We have recently introduced the tensor hypercontraction (THC) method for electronic structure, including MP2. Here, we present an algorithm for THC-MP2 that lowers the memory requirements as well as the prefactor while maintaining the formal quartic scaling that we demonstrated previously. We also describe a procedure to optimize quadrature grids used in grid-based least-squares (LS) THC-MP2. We apply this algorithm to generate grids for first-row atoms with less than 100 points/atom while incurring negligible errors in the computed energies. We benchmark the LS-THC-MP2 method using optimized grids for a wide variety of tests sets including conformational energies and reaction barriers in both the cc-pVDZ and cc-pVTZ basis sets. These tests demonstrate that the THC methodology is not limited to small basis sets and that it incurs negligible errors in both absolute and relative energies.
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http://dx.doi.org/10.1021/acs.jctc.5b00272 | DOI Listing |
J Phys Chem A
January 2025
Department of Chemistry, Southern Methodist University, Dallas, Texas 75275, United States.
Least-squares tensor hypercontraction (LS-THC) has received some attention in recent years as an approach to reduce the significant computational costs of wave function-based methods in quantum chemistry. However, previous work has demonstrated that LS-THC factorization performs disproportionately worse in the description of wave function components (e.g.
View Article and Find Full Text PDFJ Phys Chem A
September 2024
Department of Chemistry, University of Colorado, Boulder, Colorado 80302, United States.
In this article, we present an interpolative separable density fitting (ISDF)-based algorithm to calculate the exact exchange in periodic mean field calculations. In the past, decomposing the two-electron integrals into the tensor hypercontraction (THC) form using ISDF was the most expensive step of the entire mean field calculation. Here, we show that by using a multigrid-ISDF algorithm, both the memory and the CPU cost of this step can be reduced.
View Article and Find Full Text PDFJ Chem Phys
August 2024
Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA.
We present an efficient MPI-parallel algorithm and its implementation for evaluating the self-consistent correlated second-order exchange term (SOX), which is employed as a correction to the fully self-consistent GW scheme called scGWSOX (GW plus the SOX term iterated to achieve full Green's function self-consistency). Due to the application of the tensor hypercontraction (THC) in our computational procedure, the scaling of the evaluation of scGWSOX is reduced from O(nτnAO5) to O(nτN2nAO2). This fully MPI-parallel and THC-adapted approach enabled us to conduct the largest fully self-consistent scGWSOX calculations with over 1100 atomic orbitals with only negligible errors attributed to THC fitting.
View Article and Find Full Text PDFJ Chem Theory Comput
June 2024
Quantum Lab, Boehringer Ingelheim, 55218 Ingelheim am Rhein, Germany.
Quantum phase estimation based on qubitization is the state-of-the-art fault-tolerant quantum algorithm for computing ground-state energies in chemical applications. In this context, the 1-norm of the Hamiltonian plays a fundamental role in determining the total number of required iterations and also the overall computational cost. In this work, we introduce the symmetry-compressed double factorization (SCDF) approach, which combines a CDF of the Hamiltonian with the symmetry shift technique, significantly reducing the 1-norm value.
View Article and Find Full Text PDFJ Chem Theory Comput
March 2024
Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.
Even though cluster perturbation theory has been shown to be a robust noniterative alternative to coupled cluster theory, it is still plagued by high order polynomial computational scaling and the storage of higher order tensors. We present a proof-of-concept strategy for implementing a cluster perturbation theory ground-state energy series for the coupled cluster singles and doubles energy with computational scaling using tensor hypercontraction (THC). The reduction in computational scaling by two orders is achieved by decomposing two electron repulsion integrals, doubles amplitudes and multipliers, as well as selected double intermediates to the THC format.
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