Truncating the memory time in nonequilibrium dynamical mean field theory calculations

• Published in: Physical review. B 2018-06, Vol.97 (24), Article 245129
• Main Authors: Schüler, Michael, Eckstein, Martin, Werner, Philipp
• Format: Article
• Language: English
• Subjects: Computational efficiency; Computer memory; Computer simulation; Electronic structure; Equations of motion; Green's functions; Markov processes; Mean field theory; System effectiveness; Thermalization (energy absorption); Time dependence
• ISSN: 2469-9950; 2469-9969
• DOI: 10.1103/PhysRevB.97.245129

The nonequilibrium Green's functions (NEGF) approach is a versatile theoretical tool, which allows to describe the electronic structure, spectroscopy, and dynamics of strongly correlated systems. The applicability of this method is, however, limited by its considerable computational cost. Due to the treatment of the full two-time dependence of the NEGF, the underlying equations of motion involve a long-lasting non-Markovian memory kernel that results in at least an Nt3 scaling in the number of time points Nt. The system's memory time is, however, reduced in the presence of a thermalizing bath. In particular, dynamical mean field theory (DMFT), one of the most successful approaches to strongly correlated lattice systems, maps extended systems to an effective impurity coupled to a bath. In this work, we systematically investigate how the memory time can be truncated in nonequilibrium DMFT simulations of the Hubbard and Hubbard-Holstein models. We show that suitable truncation schemes, which substantially reduce the computational cost, result in excellent approximations to the full time evolution. This approach enables the propagation to longer times, making fundamental processes such as prethermalization and the final stages of thermalization accessible to nonequilibrium DMFT.