Random Phase Approximation Correlation Energy using Real-Space Density Functional Perturbation Theory

Fuente: arXiv
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Autori principali: Zhang, Boqin, Shah, Shikhar, Pask, John E., Chow, Edmond, Suryanarayana, Phanish
Natura: Preprint
Pubblicazione: 2025
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author Zhang, Boqin
Shah, Shikhar
Pask, John E.
Chow, Edmond
Suryanarayana, Phanish
author_facet Zhang, Boqin
Shah, Shikhar
Pask, John E.
Chow, Edmond
Suryanarayana, Phanish
contents We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method, while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method's accuracy by comparing with planewave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 seconds on 4608 processors.
format Preprint
id arxiv_https___arxiv_org_abs_2504_01816
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Random Phase Approximation Correlation Energy using Real-Space Density Functional Perturbation Theory
Zhang, Boqin
Shah, Shikhar
Pask, John E.
Chow, Edmond
Suryanarayana, Phanish
Computational Physics
Materials Science
Chemical Physics
We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method, while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method's accuracy by comparing with planewave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 seconds on 4608 processors.
title Random Phase Approximation Correlation Energy using Real-Space Density Functional Perturbation Theory
topic Computational Physics
Materials Science
Chemical Physics
url https://arxiv.org/abs/2504.01816