Articles dans des revues à comité de lecture
|Cluster Monte Carlo and dynamical scaling for long-range interactions|
|Flores-Sola E., Weigel M., Kenna R., Berche B.|
|Eur. Phys. J. Special Topics 226 (2017) 581-594|
|DOI : 10.1140/epjst/e2016-60338-3|
|ArXiv : arxiv:1611.05659 [PDF]|
Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each update from $O(N^2)$ to $O(N \ln N)$ or even $O(N)$, thus promising an even more dramatic computational speed-up. Here, we review the available algorithms and propose a new and particularly efficient single-cluster variant. The efficiency and dynamical scaling of the available algorithms are investigated for the Ising model with power-law decaying interactions.