The CrMES scheme as an alternative to Importance Sampling: The tail regime of the order-parameter distribution

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dc.creatorMalakis, Anastasios
dc.creatorFytas, Nikolaos G.
dc.date2005-09-22
dc.date.accessioned2026-07-07T08:57:33Z
dc.date.available2026-07-07T08:57:33Z
dc.descriptionWe review the recently developed critical minimum energy-subspace (CrMES) technique. This scheme produces an immense optimization of popular algorithms, such as the Wang-Landau (WL) and broad histogram methods, by predicting the essential part of the energy space necessary for the estimation of the critical behavior and provides a new route of critical exponent estimation. A powerful and efficient CrMES entropic sampling scheme is proposed as an alternative to the traditional importance sampling methods. Utilizing the WL random walk process in the dominant energy subspace (CrMES-WL sampling) and using the WL approximation of the density of states and appropriate microcanonical estimators we determine the magnetic properties of the 2D Ising model. Updating $(E,M)$ histograms during the high level WL-iterations, we provide a comprehensive alternative scheme to the Metropolis algorithm and by applying this procedure we present a convincing analysis for the far tail regime of the order-parameter probability distribution.
dc.description7 pages, 5 figures, Proceedings of the third NEXT Sigma Phi International Conference, Kolymbari, Greece (2005)
dc.identifierhttps://arxiv.org/abs/cond-mat/0509567
dc.identifierhttp://arxiv.org/abs/cond-mat/0509567
dc.identifierPhysica A 365, 197 (2006)
dc.identifierdoi:10.1016/j.physa.2006.01.018
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/147013
dc.subjectStatistical Mechanics
dc.titleThe CrMES scheme as an alternative to Importance Sampling: The tail regime of the order-parameter distribution
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