Adaptively truncated Hilbert space based impurity solver for dynamical mean-field theory

Abstract

We present an impurity solver based on adaptively truncated Hilbert spaces. The solver is particularly suitable for dynamical mean-field theory in circumstances where quantum Monte Carlo approaches are ineffective. It exploits the sparsity structure of quantum impurity models, in which the interactions couple only a small subset of the degrees of freedom. We further introduce an adaptive truncation of the particle or hole excited spaces, which enables computations of Green functions with an accuracy needed to avoid unphysical (sign change of imaginary part) self-energies. The method is benchmarked on the one-dimensional Hubbard model.

10 pages, 7 figures

References in corpus (8)

• Continuous-time Monte Carlo methods for quantum impurity models
• The numerical renormalization group method for quantum impurity systems
• Truncated Configuration Interaction expansions as solvers for correlated quantum impurity models and dynamical mean field theory
• Sum-rules and bath-parametrization for quantum cluster theories
• Two-stage metal-insulator transition in the 2D Hubbard model: momentum selectivity in the 8-site dynamical cluster approximation
• Bath optimization in the Cellular Dynamical Mean Field Theory
• Analytical continuation of imaginary axis data using maximum entropy
• Properties of the one-dimensional Hubbard model: cellular dynamical mean-field description

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