Second‐ and higher‐order convergence in linear and nonlinear multiconfigurational Hartree–Fock theory

Abstract

AbstractWe discuss how the local convergence of Newton–Raphson and fixed Hessian MCSCF iterative models may be rationalized in terms of a total order of convergence in an error vector and a corresponding error term. We demonstrate that a sequence of N Newton–Raphson iterations has a total order of convergence of 2N and that a sequence of N fixed Hessian iterations has a total order of convergence of N + 1. We derive the error terms of a Newton–Raphson and a fixed Hessian sequence of iterations. We discuss the implementation of the fixed Hessian and the Newton–Raphson approaches both when linear and nonlinear transformations of the variables are carried out. Sample calculations show that insight into the structure of the local convergence of Newton–Raphson and fixed Hessian models can be based on an order of convergence and an error term analysis.