In this paper a fast impurity solver is proposed for dynamical mean-field theory (DMFT) based on a decoupling of the equations of motion for the impurity Green's function. The resulting integral equations are solved efficiently with a method based on genetic algorithms. The Hubbard and periodic Anderson models are studied with this impurity solver. The method describes the Mott metal-insulator transition and works for a large range of parameters at finite temperature on the real frequency axis. This makes it useful for the exploration of real materials in the framework of local-density
approximation+DMFT.
In this paper we explore the use of an equation of motion decoupling method as an impurity solver to be used in conjunction with the dynamical mean field self-consistency condition for the solution of lattice models. We benchmark the impurity solver against exact diagonalization, and apply the method to study the infinite
U Hubbard model, the periodic Anderson model and the
pd model. This simple and numerically efficient approach yields the spectra expected for strongly correlated materials, with a quasiparticle peak and a Hubbard band. It works in a large range of parameters, and therefore can be used for the exploration of real materials using the local density approximation and dynamical mean field theory.