Performance Limitations of Flat Histogram Methods and Optimality of Wang-Landau Sampling

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dc.creatorDayal, P.
dc.creatorTrebst, S.
dc.creatorWessel, S.
dc.creatorWuertz, D.
dc.creatorTroyer, M.
dc.creatorSabhapandit, S.
dc.creatorCoppersmith, S. N.
dc.date2003-06-05
dc.date.accessioned2026-07-07T02:51:40Z
dc.date.available2026-07-07T02:51:40Z
dc.descriptionWe determine the optimal scaling of local-update flat-histogram methods with system size by using a perfect flat-histogram scheme based on the exact density of states of 2D Ising models.The typical tunneling time needed to sample the entire bandwidth does not scale with the number of spins N as the minimal N^2 of an unbiased random walk in energy space. While the scaling is power law for the ferromagnetic and fully frustrated Ising model, for the +/- J nearest-neighbor spin glass the distribution of tunneling times is governed by a fat-tailed Frechet extremal value distribution that obeys exponential scaling. We find that the Wang-Landau algorithm shows the same scaling as the perfect scheme and is thus optimal.
dc.description5 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0306108
dc.identifierhttp://arxiv.org/abs/cond-mat/0306108
dc.identifierPhys. Rev. Lett. 92, 097201 (2004)
dc.identifierdoi:10.1103/PhysRevLett.92.097201
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/21551
dc.subjectStatistical Mechanics
dc.titlePerformance Limitations of Flat Histogram Methods and Optimality of Wang-Landau Sampling
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