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DCA$^+$: Dynamical Cluster Approximation with continuous lattice self-energy by Staar, Peter; Maier, Thomas; Schulthess, Thomas C. is a scholarly article available to read on EtoBox.

What is DCA$^+$: Dynamical Cluster Approximation with continuous lattice self-energy about?

The dynamical cluster approximation (DCA) is a systematic extension beyond the single site approximation in dynamical mean field theory (DMFT), to include spatially non-local correlations in quantum many-body simulations of strongly correlated systems. We extend the DCA with a continuous lattice self-energy in oder to achieve better convergence with cluster size. The new method, which we call DCA$^+$, cures the cluster shape dependence problems of the DCA, without suffering from causality violations of previous attempts to interpolate the cluster self-energy. A practical approach based on standard inference techniques is given to deduce the continuous lattice self-energy from an interpolated cluster self-energy. We study the pseudogap region of a hole-doped two-dimensional Hubbard model and find that in the DCA$^+$ algorithm, the self-energy and pseudo-gap temperature $T^*$ converge monotonously with cluster size. Introduction of a continuous lattice self-energy eliminates artificial long-rage correlations and thus significantly reduces the sign problem of the quantum Monte Carlo cluster solver in the DCA$^+$ algorithm compared to the normal DCA. Simulations with much larger cluste

Author

Staar, Peter; Maier, Thomas; Schulthess, Thomas C.

Published

2013

Language

EN