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The European Physical Journal Special Topics

, Volume 226, Issue 11, pp 2525–2547

Dynamical Mean-Field Approach with Predictive Power for Strongly Correlated Materials

Abstract

We discuss the efficient implementation of general impurity solvers for dynamical mean-field theory. We show that both Lanczos and quantum Monte Carlo in different flavors Hirsch-Fye, continuous-time hybridization- and interaction-expansion exhibit excellent scaling on massively parallel supercomputers. We apply these algorithms to simulate realistic model Hamiltonians including the full Coulomb vertex, crystal-field splitting, and spin-orbit interaction. We discuss how to remove the sign problem in the presence of non-diagonal crystal-field and hybridization matrices. We show how to extract the physically observable quantities from imaginary time data, in particular correlation functions and susceptibilities. Finally, we present benchmarks and applications for representative correlated systems.

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Autor: M. Baumgärtel - K. Ghanem - A. Kiani - E. Koch - E. Pavarini - H. Sims - G. Zhang

Fuente: https://link.springer.com/







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