Linear Asymptotic Convergence of Anderson Acceleration: Fixed-Point Analysis

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 , and analyze the continuity and differentiability properties of and . We find that the vector of acceleration coefficients is not continuous at the fixed point . However, we show that, despite the discontinuity of , the iteration function is Lipschitz continuous and directionally differentiable at for AA(1), and we generalize this to AA() with for most cases. Furthermore, we find that is not differentiable at . We then discuss how these theoretical findings relate to the observed convergence behaviour of AA(). The discontinuity of at allows to oscillate as converges to , and the non-differentiability of allows AA() sequences to converge with root-linear convergence factors that strongly depend on the initial condition. Additional numerical results illustrate our findings.
View on arXiv