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

Abstract : 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.
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https://hal.inria.fr/hal-03359244
Contributor : Antoine Levitt Connect in order to contact the contributor
Submitted on : Thursday, September 30, 2021 - 8:52:26 AM
Last modification on : Wednesday, November 23, 2022 - 10:16:08 AM

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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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