Diagrammatic Monte Carlo and stochastic optimization methods for complex composite objects in macroscopic baths

Abstract

We give an introduction to the Diagrammatic Monte Carlo method, which provides an efficient numerical scheme for the approximation-free calculation of Matsubara Green functions and correlation functions in imaginary time. The analytic continuation from imaginary times to real frequencies is performed by a stochastic optimization procedure. © Springer-Verlag Berlin Heidelberg 2008.