Computing the self-consistent field in Kohn-Sham density functional theory

N. D. Woods; M. C. Payne; P. J. Hasnip

doi:10.1088/1361-648X/ab31c0

Computing the self-consistent field in Kohn-Sham density functional theory

N. D. Woods^*, M. C. Payne, P. J. Hasnip

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

Abstract

A new framework is presented for evaluating the performance of self-consistent field methods in Kohn-Sham density functional theory (DFT). The aims of this work are two-fold. First, we explore the properties of Kohn-Sham DFT as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms in the present context, comprising a representative benchmark suite of over fifty Kohn-Sham simulation inputs, the scf-x _n suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner.

Original language	English
Article number	453001
Journal	Journal of Physics Condensed Matter
Volume	31
Issue number	45
DOIs	https://doi.org/10.1088/1361-648X/ab31c0
Publication status	Published - 14 Aug 2019

Bibliographical note

Publisher Copyright:
© 2019 IOP Publishing Ltd.

Keywords

density functional theory
density mixing
non-linear optimisation
numerical analysis
self-consistent field methods

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Woods_2019_J._Phys.__Condens._Matter_31_453001
© 2019 IOP Publishing Ltd
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Cite this

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title = "Computing the self-consistent field in Kohn-Sham density functional theory",

abstract = "A new framework is presented for evaluating the performance of self-consistent field methods in Kohn-Sham density functional theory (DFT). The aims of this work are two-fold. First, we explore the properties of Kohn-Sham DFT as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms in the present context, comprising a representative benchmark suite of over fifty Kohn-Sham simulation inputs, the scf-x n suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner.",

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author = "Woods, {N. D.} and Payne, {M. C.} and Hasnip, {P. J.}",

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month = aug,

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doi = "10.1088/1361-648X/ab31c0",

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AU - Woods, N. D.

AU - Payne, M. C.

AU - Hasnip, P. J.

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Y1 - 2019/8/14

N2 - A new framework is presented for evaluating the performance of self-consistent field methods in Kohn-Sham density functional theory (DFT). The aims of this work are two-fold. First, we explore the properties of Kohn-Sham DFT as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms in the present context, comprising a representative benchmark suite of over fifty Kohn-Sham simulation inputs, the scf-x n suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner.

AB - A new framework is presented for evaluating the performance of self-consistent field methods in Kohn-Sham density functional theory (DFT). The aims of this work are two-fold. First, we explore the properties of Kohn-Sham DFT as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms in the present context, comprising a representative benchmark suite of over fifty Kohn-Sham simulation inputs, the scf-x n suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner.

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KW - density mixing

KW - non-linear optimisation

KW - numerical analysis

KW - self-consistent field methods

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Computing the self-consistent field in Kohn-Sham density functional theory

Abstract

Bibliographical note

Keywords

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