Compression of the electron repulsion integral tensor in tensor hypercontraction format with cubic scaling cost
Abstract
© 2015 Elsevier Inc.Electron repulsion integral tensor has ubiquitous applications
in electronic structure computations. In this work, we propose an algorithm which
compresses the electron repulsion tensor into the tensor hypercontraction format with
O(nN2logN) computational cost, where N is the number of orbital functions and n is
the number of spatial grid points that the discretization of each orbital function
has. The algorithm is based on a novel strategy of density fitting using a selection
of a subset of spatial grid points to approximate the pair products of orbital functions
on the whole domain.
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Journal articlePermalink
https://hdl.handle.net/10161/14102Published Version (Please cite this version)
10.1016/j.jcp.2015.09.014Publication Info
Lu, J; & Ying, L (2015). Compression of the electron repulsion integral tensor in tensor hypercontraction format
with cubic scaling cost. Journal of Computational Physics, 302. pp. 329-335. 10.1016/j.jcp.2015.09.014. Retrieved from https://hdl.handle.net/10161/14102.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Jianfeng Lu
Professor of Mathematics
Jianfeng Lu is an applied mathematician interested in mathematical analysis and algorithm
development for problems from computational physics, theoretical chemistry, materials
science and other related fields.More specifically, his current research focuses include:Electronic
structure and many body problems; quantum molecular dynamics; multiscale modeling
and analysis; rare events and sampling techniques.

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