Anderson Acceleration Based on the ${\mathcal{H}}^{-s}$ Sobolev Norm for Contractive and Noncontractive Fixed-Point Operators

Abstract

Anderson acceleration (AA) is a technique for accelerating the convergence of fixed-point iterations. In this paper, we apply AA to a sequence of functions and modify the norm in its internal optimization problem to the ${\mathcal{H}}^{-s}$ norm, for some positive integer $s$, to bias it towards low-frequency spectral content in the residual. We analyze the convergence of AA by quantifying its improvement over Picard iteration. We find that AA based on the ${\mathcal{H}}^{-2}$ norm is well-suited to solve fixed-point operators derived from second-order elliptic differential operators, including the Helmholtz equation.

22 pages, 8 figures, under revision

References in corpus (4)

• Anderson acceleration for contractive and noncontractive operators
• Anderson Accelerated Douglas-Rachford Splitting
• High-order numerical method for the nonlinear Helmholtz equation with material discontinuities in one space dimension
• Anderson Acceleration of Proximal Gradient Methods