A posteriori error estimates based on multilevel decompositions with large problems on the coarsest level

Fuente: arXiv
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Autores principales: Vacek, Petr, Papež, Jan, Strakoš, Zdeněk
Formato: Preprint
Publicado: 2024
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author Vacek, Petr
Papež, Jan
Strakoš, Zdeněk
author_facet Vacek, Petr
Papež, Jan
Strakoš, Zdeněk
contents Multilevel methods represent a powerful approach in numerical solution of partial differential equations. The multilevel structure can also be used to construct estimates for total and algebraic errors of computed approximations. This paper deals with residual-based error estimates that are based on properties of quasi-interpolation operators, stable-splittings, or frames. We focus on the settings where the system matrix on the coarsest level is still large and the associated terms in the estimates can only be approximated. We show that the way in which the error term associated with the coarsest level is approximated is substantial. It can significantly affect both the efficiency (accuracy) of the overall error estimates and their robustness with respect to the size of the coarsest problem. The newly proposed approximation of the coarsest-level term is based on using the conjugate gradient method with an appropriate stopping criterion. We prove that the resulting estimates are efficient and robust with respect to the size of the coarsest-level problem. Numerical experiments illustrate the theoretical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06532
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A posteriori error estimates based on multilevel decompositions with large problems on the coarsest level
Vacek, Petr
Papež, Jan
Strakoš, Zdeněk
Numerical Analysis
65N15, 65N55, 65N22, 65N30, 65F10
Multilevel methods represent a powerful approach in numerical solution of partial differential equations. The multilevel structure can also be used to construct estimates for total and algebraic errors of computed approximations. This paper deals with residual-based error estimates that are based on properties of quasi-interpolation operators, stable-splittings, or frames. We focus on the settings where the system matrix on the coarsest level is still large and the associated terms in the estimates can only be approximated. We show that the way in which the error term associated with the coarsest level is approximated is substantial. It can significantly affect both the efficiency (accuracy) of the overall error estimates and their robustness with respect to the size of the coarsest problem. The newly proposed approximation of the coarsest-level term is based on using the conjugate gradient method with an appropriate stopping criterion. We prove that the resulting estimates are efficient and robust with respect to the size of the coarsest-level problem. Numerical experiments illustrate the theoretical findings.
title A posteriori error estimates based on multilevel decompositions with large problems on the coarsest level
topic Numerical Analysis
65N15, 65N55, 65N22, 65N30, 65F10
url https://arxiv.org/abs/2405.06532