Accelerating self-consistent field convergence with the augmented Roothaan-Hall energy function.
Abstract
Based on Pulay's direct inversion iterative subspace (DIIS) approach, we present a
method to accelerate self-consistent field (SCF) convergence. In this method, the
quadratic augmented Roothaan-Hall (ARH) energy function, proposed recently by Høst
and co-workers [J. Chem. Phys. 129, 124106 (2008)], is used as the object of minimization
for obtaining the linear coefficients of Fock matrices within DIIS. This differs from
the traditional DIIS of Pulay, which uses an object function derived from the commutator
of the density and Fock matrices. Our results show that the present algorithm, abbreviated
ADIIS, is more robust and efficient than the energy-DIIS (EDIIS) approach. In particular,
several examples demonstrate that the combination of ADIIS and DIIS ("ADIIS+DIIS")
is highly reliable and efficient in accelerating SCF convergence.
Type
Journal articleSubject
AccelerationBiophysics
Computer Simulation
Equipment Design
Image Interpretation, Computer-Assisted
Protein Conformation
Quantum Theory
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https://hdl.handle.net/10161/3375Published Version (Please cite this version)
10.1063/1.3304922Publication Info
Hu, Xiangqian; & Yang, Weitao (2010). Accelerating self-consistent field convergence with the augmented Roothaan-Hall energy
function. J Chem Phys, 132(5). pp. 054109. 10.1063/1.3304922. Retrieved from https://hdl.handle.net/10161/3375.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Weitao Yang
Philip Handler Distinguished Professor of Chemistry
Prof. Yang, the Philip Handler Professor of Chemistry, is developing methods for quantum
mechanical calculations of large systems and carrying out quantum mechanical simulations
of biological systems and nanostructures. His group has developed the linear scaling
methods for electronic structure calculations and more recently the QM/MM methods
for simulations of chemical
reactions in enzymes.

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