Variational density matrix optimization using semidefinite programming

Details Variational density matrix optimization using semidefinite programming Variational density matrix optimization using semidefinite programming

2010-06-18

arxiv.org/abs/1006.3721v2

Computer Physics Communications, 182(9, SI):2025-2028, SEP 2011

Physics

Computational Physics

corrected typos, added doi

Scientific paper

10.1016/j.cpc.2010.12.034

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.

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