Linear Asymptotic Convergence of Anderson Acceleration: Fixed-Point Analysis
Hans De Sterck, Yunhui He

TL;DR
This paper analyzes the asymptotic convergence of Anderson acceleration (AA) for fixed-point iterations, revealing that AA sequences converge root-linearly with oscillating acceleration coefficients and that the iteration map is Lipschitz continuous but not differentiable at the fixed point.
Contribution
It provides a theoretical analysis of AA's convergence properties, including the discontinuity of acceleration coefficients and the non-differentiability of the iteration map at the fixed point.
Findings
AA(m) sequences converge root-linearly with initial-condition-dependent factors.
AA(m) acceleration coefficients oscillate and do not converge.
The iteration map is Lipschitz continuous but not differentiable at the fixed point.
Abstract
We study the asymptotic convergence of AA(), i.e., Anderson acceleration with window size for accelerating fixed-point methods , . Convergence acceleration by AA() has been widely observed but is not well understood. We consider the case where the fixed-point iteration function is differentiable and the convergence of the fixed-point method itself is root-linear. We identify numerically several conspicuous properties of AA() convergence: First, AA() sequences converge root-linearly but the root-linear convergence factor depends strongly on the initial condition. Second, the AA() acceleration coefficients do not converge but oscillate as converges to . To shed light on these observations, we write the AA() iteration as an augmented fixed-point iteration , $z_k \in…
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Taxonomy
TopicsIterative Methods for Nonlinear Equations · Matrix Theory and Algorithms · Numerical methods for differential equations
