Interpolative Separable Density Fitting through Centroidal Voronoi Tessellation With Applications to Hybrid Functional Electronic Structure Calculations
Kun Dong, Wei Hu, Lin Lin

TL;DR
This paper introduces a fast, density-based centroidal Voronoi tessellation method for selecting interpolation points in density fitting, significantly reducing computational cost while maintaining accuracy in hybrid functional electronic structure calculations.
Contribution
The authors propose a novel CVT-based approach for selecting interpolation points in ISDF, replacing the expensive QRCP method with a more efficient, density-driven algorithm.
Findings
CVT method achieves comparable accuracy to QRCP-based method.
CVT significantly reduces computational time in large-scale calculations.
Enhanced smoothness of potential energy surface in AIMD simulations.
Abstract
The recently developed interpolative separable density fitting (ISDF) decomposition is a powerful way for compressing the redundant information in the set of orbital pairs, and has been used to accelerate quantum chemistry calculations in a number of contexts. The key ingredient of the ISDF decomposition is to select a set of non-uniform grid points, so that the values of the orbital pairs evaluated at such grid points can be used to accurately interpolate those evaluated at all grid points. The set of non-uniform grid points, called the interpolation points, can be automatically selected by a QR factorization with column pivoting (QRCP) procedure. This is the computationally most expensive step in the construction of the ISDF decomposition. In this work, we propose a new approach to find the interpolation points based on the centroidal Voronoi tessellation (CVT) method, which offers a…
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Taxonomy
TopicsAdvanced Chemical Physics Studies · Advanced NMR Techniques and Applications · Machine Learning in Materials Science
