Domain decomposition methods and preconditioning strategies using generalized locally Toepltiz tools: proposals, analysis, and numerical validation
Abdessadek Rifqui, Ahmed Ratnani, Stefano Serra-Capizzano

TL;DR
This paper uses generalized locally Toeplitz (GLT) sequences to analyze the spectral properties and convergence of Schwarz domain decomposition methods, providing explicit spectral expressions and insights into their efficiency and scalability.
Contribution
It introduces a GLT-based spectral analysis framework for Schwarz methods, offering explicit spectral characterizations and a unified understanding of their convergence behavior.
Findings
GLT symbols describe spectral evolution with mesh refinement
Restricted Schwarz variants improve parallel efficiency
Numerical experiments confirm theoretical predictions
Abstract
In the current work we present a spectral analysis of the additive and multiplicative Schwarz methods within the framework of domain decomposition techniques, by investigating the spectral properties of these classical Schwarz preconditioning matrix-sequences, with emphasis on their convergence behavior and on the effect of transmission operators. In particular, after a general presentation of various options, we focus on restricted variants of the Schwarz methods aimed at improving parallel efficiency, while preserving their convergence features. In order to rigorously describe and analyze the convergence behavior, we employ the theory of generalized locally Toeplitz (GLT) sequences, which provides a robust framework for studying the asymptotic spectral distribution of the discretized operators arising from Schwarz iterations. By associating each operator sequence with the appropriate…
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Taxonomy
TopicsMatrix Theory and Algorithms · Advanced Numerical Methods in Computational Mathematics · Advanced Mathematical Modeling in Engineering
