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On a New Solution to the Electron Correlation Problem in Quantum Chemistry: The Density Matrix Renormalization Group Algorithm: the density matrix renormalization group algorithm

Gerrit Moritz

Published Jan 1, 2007• 0 citations
Publisher
DOI
10.3929/ethz-a-005537491

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Quantum Chemistry / Electron Correlation / Density Matrix Renormalization Group / Transition Metal Chemistry In this work, we derive the density matrix renormalization group (DMRG) algorithm in the language of configuration interaction. Furthermore, the development of DMRG in quantum chemistry is reviewed and DMRG-specific peculiarities are discussed. Finally, we discuss new results for a dinuclear μ -oxo bridged copper cluster, which is an important active-site structure in transition-metal chemistry, an area in which we pioneered the application of DMRG.
This chapter is concerned with the problem of strongly correlated electrons in quantum chemistry. We describe how a technique known as the density matrix renormalization group (DMRG) can tackle complicated chemical problems of strong correlation by capturing the local nature of the correlations. We analyse the matrix product state structure of the DMRG wavefunction that encodes one-dimensional aspects of locality. We also discuss the connection to the traditional ideas of the renormalization group. We finish with a survey of applications of the DMRG, its strengths and weaknesses in chemical applications, and its recent promising generalization to tensor network states.
We study the recently developed Density Matrix Renormalization Group (DMRG) algorithm in the context of quantum chemistry. In contrast to traditional approaches, this algorithm is believed to yield arbitrarily high accuracy in the energy with only polynomial computational effort. We describe in some detail how this is achieved. We begin by introducing the principles of the renormalization procedure, and how one formulates an algorithm for use in quantum chemistry. The renormalization group algorithm is then interpreted in terms of familiar quantum chemical concepts, and its numerical behavior, including its convergence and computational cost, are studied using both model and real systems. The asymptotic convergence of the algorithm is derived. Finally, we examine the performance of the DMRG on widely studied chemical problems, such as the water molecule, the twisting barrier of ethene, and the dissociation of nitrogen. In all cases, the results compare favorably with the best existing quantum chemical methods, and particularly so when the nondynamical correlation is strong. Some perspectives for future development are given.