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In the literature, there exist several studies on symbol-based multigrid methods for the solution of linear systems having structured coefficient matrices. In particular, the convergence analysis for such methods has been obtained in an…

Numerical Analysis · Mathematics 2021-11-15 Matthias Bolten , Marco Donatelli , Paola Ferrari , Isabella Furci

We present novel improvements in the context of symbol-based multigrid procedures for solving large block structured linear systems. We study the application of an aggregation-based grid transfer operator that transforms the symbol of a…

Numerical Analysis · Mathematics 2024-03-05 Matthias Bolten , Marco Donatelli , Paola Ferrari , Isabella Furci

The main focus of this paper is the study of efficient multigrid methods for large linear systems with a particular saddle-point structure. Indeed, when the system matrix is symmetric, but indefinite, the variational convergence theory that…

Numerical Analysis · Mathematics 2023-08-30 Marco Donatelli , Matthias Bolten , Paola Ferrari , Isabella Furci

Multigrid is one of the most efficient methods for solving large-scale linear systems that arise from discretized partial differential equations. As a foundation for multigrid analysis, two-grid theory plays an important role in motivating…

Numerical Analysis · Mathematics 2021-08-17 Xuefeng Xu , Chen-Song Zhang

Starting from the spectral analysis of g-circulant matrices, we consider a new multigrid method for circulant and Toeplitz matrices with given generating function. We assume that the size n of the coefficient matrix is divisible by g \geq 2…

Numerical Analysis · Mathematics 2010-10-28 Marco Donatelli , Stefano Serra-Capizzano , Debora Sesana

The nonlocal problems have been used to model very different applied scientific phenomena, which involve the fractional Laplacian when one looks at the L\'{e}vy processes and stochastic interfaces. This paper deals with the nonlocal…

Numerical Analysis · Mathematics 2021-08-17 Minghua Chen , Sven-Erik Ekström , Stefano Serra-Capizzano

Multigrid is a powerful solver for large-scale linear systems arising from discretized partial differential equations. The convergence theory of multigrid methods for symmetric positive definite problems has been well developed over the…

Numerical Analysis · Mathematics 2022-04-19 Xuefeng Xu

Saddle point problems arise in a variety of applications, e.g., when solving the Stokes equations. They can be formulated such that the system matrix is symmetric, but indefinite, so the variational convergence theory that is usually used…

Numerical Analysis · Mathematics 2022-03-14 Matthias Bolten , Marco Donatelli , Paola Ferrari , Isabella Furci

Given a multigrid procedure for linear systems with coefficient matrices $A_n$, we discuss the optimality of a related multigrid procedure with the same smoother and the same projector, when applied to properly related algebraic problems…

Numerical Analysis · Mathematics 2012-11-03 Stefano Serra-Capizzano , Cristina Tablino Possio

Two-grid methods with exact solution of the Galerkin coarse-grid system have been well studied by the multigrid community: an elegant identity has been established to characterize the convergence factor of exact two-grid methods. In…

Numerical Analysis · Mathematics 2022-01-11 Xuefeng Xu , Chen-Song Zhang

The Local Fourier analysis (LFA) is a classic tool to prove convergence theorems for multigrid methods (MGMs). In particular, we are interested in optimality that is a convergence speed independent of the size of the involved matrices. For…

Numerical Analysis · Mathematics 2008-07-17 Marco Donatelli

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

Two of the most popular parallel-in-time methods are Parareal and multigrid-reduction-in-time (MGRIT). Recently, a general convergence theory was developed in Southworth (2019) for linear two-level MGRIT/Parareal that provides necessary and…

Numerical Analysis · Mathematics 2020-10-23 Ben S. Southworth , Wayne Mitchell , Andreas Hessenthaler , Federico Danieli

The convergence rate of a multigrid method depends on the properties of the smoother and the so-called grid transfer operator. In this paper we define and analyze new grid transfer operators with a generic cutting size which are applicable…

Numerical Analysis · Mathematics 2016-08-12 Maria Charina , Marco Donatelli , Lucia Romani , Valentina Turati

In this article we consider two-grid finite element methods for solving semilinear interface problems in d space dimensions, for d=2 or d=3. We first describe in some detail the target problem class with discontinuous diffusion…

Numerical Analysis · Mathematics 2012-03-05 Michael Holst , Ryan Szypowski , Yunrong Zhu

Algebraic multigrid (AMG) is one of the most efficient iterative methods for solving large sparse system of equations. However, how to build/check restriction and prolongation operators in practical of AMG methods for nonsymmetric {\em…

Numerical Analysis · Mathematics 2022-02-24 Minghua Chen , Rongjun Cao , Stefano Serra-Capizzano

We derive sharp approximation error bounds for inverse block Toeplitz matrices associated with multivariate long-memory stationary processes. The error bounds are evaluated for both column and row sums. These results are used to prove the…

Statistics Theory · Mathematics 2024-06-11 Akihiko Inoue , Junho Yang

Two-grid theory plays a fundamental role in the design and analysis of multigrid methods. This paper is devoted to a new convergence analysis of two-grid methods for singular and symmetric positive semidefinite systems. Specifically, we…

Numerical Analysis · Mathematics 2026-01-06 Xuefeng Xu

In this paper we derive new uniform convergence estimates for the V-cycle MGM applied to symmetric positive definite Toeplitz block tridiagonal matrices, by also discussing few connections with previous results. More concretely, the…

Numerical Analysis · Mathematics 2018-03-06 Minghua Chen , Weihua Deng , Stefano Serra-Capizzano

The predicted reduced resiliency of next-generation high performance computers means that it will become necessary to take into account the effects of randomly occurring faults on numerical methods. Further, in the event of a hard fault…

Numerical Analysis · Mathematics 2017-09-07 Mark Ainsworth , Christian Glusa
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