A-posteriori-steered p-robust multigrid and domain decomposition methods with optimal step-sizes for mixed finite element discretizations of elliptic problems

Abstract

In this work, we develop algebraic solvers for linear systems arising from the discretization of second-order elliptic partial differential equations by saddle-point mixed finite element methods of arbitrary polynomial degree p 0 on possibly highly graded simplicial meshes. We present a multigrid and a two-level domain decomposition approach in two and three space dimensions, steered by a posteriori estimators of the algebraic error. First, we extend [Miraci, Papez, and Vohral\'ik, 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 p-robust 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 Lagrange 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 [Falk and Winther, Found. Comput. Math. (2025), DOI 10.1007/s10208- 025-09700-2] 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 p-robustly and, simultaneously, that the associated a posteriori estimator is p-robustly efficient. 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 p-robust 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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