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Variational determination of the two-particle density matrix as a quantum many-body technique

In this thesis the variational optimisation of the density matrix is discussed as a method in many-body quantum mechanics. This is a relatively unknown technique in which one tries to obtain the two-particle reduced density matrix directly in a variational approach. In the first Chapter we introduce the subject in the broader context of many-body quantum mechanics, and briefly sketch the history of the field. The second Chapter tries to summarise what is known about N-representability of reduced density matrices, and derives these results in a unified framework. The optimisation problem can be formulated as a semidefinite program. Three different algorithms are discussed in Chapter three, and their performance is compared. In Chapter four we show how symmetry can be exploited to reduce the computational cost considerably. Several applications of the method are discussed in Chapter five. We show that the standard two-index constraints fail in the strong-correlation limit of the one-dimensional Hubbard model. In Chapter six we identify the spin-adapted lifting conditions as the most compact constraints that can correctly describe this limit.