A-posteriori-steered $p$-robust multigrid and domain decomposition methods with optimal step-sizes for mixed finite element discretizations of elliptic problems
A-posteriori-steered $p$-robust multigrid and domain decomposition methods with optimal step-sizes for mixed finite element discretizations of elliptic problems
Résumé
In this work, we develop algebraic solvers for linear systems arising from the discretization of second-order elliptic problems by saddle-point mixed finite element methods of arbitrary polynomial degree $p \ge 0$. We present a multigrid and a two-level domain decomposition
approach in two or three space dimensions, which are steered by their respective a~posteriori estimators of the algebraic error.
First, we extend the results of [A. Miraçi, J. Papež, and M. Vohralík, SIAM J. Sci. Comput. 43 (2021), S117–S145]
to the mixed finite element setting. Extending the multigrid procedure itself is rather natural. To obtain analogous theoretical results, however, a multilevel stable decomposition of the velocity space is needed. In two space dimensions, we can treat the velocity space as the curl of a stream-function space, for which the previous results apply. In three space dimensions, we design a novel stable decomposition by combining a one-level high-order local stable decomposition of [Chaumont-Frelet and Vohralík, SIAM J. Numer. Anal. 61 (2023), 1783--1818]
and a multilevel lowest-order stable decomposition of
[Hiptmair, Wu, and Zheng,
Numer. Math. Theory Methods Appl. 5 (2012), 297–332].
This allows us to prove that our multigrid solver contracts the algebraic
error at each iteration and, simultaneously, that the associated a~posteriori
estimator is efficient. A $p$-robust contraction is shown in
two space dimensions.
Next, we use this multilevel methodology to define a two-level domain
decomposition method where the subdomains consist of overlapping patches of
coarse-level elements sharing a common coarse-level vertex. We again establish a
($p$-robust) contraction of the solver and efficiency of the a~posteriori
estimator. Numerical results presented both for the multigrid approach and the
domain decomposition method confirm the theoretical findings.
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