Discrete $p$-robust $\mathbf{H}(\mathrm{div})$-liftings and a posteriori estimates for elliptic problems with $H^{-1}$ source terms

TL;DR

This paper develops robust discrete liftings into $ ext{H}( ext{div})$ spaces for polynomial data on refined meshes, enabling improved a posteriori error estimates for elliptic and parabolic problems with $H^{-1}$ sources.

Contribution

It introduces polynomial-degree robust discrete liftings into $ ext{H}( ext{div})$ spaces, facilitating error analysis without transition conditions or hanging nodes.

Findings

Guaranteed upper bounds on errors for elliptic problems.

Polynomial-degree robustness of the error estimators.

Applicability to meshes with hanging nodes and adaptive refinement.

Abstract

We establish the existence of liftings into discrete subspaces of $\mathbf{H}(\mathrm{div})$ of piecewise polynomial data on locally refined simplicial partitions of polygonal/polyhedral domains. Our liftings are robust with respect to the polynomial degree. This result has important applications in the a posteriori error analysis of parabolic problems, where it permits the removal of so-called transition conditions that link two consecutive meshes. It can also be used in a the posteriori error analysis of elliptic problems, where it allows the treatment of meshes with arbitrary numbers of hanging nodes between elements. We present a constructive proof based on the a posteriori error analysis of an auxiliary elliptic problem with $H^{-1}$ source terms, thereby yielding results of independent interest. In particular, for such problems, we obtain guaranteed upper bounds on the error along with polynomial-degree robust local efficiency of the estimators.