Reformulation of the Anderson method using singular value decomposition for stable convergence in self-consistent calculations

抄録

The Anderson method provides a significant acceleration of convergence in solving nonlinear simultaneous equations by trying to minimize the residual norm in a least-square sense at each iteration step. In the present study I use singular value decomposition to reformulate the Anderson method. The proposed version contains only a single parameter which should be determined in a trial-and-error way, whereas the original one contains two. This reduction leads to stable convergence in real-world self-consistent electronic structure calculations.