Journal article
Shivesh Pathak, I. López, Alex J. Lee, William P. Bricker, R. L. Fernández, S. Lehtola, Joshua A. Rackers
Journal of Chemical Physics, 2022
Journal of Chemical Physics, 2022
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APA
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Pathak, S., López, I., Lee, A. J., Bricker, W. P., Fernández, R. L., Lehtola, S., & Rackers, J. A. (2022). Accurate Hellmann-Feynman forces from density functional calculations with augmented Gaussian basis sets. Journal of Chemical Physics.
Chicago/Turabian
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Pathak, Shivesh, I. López, Alex J. Lee, William P. Bricker, R. L. Fernández, S. Lehtola, and Joshua A. Rackers. “Accurate Hellmann-Feynman Forces from Density Functional Calculations with Augmented Gaussian Basis Sets.” Journal of Chemical Physics (2022).
MLA
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Pathak, Shivesh, et al. “Accurate Hellmann-Feynman Forces from Density Functional Calculations with Augmented Gaussian Basis Sets.” Journal of Chemical Physics, 2022.
BibTeX Click to copy
@article{shivesh2022a,
title = {Accurate Hellmann-Feynman forces from density functional calculations with augmented Gaussian basis sets.},
year = {2022},
journal = {Journal of Chemical Physics},
author = {Pathak, Shivesh and López, I. and Lee, Alex J. and Bricker, William P. and Fernández, R. L. and Lehtola, S. and Rackers, Joshua A.}
}
Abstract
The Hellmann-Feynman (HF) theorem provides a way to compute forces directly from the electron density, enabling efficient force calculations for large systems through machine learning (ML) models for the electron density. The main issue holding back the general acceptance of the HF approach for atom-centered basis sets is the well-known Pulay force which, if naively discarded, typically constitutes an error upward of 10 eV/Å in forces. In this work, we demonstrate that if a suitably augmented Gaussian basis set is used for density functional calculations, the Pulay force can be suppressed, and HF forces can be computed as accurately as analytical forces with state-of-the-art basis sets, allowing geometry optimization and molecular dynamics to be reliably performed with HF forces. Our results pave a clear path forward for the accurate and efficient simulation of large systems using ML densities and the HF theorem.
