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Published October 15, 2012 | Published
Journal Article Open

Truncated configuration interaction expansions as solvers for correlated quantum impurity models and dynamical mean-field theory

Abstract

The development of polynomial cost solvers for correlated quantum impurity models, with controllable errors, is a central challenge in quantum many-body physics, where these models find applications ranging from nanoscience to the dynamical mean-field theory (DMFT). Here, we describe how configuration interaction (CI) approximations to exact diagonalization (ED) may be used as solvers in DMFT. CI approximations retain the main advantages of ED, such as the ability to treat general interactions and off-diagonal hybridizations and to obtain real spectral information, but are of polynomial cost. Furthermore, their errors can be controlled by monitoring the convergence of physical quantities as a function of the CI hierarchy. Using benchmark DMFT applications, such as single-site DMFT of the one-dimensional Hubbard model and 2×2 cluster DMFT of the two-dimensional Hubbard model, we show that CI approximations allow us to obtain near-exact ED results for a tiny fraction of the cost. This is true over the entire range of interaction strengths including "difficult" regimes, such as in the pseudogap phase of the two-dimensional Hubbard model. We use the ability of CI approximations to treat large numbers of orbitals to demonstrate convergence of the bath representation in the 2×2 cluster DMFT using a 24-bath orbital representation. CI approximations thus form a promising route to extend ED to problems that are currently difficult to study using other solvers such as continuous-time quantum Monte Carlo, including impurity models with large numbers of orbitals and general interactions.

Additional Information

© 2012 American Physical Society. Received 12 March 2012; published 22 October 2012. D. Zgid acknowledges helpful discussions with A. J. Millis, D. R. Reichman, A. I. Lichtenstein, L. de Medici, and A. Liebsch. D. Zgid and G. K.-L. Chan acknowledge support from the Department of Energy, Office of Science, through Award No. DE-FG02-07ER46432. E. Gull was partially supported by NSF-DMR-1006282.

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August 19, 2023
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