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Analysis of a New Harmonically Enriched Multiscale Coarse Space for Domain Decomposition Methods

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arxiv 1512.05285 v1 pith:JCNOGAYX submitted 2015-12-16 math.NA cs.NA

classification math.NAcs.NA
keywords coarsespaceenrichedharmonicallymultiscaleanalysiscalldecomposition
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We propose a new, harmonically enriched multiscale coarse space (HEM) for domain decomposition methods. For a coercive high contrast model problem, we show how to enrich the coarse space so that the method is robust against any variations and discontinuities in the problem parameters both inside subdomains and across and along subdomain boundaries. We prove our results for an enrichment strategy based on solving simple, lower dimensional eigenvalue problems on the interfaces between subdomains, and we call the resulting coarse space the spectral harmonically enriched multiscale coarse space (SHEM). We then also give a variant that performs equally well in practice, and does not require the solve of eigenvalue problems, which we call non-spectral harmonically enriched multiscale coarse space (NSHEM). Our enrichment process naturally reaches the optimal coarse space represented by the full discrete harmonic space, which enables us to turn the method into a direct solver (OHEM). We also extensively test our new coarse spaces numerically, and the results confirm our analysis

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Optimal Spectral Approximation in the Overlaps for Generalized Finite Element Methods

    math.NA 2025-07 conditional novelty 6.0 of 10

    The ring-localized MS-GFEM variant achieves nearly exponential a priori error decay in the number of local basis functions, with cheaper eigenvalue computations and a preconditioner application.

  2. Spectral substructured two-level domain decomposition methods

    math.NA 2019-08 conditional novelty 6.0 of 10

    The paper introduces interface-only two-level domain decomposition methods (S2S), proves convergence formulas, and shows spectral coarse spaces are not always asymptotically optimal.

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