Efficient Implementation of the Random Phase Approximation with Domain-Based Local Pair Natural Orbitals

We present an efficient implementation of the direct random phase approximation (RPA) for molecular systems within the domain-based local pair natural orbital (DLPNO) framework. With recommended loose, normal, and tight parameter settings, DLPNO-RPA achieves approximately 99.7-99.95% accuracy in the total correlation energy compared to a canonical implementation, enabling highly accurate reaction energies and potential energy surfaces to be computed while substantially reducing computational costs. As an application, we demonstrate the capability of DLPNO-RPA to efficiently calculate basis set-converged binding energies for a set of large molecules, with results showing excellent agreement with high-level reference data from both coupled cluster and diffusion Monte Carlo. This development paves the way for the routine use of RPA-based methods in molecular quantum chemistry.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-03-05
DOI
https://doi.org/10.1021/acs.jctc.4c01540
Citations
2
Primary Topic
Quantum, superfluid, helium dynamics
Type
article
Field-Weighted Citation Impact
2.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient Implementation of the Random Phase Approximation with Domain-Based Local Pair Natural Orbitals

Timothy C. Berkelbach, Yu Hsuan Liang, Hong‐Zhou Ye, Garnet Kin‐Lic Chan et al.
2 citations
Journal of Chemical Theory and Computation
Quantum, superfluid, helium dynamics
2.49
article

Efficient Implementation of the Random Phase Approximation with Domain-Based Local Pair Natural Orbitals

Timothy C. Berkelbach, Yu Hsuan Liang, Hong‐Zhou Ye, Garnet Kin‐Lic Chan, Xing Zhang
article en
2 citations

Abstract

We present an efficient implementation of the direct random phase approximation (RPA) for molecular systems within the domain-based local pair natural orbital (DLPNO) framework. With recommended loose, normal, and tight parameter settings, DLPNO-RPA achieves approximately 99.7-99.95% accuracy in the total correlation energy compared to a canonical implementation, enabling highly accurate reaction energies and potential energy surfaces to be computed while substantially reducing computational costs. As an application, we demonstrate the capability of DLPNO-RPA to efficiently calculate basis set-converged binding energies for a set of large molecules, with results showing excellent agreement with high-level reference data from both coupled cluster and diffusion Monte Carlo. This development paves the way for the routine use of RPA-based methods in molecular quantum chemistry.

Journal of Chemical Theory and ComputationVol. 21(6)
California Institute of Technology (US), Center for Physical Sciences and Technology (LT), Institute of Catalysis and Petrochemistry (RU), Division of Chemistry (US), Flatiron Health (United States) (US), Flatiron Institute (US), University of Maryland, College Park (US), Columbia University (US)
Simons Foundation, Columbia University, University of Maryland, Office of Science, Division of Chemistry
Openalex Percentile: Top 13%
Quantum, superfluid, helium dynamics
2.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.