Fast periodic Gaussian density fitting by range separation
Abstract
We present an efficient implementation of periodic Gaussian density fitting (GDF) using the Coulomb metric. The three-center integrals are divided into two parts by range-separating the Coulomb kernel, with the short-range part evaluated in real space and the long-range part in reciprocal space. With a few algorithmic optimizations, we show that this new method -- which we call range-separated GDF (RSGDF) -- scales sublinearly to linearly with the number of -points for small to medium-sized -point meshes that are commonly used in periodic calculations with electron correlation. Numerical results on a few three-dimensional solids show about -fold speedups over the previously developed GDF with little precision loss. The error introduced by RSGDF is about in the converged Hartree-Fock energy with default auxiliary basis sets and can be systematically reduced by increasing the size of the auxiliary basis with little extra work. [The article has been accepted by The Journal of Chemical Physics.]
Keywords
Cite
@article{arxiv.2102.02989,
title = {Fast periodic Gaussian density fitting by range separation},
author = {Hong-Zhou Ye and Timothy C. Berkelbach},
journal= {arXiv preprint arXiv:2102.02989},
year = {2021}
}
Comments
7 pages, 3 figures