Enrique Otarola , Daniel Quero

In this work we study the convergence properties of the one-level parallel Schwarz method with Robin transmission conditions applied to the one-dimensional and two-dimensional Helmholtz and Maxwell's equations. One-level methods are not…

Numerical Analysis · Mathematics 2022-01-13 Niall Bootland , Victorita Dolean , Alexandros Kyriakis , Jennifer Pestana

We analyze and test using Fourier extensions that minimize a Hilbert space norm for the purpose of solving partial differential equations (PDEs) on surfaces. In particular, we prove that the approach is arbitrarily high-order and also show…

Numerical Analysis · Mathematics 2025-12-30 Daniel R. Venn , Steven J. Ruuth

An error analysis of trigonometric integrators (or exponential integrators) applied to spatial semi-discretizations of semilinear wave equations with periodic boundary conditions in one space dimension is given. In particular, optimal…

Numerical Analysis · Mathematics 2015-02-03 Ludwig Gauckler

This paper addresses the efficient solution of linear systems arising from curl-conforming finite element discretizations of $H(\mathrm{curl})$ elliptic problems with heterogeneous coefficients. We first employ the discrete form of a…

Numerical Analysis · Mathematics 2025-06-10 Chupeng Ma , Yongwei Zhang

This paper builds on the algebraic theory in the companion paper [Algebraic Error Analysis for Mixed-Precision Multigrid Solvers] to obtain discretization-error-accurate solutions for linear elliptic partial differential equations (PDEs) by…

Numerical Analysis · Mathematics 2020-07-15 Rasmus Tamstorf , Joseph Benzaken , Stephen F. McCormick

This paper establishes the first theoretical framework for analyzing the rounding-error effects on multigrid methods using mixed-precision iterative-refinement solvers. While motivated by the sparse symmetric positive definite (SPD) matrix…

Numerical Analysis · Mathematics 2020-07-15 Stephen F. McCormick , Joseph Benzaken , Rasmus Tamstorf

We investigate the application of windowed Fourier frames (WFFs) to the numerical solution of partial differential equations, focussing on elliptic equations. The action of a partial differential operator (PDO) on a windowed plane wave is…

Analysis of PDEs · Mathematics 2010-09-13 Samir K. Bhowmik , Christiaan C. Stolk

Periodic micromagnetic finite element method (PM-FEM) is introduced to solve periodic unit cell problems using the Landau-Lifshitz-Gilbert equation. PM-FEM is applicable to general problems with 1D, 2D, and 3D periodicities. PM-FEM is based…

Numerical Analysis · Mathematics 2024-09-24 Fangzhou Ai , Jiawei Duan , Vitaliy Lomakin

The multigrid algorithm is an efficient numerical method for solving a variety of elliptic partial differential equations (PDEs). The method damps errors at progressively finer grid scales, resulting in faster convergence compared to…

Numerical Analysis · Mathematics 2021-05-06 Francisco Holguin , GS Sidharth , Gavin Portwood

In this paper we study convergence estimates for a multigrid algorithm with smoothers of successive subspace correction (SSC) type, applied to symmetric elliptic PDEs. First, we revisit a general convergence analysis on a class of multigrid…

Numerical Analysis · Mathematics 2018-05-09 Eugenio Aulisa , Giorgio Bornia , Sara Calandrini , Giacomo Capodaglio

High-order numerical methods for solving elliptic equations over arbitrary domains typically require specialized machinery, such as high-quality conforming grids for finite elements method, and quadrature rules for boundary integral…

Numerical Analysis · Mathematics 2021-06-02 Saad Qadeer , Boyce E. Griffith

Due to the lack of corresponding analysis on appropriate mapping operator between two grids, high-order two-grid difference algorithms are rarely studied. In this paper, we firstly discuss the boundedness of a local bi-cubic Lagrange…

Numerical Analysis · Mathematics 2024-08-14 Bingyin Zhang , Hongfei Fu

We examine what is an efficient and scalable nonlinear solver, with low work and memory complexity, for many classes of discretized partial differential equations (PDEs) - matrix-free Full multigrid (FMG) with a Full Approximation Storage…

Numerical Analysis · Mathematics 2023-06-07 Mark F. Adams

For describing the probability distribution of the positions and times of particles performing anomalous motion, fractional PDEs are derived from the continuous time random walk models with waiting time distribution having divergent first…

Numerical Analysis · Mathematics 2016-10-11 Zhijiang Zhang , Weihua Deng

This paper proposes some efficient and accurate adaptive two-grid (ATG) finite element algorithms for linear and nonlinear partial differential equations (PDEs). The main idea of these algorithms is to utilize the solutions on the $k$-th…

Numerical Analysis · Mathematics 2020-09-22 Yukun Li , Yi Zhang

We investigate the lifting property of modulation spaces and construct explicit isomorpisms between them. For each weight function $\omega$ and suitable window function $\fy $, the Toeplitz operator (or localization operator) $\tp_\fy…

Functional Analysis · Mathematics 2009-10-23 Karl-Heinz Gröchenig , Joachim Toft

Given a space of homogeneous type we give sufficient conditions on a variable exponent {p(.)} so that the fractional maximal operator {M_{\eta}} maps {L^{p(.)}(X)} to {L^{q(.)}(X)}, where {1/p(.) - 1/q(.) = {\eta}}. In the endpoint case we…

Classical Analysis and ODEs · Mathematics 2015-12-01 David Cruz-Uribe , Parantap Shukla

Federated Learning (FL) has evolved as a promising technique to handle distributed machine learning across edge devices. A single neural network (NN) that optimises a global objective is generally learned in most work in FL, which could be…

Information Theory · Computer Science 2022-03-10 Sawan Singh Mahara , Shruti M. , B. N. Bharath , Akash Murthy

We present a unified framework for analyzing local SGD methods in the convex and strongly convex regimes for distributed/federated training of supervised machine learning models. We recover several known methods as a special case of our…

Machine Learning · Computer Science 2020-11-06 Eduard Gorbunov , Filip Hanzely , Peter Richtárik