Rate optimal adaptive FEM with inexact solver for nonlinear operators
For researchers in numerical analysis, this work extends optimality guarantees of adaptive FEM to include iterative solver costs, a previously missing piece.
The paper proves convergence with optimal algebraic rates for adaptive FEM applied to nonlinear equations with strongly monotone operators, including the cost of inexact Picard iteration. Numerical experiments confirm optimal computational cost.
We prove convergence with optimal algebraic rates for an adaptive finite element method for nonlinear equations with strongly monotone operator. Unlike prior works, our analysis also includes the iterative and inexact solution of the arising nonlinear systems by means of the Picard iteration. Using nested iteration, we prove, in particular, that the number of of Picard iterations is uniformly bounded in generic cases, and the overall computational cost is (almost) optimal. Numerical experiments confirm the theoretical results.