Multilevel coarse graining and nano-pattern discovery in many particle stochastic systems
The authors consider accelerating microscopic simulation methods with competing short and long range interactions arising in numerous physical systems and propose the multilevel coarse graining Monte Carlo method based on a hybrid statistical mechanics and statistics approach. The method can be designed to sample the exact or controlled-error approximations of the target distribution, providing information on levels of different resolutions, as well as the microscopic level. Applications in phase transition and pattern formation problems confirm the efficiency of the proposed methods.
scientific article; zbMATH DE number 6036616
scientific article