arXiv · 1711.05346
Lifted Worm Algorithm for the Ising Model
Abstract
We design an irreversible worm algorithm for the zero-field ferromagnetic Ising model by using the lifting technique. We study the dynamic critical behavior of an energy estimator on both the complete graph and toroidal grids, and compare our findings with reversible algorithms such as the Prokof'ev-Svistunov worm algorithm. Our results show that the lifted worm algorithm improves the dynamic exponent of the energy estimator on the complete graph, and leads to a significant constant improvement on toroidal grids.
Explore related subjects
Keep this discovery
Eren Metin Elçi, Jens Grimm, Lijie Ding, Abrahim Nasrawi, Timothy M. Garoni, Youjin Deng. 2017-11-14. Lifted Worm Algorithm for the Ising Model. https://doi.org/10.1103/physreve.97.042126
Cite the original work for its findings. Save a collection to share your selection of sources.