A robust and efficient line search for self-consistent field iterations - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Journal of Computational Physics Année : 2022

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

Résumé

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.

Dates et versions

hal-03359244 , version 1 (30-09-2021)

Identifiants

Citer

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⟩
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