A robust and efficient line search for self-consistent field iterations

Michael F. Herbst (1) , Antoine Levitt (2, 3)

1 RWTH - Rheinisch-Westfälische Technische Hochschule Aachen University
2 MATHERIALS - MATHematics for MatERIALS
3 CERMICS - Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique

We propose a novel adaptive damping algorithm for the self-consistent field (SCF) iterations of Kohn-Sham density-functional theory, using a backtracking line search to automatically adjust the damping in each SCF step. This line search is based on a theoretically sound, accurate and inexpensive model for the energy as a function of the damping parameter. In contrast to usual damped SCF schemes, the resulting algorithm is fully automatic and does not require the user to select a damping. We successfully apply it to a wide range of challenging systems, including elongated supercells, surfaces and transition-metal alloys.

Domaines: Equations aux dérivées partielles [math.AP]

Michael F. Herbst, Antoine Levitt. A robust and efficient line search for self-consistent field iterations. Journal of Computational Physics, 2022, 459, ⟨10.1016/j.jcp.2022.111127⟩. ⟨hal-03359244⟩