Variational density matrix optimization using semidefinite programming

被引：1

作者：

Verstichel, Brecht ^{[1
]}

van Aggelen, Helen ^{[2
]}

Van Neck, Dimitri ^{[1
]}

Ayers, Paul W. ^{[3
]}

Bultinck, Patrick ^{[2
]}

机构：

[1] Univ Ghent, Ctr Mol Modeling, B-9052 Zwijnaarde, Belgium

[2] Univ Ghent, Dept Inorgan & Phys Chem, B-9000 Ghent, Belgium

[3] McMaster Univ, Dept Chem, Hamilton, ON L8S 4M1, Canada

来源：

COMPUTER PHYSICS COMMUNICATIONS | 2011年 / 182卷 / 09期

关键词：

Variational; Density matrix; Semidefinite programming; STATE CORRELATION ENERGIES; ATOMIC IONS;

D O I：

10.1016/j.cpc.2010.12.034

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We discuss how semidefinite programming can be used to determine the second-order density matrix directly through a variational optimization. We show how the problem of characterizing a physical or N-representable density matrix leads to matrix-positivity constraints on the density matrix. We then formulate this in a standard semidefinite programming form, after which two interior point methods are discussed to solve the SDP. As an example we show the results of an application of the method on the isoelectronic series of Beryllium. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：2025 / 2028

页数：4

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