Non-Negative Least Squares Reweighting and Pruning of Quadrature Grids for Tensor Hypercontraction

Fuente: arXiv
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Auteurs principaux: Hillers-Bendtsen, Andreas Erbs, Lu, Lixin, Martínez, Todd J.
Format: Preprint
Publié: 2026
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author Hillers-Bendtsen, Andreas Erbs
Lu, Lixin
Martínez, Todd J.
author_facet Hillers-Bendtsen, Andreas Erbs
Lu, Lixin
Martínez, Todd J.
contents Tensor hypercontraction provides an attractive four-center two-electron repulsion integral format that can lower the scaling of many electronic structure methods while only requiring O(N^2) memory. However, in its grid-based least-squares incarnation, tensor hypercontraction requires the tedious design of compact spatial quadrature grids to achieve efficiency and accuracy, representing a bottleneck for widespread application. To simplify grid generation, we devise a reweighting scheme in which the grid weights are optimized to ensure accurate reproduction of the atomic orbital overlap matrix by numerical integration. By casting this fitting task as a non-negative least-squares problem, we obtain a black-box methodology that not only yields robust grids for tensor hypercontraction as well as numerical integration of other integrals but also prunes the grids by zeroing quadrature weights for insignificant points.
format Preprint
id arxiv_https___arxiv_org_abs_2604_03899
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Non-Negative Least Squares Reweighting and Pruning of Quadrature Grids for Tensor Hypercontraction
Hillers-Bendtsen, Andreas Erbs
Lu, Lixin
Martínez, Todd J.
Chemical Physics
Tensor hypercontraction provides an attractive four-center two-electron repulsion integral format that can lower the scaling of many electronic structure methods while only requiring O(N^2) memory. However, in its grid-based least-squares incarnation, tensor hypercontraction requires the tedious design of compact spatial quadrature grids to achieve efficiency and accuracy, representing a bottleneck for widespread application. To simplify grid generation, we devise a reweighting scheme in which the grid weights are optimized to ensure accurate reproduction of the atomic orbital overlap matrix by numerical integration. By casting this fitting task as a non-negative least-squares problem, we obtain a black-box methodology that not only yields robust grids for tensor hypercontraction as well as numerical integration of other integrals but also prunes the grids by zeroing quadrature weights for insignificant points.
title Non-Negative Least Squares Reweighting and Pruning of Quadrature Grids for Tensor Hypercontraction
topic Chemical Physics
url https://arxiv.org/abs/2604.03899