Unconditional full linear convergence and quasi-optimal complexity of smoothed adaptive finite element methods

Fuente: arXiv
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Autori principali: Bringmann, Philipp, Lietz, Christoph, Praetorius, Dirk
Natura: Preprint
Pubblicazione: 2026
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author Bringmann, Philipp
Lietz, Christoph
Praetorius, Dirk
author_facet Bringmann, Philipp
Lietz, Christoph
Praetorius, Dirk
contents We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai: SIAM J. Sci. Comput. 43, 2021]. S-AFEM modifies the classical adaptive finite element method (AFEM) by performing accurate discrete solves only on periodically determined mesh levels, while the intermediate levels employ a fixed number of cheap smoothing iterations. Numerical experiments in that work showed that this strategy generates adapted meshes comparable to those of AFEM at substantially lower computational cost. In this paper, we prove unconditional full R-linear convergence of a suitable quasi-error quantity and, for sufficiently small adaptivity parameters, optimal convergence rates with respect to the overall computational cost. The analysis requires only a mild uniform stability assumption on the employed smoother, satisfied by standard methods such as Richardson, Gauss-Seidel, conjugate gradient, and multigrid schemes. Our results apply to general second-order linear elliptic PDEs and show that S-AFEM retains all desired abstract convergence guarantees of AFEM while reducing the cumulative computational time. Numerical experiments validate the theory, analyze runtime performance, and underline the potential of S-AFEM for speed-up in AFEM computations.
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id arxiv_https___arxiv_org_abs_2601_20677
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Unconditional full linear convergence and quasi-optimal complexity of smoothed adaptive finite element methods
Bringmann, Philipp
Lietz, Christoph
Praetorius, Dirk
Numerical Analysis
65N50 (Primary) 65N30, 65N15, 65Y20, 41A25, 65F10 (Secondary)
We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai: SIAM J. Sci. Comput. 43, 2021]. S-AFEM modifies the classical adaptive finite element method (AFEM) by performing accurate discrete solves only on periodically determined mesh levels, while the intermediate levels employ a fixed number of cheap smoothing iterations. Numerical experiments in that work showed that this strategy generates adapted meshes comparable to those of AFEM at substantially lower computational cost. In this paper, we prove unconditional full R-linear convergence of a suitable quasi-error quantity and, for sufficiently small adaptivity parameters, optimal convergence rates with respect to the overall computational cost. The analysis requires only a mild uniform stability assumption on the employed smoother, satisfied by standard methods such as Richardson, Gauss-Seidel, conjugate gradient, and multigrid schemes. Our results apply to general second-order linear elliptic PDEs and show that S-AFEM retains all desired abstract convergence guarantees of AFEM while reducing the cumulative computational time. Numerical experiments validate the theory, analyze runtime performance, and underline the potential of S-AFEM for speed-up in AFEM computations.
title Unconditional full linear convergence and quasi-optimal complexity of smoothed adaptive finite element methods
topic Numerical Analysis
65N50 (Primary) 65N30, 65N15, 65Y20, 41A25, 65F10 (Secondary)
url https://arxiv.org/abs/2601.20677