Adaptive Spectral Galerkin Methods with Dynamic Marking
Code:
54/2015
Title:
Adaptive Spectral Galerkin Methods with Dynamic Marking
Date:
Monday 2nd November 2015
Author(s):
Canuto, C.; Nochetto, R. H.; Stevenson, R.; Verani, M.
Abstract:
The convergence and optimality theory of adaptive Galerkin methods is
almost exclusively based on the Dorfler marking. This entails a fixed
parameter and leads to a contraction constant bounded below away from
zero. For spectral Galerkin methods this is a severe limitation which affects performance. We present a dynamic marking strategy that allows for a super-linear relation between consecutive discretization errors, and show exponential convergence with linear computational complexity whenever the solution belongs to a Gevrey approximation class.