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Title: Approximate Green’s Function Coupled Cluster Method Employing Effective Dimension Reduction

Journal Article · · Journal of Chemical Theory and Computation
ORCiD logo [1]; ORCiD logo [2];  [2]; ORCiD logo [1];  [2]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
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The Green's function coupled cluster (GFCC) method is a powerful many-body tool for computing the electronic structure of molecular and periodic systems, especially when electrons of the system are strongly correlated. However, for the GFCC to be routinely used in the electronic structure calculations, robust numerical techniques and approximations must be employed to reduce its high computational overhead. In our recent studies, we demonstrated that the GFCC equations can be solved directly in the frequency domain using iterative linear solvers, which can be easily distributed in a massively parallel environment. In the present work, we demonstrate a successful application of model-order-reduction (MOR) techniques in the GFCC framework. Briefly, for a frequency regime which requires high resolution spectral function, instead of solving GFCC linear equation of full dimension for every single frequency point, an efficiently-solvable linear system model of a reduced dimension may be built upon projecting the original GFCC linear system onto a subspace. From this reduced order model is obtained a reasonable approximation to the full dimensional GFCC linear equations in both interpolative and extrapolative spectral regions. Furthermore, we show that the subspace can be properly constructed in an iterative manner from the auxiliary vectors of the GFCC linear equations at some selected frequencies within the spectral region of interest. During the iterations, the quality of the subspace and the linear system model can be systematically improved. The method is tested in terms of the efficiency and accuracy of computing spectral functions for some typical molecular systems such as carbon monoxide, 1,3-butadiene, benzene, and adenine. As a byproduct, the obtained reduced order model may provide a high quality initial guess which improves the convergence rate for the existing iterative linear solver.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1498694
Journal Information:
Journal of Chemical Theory and Computation, Vol. 15, Issue 5; ISSN 1549-9618
Publisher:
American Chemical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 16 works
Citation information provided by
Web of Science

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Cited By (4)

Green’s function coupled cluster simulation of the near-valence ionizations of DNA-fragments journal January 2020
Rank reduced coupled cluster theory. II. Equation-of-motion coupled-cluster singles and doubles journal October 2019
Construction of Green's functions on a quantum computer: Quasiparticle spectra of molecules journal January 2020
The Chronus Quantum software package journal August 2019

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