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

TL;DR

This paper develops p-robust multigrid and domain decomposition solvers for mixed finite element discretizations of elliptic PDEs, using a posteriori error estimators to steer the methods and prove their efficiency and convergence.

Contribution

It introduces novel p-robust multilevel stable decompositions for mixed finite element spaces in 2D and 3D, extending previous work and enabling efficient solvers with optimal step-sizes.

Findings

Multigrid solver contracts algebraic error p-robustly.

A posteriori estimators are p-robustly efficient.

Numerical results confirm theoretical convergence and efficiency.

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 $p \ge 0$ 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 [Mira\c{c}i, Pape\v{z}, 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.