Performance improvement of deorbitalized exchange-correlation functionals

Deorbitalization of a conventional meta-generalized-gradient exchange-correlation approximation replaces its dependence upon the Kohn-Sham (KS) kinetic energy density with a dependence on the density gradient and Laplacian. In principle, that simplification should provide improved computational performance relative to the original meta-generalized-gradient-approximation form because of the shift from an orbital-dependent generalized KS potential to a true KS local potential. Often that prospective gain is lost because of problematic roughness in the density caused by the density Laplacian and consequent roughness in the exchange-correlation potential from the resulting higher-order spatial derivatives of the density in it. We address the problem by constructing a deorbitalizer based on the ``${\mathrm{r}}^{2}\mathrm{SCAN}$ piecewise polynomial'' (RPP) deorbitalizer from A. D. Kaplan and J. P. Perdew [Phys. Rev. Mater. 6, 083803 (2022)] with comparative smoothness of the potential along with retention of constraint satisfaction as design goals. Applied to the ${\mathrm{r}}^{2}\mathrm{SCAN}$ exchange-correlation functional presented by J. W. Furness et al. [J. Phys. Chem. Lett. 11, 8208 (2020)], we find substantial timing improvements for solid-state calculations over both ${\mathrm{r}}^{2}\mathrm{SCAN}$ and its earlier deorbitalization for high-precision calculations of structural properties, while improving upon the accuracy of RPP deorbitalization for both solids and molecules.

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Publication Details

Journal
Physical Review Materials
Published
2026-04-03
DOI
https://doi.org/10.1103/rbf1-cp89
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Performance improvement of deorbitalized exchange-correlation functionals

Samuel B. Trickey, H. Francisco, Antonio C. Cancio
Physical Review Materials
Machine Learning in Materials Science
article

Performance improvement of deorbitalized exchange-correlation functionals

Samuel B. Trickey, H. Francisco, Antonio C. Cancio
article en

Abstract

Deorbitalization of a conventional meta-generalized-gradient exchange-correlation approximation replaces its dependence upon the Kohn-Sham (KS) kinetic energy density with a dependence on the density gradient and Laplacian. In principle, that simplification should provide improved computational performance relative to the original meta-generalized-gradient-approximation form because of the shift from an orbital-dependent generalized KS potential to a true KS local potential. Often that prospective gain is lost because of problematic roughness in the density caused by the density Laplacian and consequent roughness in the exchange-correlation potential from the resulting higher-order spatial derivatives of the density in it. We address the problem by constructing a deorbitalizer based on the ``${\mathrm{r}}^{2}\mathrm{SCAN}$ piecewise polynomial'' (RPP) deorbitalizer from A. D. Kaplan and J. P. Perdew [Phys. Rev. Mater. 6, 083803 (2022)] with comparative smoothness of the potential along with retention of constraint satisfaction as design goals. Applied to the ${\mathrm{r}}^{2}\mathrm{SCAN}$ exchange-correlation functional presented by J. W. Furness et al. [J. Phys. Chem. Lett. 11, 8208 (2020)], we find substantial timing improvements for solid-state calculations over both ${\mathrm{r}}^{2}\mathrm{SCAN}$ and its earlier deorbitalization for high-precision calculations of structural properties, while improving upon the accuracy of RPP deorbitalization for both solids and molecules.

Physical Review MaterialsVol. 10(4)
George Mason University (US), Ball State University (US), University of Florida (US)
National Science Foundation
Openalex Percentile: Top 100%
Machine Learning in Materials Science
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