Meta-generalized gradient approximation made in the Hartree gauge
Yan Oueis, Akilan Ramasamy, James W. Furness, Jamin Kidd, Timo Lebeda, Jianwei Sun

TL;DR
This paper introduces a new meta-GGA exchange functional in density functional theory, constructed within the Hartree gauge using hydrogen atom data, enhancing the foundation for more accurate nonlocal functionals.
Contribution
It develops a meta-GGA exchange functional explicitly formulated in the Hartree gauge, utilizing hydrogen atom exchange energy density for improved gauge alignment in DFT.
Findings
Provides a gauge-aligned meta-GGA exchange functional
Expands reference datasets for machine learning in DFT
Establishes a foundation for more accurate nonlocal density functionals
Abstract
In density functional theory (DFT), exact constraints, fundamental mathematical properties of the exchange-correlation (XC) energy and its underlying XC hole, along with paradigm systems such as the uniform electron gas and the hydrogen atom have been instrumental in developing exchange- correlation (XC) density functional approximations (DFAs). However, since the spatial XC energy density is not uniquely defined, its exact constraints can only be formulated within a chosen gauge and are therefore seldom utilized in DFA construction. Here, we propose a meta-generalized gradient approximation for the exchange energy, explicitly constructed within the Hartree gauge, using the hydrogen atom's exchange energy density for gauge alignment in core and asymptotic regions. By formulating DFAs at the XC energy density level, this approach expands reference datasets for machine learning and…
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Taxonomy
TopicsMachine Learning in Materials Science · Cold Atom Physics and Bose-Einstein Condensates · Quantum many-body systems
