Self-Consistent Density-Functional Embedding: A Novel Approach for Density-Functional Approximations
Author(s) -
Uliana Mordovina,
Teresa E. Reinhard,
Ίρις Θεοφίλου,
Heiko Appel,
Ángel Rubio
Publication year - 2019
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.9b00063
Subject(s) - embedding , density functional theory , orbital free density functional theory , benchmark (surveying) , projection (relational algebra) , statistical physics , set (abstract data type) , hybrid functional , time dependent density functional theory , functional theory , physics , computer science , algorithm , quantum mechanics , artificial intelligence , geodesy , geography , programming language
In the present work, we introduce a self-consistent density-functional embedding technique, which leaves the realm of standard energy-functional approaches in density functional theory and targets directly the density-to-potential mapping that lies at its heart. Inspired by the density matrix embedding theory, we project the full system onto a set of small interacting fragments that can be solved accurately. Based on the rigorous relation of density and potential in density functional theory, we then invert the fragment densities to local potentials. Combining these results in a continuous manner provides an update for the Kohn-Sham potential of the full system, which is then used to update the projection. We benchmark our approach for molecular bond stretching in one and two dimensions and show that, in these cases, the scheme converges to accurate approximations for densities and Kohn-Sham potentials. We demonstrate that the known steps and peaks of the exact exchange-correlation potential are reproduced by our method with remarkable accuracy.
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