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Stochastic Vector Techniques in Ground-State Electronic Structure

delete2022-04-20
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OA
AI
R
Roi Baer *
D
Daniel Neuhauser
E
Eran Rabani
DOI:10.1146/annurev-physchem-090519-045916delete
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Abstract

Abstract

En 中文
We review a suite of stochastic vector computational approaches for studying the electronic structure of extended condensed matter systems. These techniques help reduce algorithmic complexity, facilitate efficient parallelization, simplify computational tasks, accelerate calculations, and diminish memory requirements. While their scope is vast, we limit our study to ground-state and finite temperature density functional theory (DFT) and second-order many-body perturbation theory. More advanced topics, such as quasiparticle (charge) and optical (neutral) excitations and higher-order processes, are covered elsewhere. We start by explaining how to use stochastic vectors in computations, characterizing the associated statistical errors. Next, we show how to estimate the electron density in DFT and discuss effective techniques to reduce statistical errors. Finally, we review the use of stochastic vectors for calculating correlation energies within the second-order Moller-Plesset perturbation theory and its finite temperature variational form. Example calculation results are presented and used to demonstrate the efficacy of the methods.
Keywords:
stochastic vectors
stochastic trace
density functional theory
linear scaling

Journal

Annual Review of Physical Chemistry cover
Annual Review of Physical Chemistry
IF:
11.7
Papers:
1.5K
Citations:
8.9K

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U
university of california los angeles
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5.3W
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University of California System cover
University of California System
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Papers: 33.7W
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H
Hebrew University of Jerusalem
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