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In this paper, we will introduce a high order numerical method to solve the scattering problems with non-periodic incident fields and (locally perturbed) periodic surfaces. For the problems we are considering, the classical methods to treat…

Numerical Analysis · Mathematics 2018-07-26 Ruming Zhang

The dual formulation for linear elasticity, in contrast to the primal formulation, is not affected by locking, as it is based on the stresses as main unknowns. Thus it is quite attractive for nearly incompressible and incompressible…

Numerical Analysis · Mathematics 2021-06-28 Gabriele Rovi , Rolf Krause

The convergence of multigrid methods degrades significantly if a small number of low quality cells are present in a finite element mesh, and this can be a barrier to the efficient and robust application of multigrid on complicated geometric…

Computational Engineering, Finance, and Science · Computer Science 2024-02-21 Yuxuan Chen , Garth N. Wells

In this paper we analyze the Schwarz alternating method for unconstrained elliptic optimal control problems. We discuss the convergence properties of the method in the continuous case first and then apply the arguments to the finite…

Numerical Analysis · Mathematics 2022-01-05 Wei Gong , Felix Kwok , Zhiyu Tan

In this paper, we partially answer open questions about the convergence of overlapping Schwarz methods. We prove that overlapping Schwarz methods with Dirichlet transmission conditions for semilinear elliptic and parabolic equations always…

Numerical Analysis · Mathematics 2011-04-22 Minh-Binh Tran

Image inpainting is a fundamental task in computer vision, aiming to restore missing or corrupted regions in images realistically. While recent deep learning approaches have significantly advanced the state-of-the-art, challenges remain in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Jacob Fein-Ashley , Benjamin Fein-Ashley

We present a robust and efficient multigrid method for single-patch isogeometric discretizations using tensor product B-splines of maximum smoothness. Our method is based on a stable splitting of the spline space into a large subspace of…

Numerical Analysis · Mathematics 2017-08-22 Clemens Hofreither , Stefan Takacs

We present a two-level overlapping Schwarz preconditioner for three-dimensional problems discretized with the Virtual Element Method. Our approach handles general polyhedral meshes and irregular subdomains, extending the applicability of…

Numerical Analysis · Mathematics 2025-12-09 Ana Aguilar-Pineda , Luis F. Amey , Adrian Angulo-Paniagua , Juan G. Calvo

By the use of Green's second integral identity we determine the field scattered from a two-dimensional randomly rough isotropic or anisotropic Dirichlet or Neumann surface when it is illuminated by a scalar Gaussian beam. The integral…

Schwarz methods are attractive parallel solution techniques for solving large-scale linear systems obtained from discretizations of partial differential equations (PDEs). Due to the iterative nature of Schwarz methods, convergence rates are…

Numerical Analysis · Mathematics 2017-05-12 Martin J. Gander , Soheil Hajian

We deal with the numerical solution of linear elliptic problems with varying diffusion coefficient by the $hp$-discontinuous Galerkin method. We develop a two-level hybrid Schwarz preconditioner for the arising linear algebraic systems. The…

Numerical Analysis · Mathematics 2025-09-19 Vit Dolejsi , Tomas Hammerbauer

We present here the classical Schwarz method with a time domain decomposition applied to unconstrained parabolic optimal control problems. Unlike Dirichlet-Neumann and Neumann-Neumann algorithms, we find different properties based on the…

Numerical Analysis · Mathematics 2024-08-23 Martin Jakob Gander , Liu-Di Lu

This paper describes an approach to global smoothing problems for non-dispersive equations based on ideas of comparison principle and canonical transformation established in authors' previous paper, where dispersive equations were treated.…

Analysis of PDEs · Mathematics 2015-08-04 Michael Ruzhansky , Mitsuru Sugimoto

The additive Schwarz method is usually presented as a preconditioner for a PDE linearization based on overlapping subsets of nodes from a global discretization. It has previously been shown how to apply Schwarz preconditioning to a…

Numerical Analysis · Mathematics 2019-02-05 Kevin W. Aiton , Tobin A. Driscoll

The multiple scattering of scalar waves in diffusive media is investigated by means of the radiative transfer equation. This approach amounts to a resummation of the ladder diagrams of the Born series; it does not rely on the diffusion…

Condensed Matter · Physics 2007-05-23 E. Amic , J. M. Luck , Th. M. Nieuwenhuizen

Along with recent diffusion models, randomized smoothing has become one of a few tangible approaches that offers adversarial robustness to models at scale, e.g., those of large pre-trained models. Specifically, one can perform randomized…

Machine Learning · Computer Science 2023-10-30 Jongheon Jeong , Jinwoo Shin

A symmetric and a nonsymmetric variant of the additive Schwarz preconditioner are proposed for the solution of a nonsymmetric system of algebraic equations arising from a general finite volume element discretization of symmetric elliptic…

Numerical Analysis · Mathematics 2018-06-14 Leszek Marcinkowski , Talal Rahman , Atle Loneland , Jan Valdman

Nonlinear domain decomposition methods became popular in recent years since they can improve the nonlinear convergence behavior of Newton's method significantly for many complex problems. In this article, a nonlinear two-level Schwarz…

Numerical Analysis · Mathematics 2024-09-06 Axel Klawonn , Martin Lanser

This paper proposes a two-level restricted additive Schwarz (RAS) method for multiscale PDEs, built on top of a multiscale spectral generalized finite element method (MS-GFEM). The method uses coarse spaces constructed from optimal local…

Numerical Analysis · Mathematics 2024-08-30 Arne Strehlow , Chupeng Ma , Robert Scheichl

Adaptive gradient methods like AdaGrad are widely used in optimizing neural networks. Yet, existing convergence guarantees for adaptive gradient methods require either convexity or smoothness, and, in the smooth setting, only guarantee…

Machine Learning · Computer Science 2019-10-22 Xiaoxia Wu , Simon S. Du , Rachel Ward
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