Statistical Analysis of Semiclassical Dispersion Corrections
Thomas Weymuth, Jonny Proppe, and Markus Reiher

TL;DR
This paper provides a comprehensive statistical evaluation of semiclassical dispersion correction parameters, revealing how choices in fitting procedures affect prediction reliability and emphasizing the importance of uncertainty quantification.
Contribution
It introduces a rigorous statistical framework for analyzing and estimating uncertainties in semiclassical dispersion correction parameters and predictions.
Findings
Choice of cost function has minimal impact on parameters.
Bootstrap analysis yields reliable uncertainty estimates.
Error accumulation increases with molecule size, affecting accuracy.
Abstract
Semiclassical dispersion corrections developed by Grimme and coworkers have become indispensable in applications of Kohn-Sham density functional theory. We present an in-depth assessment of the fit parameters present in semiclassical (D3-type) dispersion corrections by means of a statistically rigorous analysis. We find that the choice of the cost function generally has a small effect on the empirical parameters of D3-type dispersion corrections with respect to the reference set under consideration. Only in a few cases, the choice of cost function has a surprisingly large effect on the total dispersion energies. In particular, the weighting scheme in the cost function can significantly affect the reliability of predictions. In order to obtain unbiased (data-independent) uncertainty estimates for both the empirical fit parameters and the corresponding predictions, we carried out a…
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