Efficient treatment of two-particle vertices in dynamical mean-field theory

TL;DR

This paper introduces a numerically stable and efficient algorithm for calculating two-particle response functions in dynamical mean-field theory, leveraging high-frequency asymptotics for improved convergence.

Contribution

The authors develop a novel algorithm that accurately infers the asymptotic behavior of the irreducible vertex function, enhancing computational stability and efficiency in DMFT calculations.

Findings

Rapid convergence of the vertex function towards its asymptotic form observed

Algorithm tested successfully on multiple examples

Improved numerical stability in two-particle response calculations

Abstract

We present an efficient and numerically stable algorithm for calculation of two-particle response functions within the dynamical mean-field theory. The technique is based on inferring the high frequency asymptotic behavior of the irreducible vertex function from the local dynamical susceptibility. The algorithm is tested on several examples. In all cases rapid convergence of the vertex function towards its asymptotic form is observed.