Continuous momentum dependence in the dynamical cluster approximation

Urs R. Hähner, Thomas A. Maier, Thomas C. Schulthess

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The dynamical cluster approximation (DCA) is a quantum cluster extension to the single-site dynamical mean-field theory that incorporates spatially nonlocal dynamic correlations systematically and nonperturbatively. The DCA+ algorithm addresses the cluster shape dependence of the DCA and improves the convergence with cluster size by introducing a lattice self-energy with continuous momentum dependence. However, we show that the DCA+ algorithm is plagued by a fundamental problem when its self-consistency equations are formulated using the bare Green's function of the cluster. This problem is most severe in the strongly correlated regime at low doping, where the DCA+ self-energy becomes overly metallic and local, and persists to cluster sizes where the standard DCA has long converged. In view of the failure of the DCA+ algorithm, we propose to complement DCA simulations with a post-interpolation procedure for single-particle and two-particle correlation functions to preserve continuous momentum dependence and the associated benefits in the DCA. We demonstrate the effectiveness of this practical approach with results for the half-filled and hole-doped two-dimensional Hubbard model.

Original languageEnglish
Article number195114
JournalPhysical Review B
Volume101
Issue number19
DOIs
StatePublished - May 15 2020

Funding

All simulations were done using the DCA++ code [20]. The work of T.A.M. was supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, Division of Materials Sciences and Engineering. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program and of the Swiss National Supercomputing Center (CSCS). OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. All simulations were done using the code . The work of T.A.M. was supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, Division of Materials Sciences and Engineering. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program and of the Swiss National Supercomputing Center (CSCS). OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

FundersFunder number
Advanced Scientific Computing Research and Basic Energy Sciences
DOE Office of Science
Swiss National Supercomputing Center
U.S. Department of Energy
Office of ScienceDE-AC05-00OR22725
Advanced Scientific Computing Research
Division of Materials Sciences and Engineering

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