Lifted worm algorithm for the Ising model

Eren Metin Elçi, Jens Grimm, Lijie Ding, Abrahim Nasrawi, Timothy M. Garoni, Youjin Deng

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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 energylike observable 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 energylike observable on the complete graph and leads to a significant constant improvement on toroidal grids.

Original languageEnglish
Article number042126
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume97
Issue number4
DOIs
StatePublished - Apr 18 2018
Externally publishedYes

Fingerprint

Dive into the research topics of 'Lifted worm algorithm for the Ising model'. Together they form a unique fingerprint.

Cite this