Bold Diagrammatic Monte Carlo in the Lens of Stochastic Iterative Methods

Abstract

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.

References in corpus (4)

• Fermi-Polaron: Diagrammatic Monte Carlo for Divergent Sign-Alternating Series
• Applications of quantum Monte Carlo methods in condensed systems
• Bold Diagrammatic Monte Carlo: When Sign Problem is Welcome
• Bold Diagrammatic Monte Carlo Method Applied to Fermionized Frustrated Spins

Cited by in corpus (5)

• Solving Caldeira-Leggett Model by Inchworm Method with Frozen Gaussian Approximation
• Numerical analysis for inchworm Monte Carlo method: Sign problem and error growth
• Triangularized Orthogonalization-free Method for Solving Extreme Eigenvalue Problems
• Bold Feynman diagrams and the Luttinger-Ward formalism via Gibbs measures. Part I: Perturbative approach
• Inchworm Monte Carlo method for open quantum systems