Bold Diagrammatic Monte Carlo in the Lens of Stochastic Iterative Methods
Provides theoretical understanding of BDMC convergence for researchers using diagrammatic Monte Carlo in quantum many-body physics.
The paper analyzes bold diagrammatic Monte Carlo (BDMC) methods through the lens of stochastic iterative methods, investigating convergence enhancement via condition number analysis, and compares BDMC with related approaches on model systems.
This work aims at understanding of bold diagrammatic Monte Carlo (BDMC) methods for stochastic summation of Feynman diagrams from the angle of stochastic iterative methods. The convergence enhancement trick of the BDMC is investigated from the analysis of condition number and convergence of the stochastic iterative methods. Numerical experiments are carried out for model systems to compare the BDMC with related stochastic iterative approaches.