Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Physical review. B, Condensed matter

Wolff algorithm and anisotropic continuous-spin models: An application to the spin–van der Waals model

Marco D’Onorio De Meo, Suhk Kun Oh

Published Jul 1, 1992• 6 citations
Publisher

Abstract

The problem of applying Wolff's cluster algorithm to anisotropic classical spin models is resolved by modifying a part of the Wolff algorithm. To test the effectiveness of our modified algorithm, the spin--van der Waals model is investigated in detail. Our estimate of the dynamical exponent of the model is z=0.19\ifmmode\pm\else\textpm\fi{}0.04.

DOI
10.1103/physrevb.46.257

Related papers

Critical Dynamics Behavior of the Wolff Algorithm in the Site-Bond-Correlated Ising Model

Paulo R. A. Campos, Roberto Nicolau Onody

Here we apply the Wolff single-cluster algorithm to the site-bond-correlated Ising model and study its critical dynamical behavior. We have verified that the autocorrelation time diminishes in the presence of dilution and correlation, showing that the Wolff algorithm performs even better in such situations. The critical dynamical exponents are also estimated.

International Journal of Modern Physics C•Sep 1, 1998•0 citations

Numerical simulation study of the dynamical behavior of the Niedermayer algorithm

Daniel Girardi, N. S. Branco

We calculate the dynamic critical exponent for the Niedermayer algorithm applied to the two-dimensional Ising and XY models, for various values of the free parameter E 0 . For E 0 = − 1 we regain the Metropolis algorithm and for E 0 = 1 we regain the Wolff algorithm. For − 1 < E 0 < 1, we show that the mean size of the clusters of (possibly) turned spins initially grows with the linear size of the lattice, L , but eventually saturates at a given lattice size , which depends on E 0 . For , the Niedermayer algorithm is equivalent to the Metropolis one, i.e., they have the same dynamic exponent. For E 0 > 1, the autocorrelation time is always greater than for E 0 = 1 (Wolff) and, more important, it also grows faster than a power of L . Therefore, we show that the best choice of cluster algorithm is the Wolff one, when comparing against the Niedermayer generalization. We also obtain the dynamic behavior of the Wolff algorithm: although not conclusively, we propose a scaling law for the dependence of the autocorrelation time on L .

arXiv:1003.3655•Journal of Statistical Mechanics Theory and Experiment•Apr 16, 2010•2 citations

The influence of the Wolff cluster structure on the determination of the critical dynamic exponent

Paulo R. A. Campos, N.G.F. Demedeiros, Roberto Nicolau Onody

Recently we reported some interesting features of the Wolff algorithm behaviour when applied to the site-bond-correlated Ising model. Our main results were that a stronger correlation diminishes the autocorrelation time but it does not change or affect the critical dynamic exponent. In this work, we analyse the Wolff cluster structure and how it varies with the spatial correlation. The fractal dimensions are determined for several values of the magnetic atom concentration and spatial correlation, giving an estimation of the Wolff critical dynamic exponent.

Philosophical Magazine Letters•Jul 1, 1999•0 citations

The influence of the Wolff's cluster structure on the determination of the critical dynamic exponent

Paulo R. A. Campos, N. G. F. de Medeiros, Roberto Nicolau Onody

Recently we reported some interesting features of the Wolff's algorithm behavior when applied to the site-bond-correlated Ising model.Our main results were that a stronger correlation diminishes the autocorrelation time but it does not change or affectthe critical dynamic exponent.In this paper, we analyse the Wolff's cluster structure and how it varies with the spatial correlation. The fractal dimensions are determined for several values of the magnetic atoms concentration and spacial correlation, giving an estimative of the critical dynamic exponent.

arXiv:cond-mat/9908151•Aug 10, 1999•0 citations

Percolation properties of the Wolff clusters in planar triangular spin models

P. W. Leung, Christopher L. Henley

We formulate the Wolff algorithm as a site-bond percolation problem, apply it to the ferromagnetic and antiferromagnetic planar triangular spin models, and study the percolation critical behavior using finite-size scaling. In the former case the Wolff algorithm is successful as an accelerating algorithm, whereas in the latter case it is not. We found the percolation temperatures and the cluster exponents for both models. In the antiferromagnetic model, the percolation temperature is higher than the critical temperature of the spin system. The cluster exponents are found to be the same as the random two-dimensional (2D) percolation. In the ferromagnetic model, the percolation temperature agrees with the critical temperature, and the cluster exponents are different from the random 2D percolation, meaning that they are in different universal classes. For the ferromagnetic model we discuss the mechanism of the cluster growth in the regime of the Kosterlitz-Thouless transition. We also note a relation between the dynamic exponent and the percolation exponents.

Physical review. B, Condensed matter•Jan 1, 1991•19 citations

Comparison of cluster algorithms for the bond-diluted Ising model

Arnold H. Kole, G. T. Barkema, Lars Fritz

Monte Carlo cluster algorithms are popular for their efficiency in studying the Ising model near its critical temperature. We might expect that this efficiency extends to the bond-diluted Ising model. We show, however, that this is not always the case by comparing how the correlation times τ_{w} and τ_{sw} of the Wolff and Swendsen-Wang cluster algorithms scale as a function of the system size L when applied to the two-dimensional bond-diluted Ising model. We demonstrate that the Wolff algorithm suffers from a much longer correlation time than in the pure Ising model, caused by isolated (groups of) spins which are infrequently visited by the algorithm. With a simple argument we prove that these cause the correlation time τ_{w} to be bounded from below by L^{z_{w}} with a dynamical exponent z_{w}=γ/ν≈1.75 for a bond concentration p<1. Furthermore, we numerically show that this lower bound is actually taken for several values of p in the range 0.5<p<1. Moreover, we show that the Swendsen-Wang algorithm does not suffer from the same problem. Consequently, it has a much shorter correlation time, shorter than in the pure Ising model even. Numerically at p=0.6, we find that its dynamical exponent is z_{sw}=0.09(4).

arXiv:2107.08534•Physical review. E•Jan 31, 2022•4 citations
The problem of applying Wolff's cluster algorithm to anisotropic classical spin models is resolved by modifying a part of the Wolff algorithm. To test the effectiveness of our modified algorithm, the spin--van der Waals model is investigated in detail. Our estimate of the dynamical exponent of the model is z=0.19\ifmmode\pm\else\textpm\fi{}0.04.
We calculate the dynamic critical exponent for the Niedermayer algorithm applied to the two-dimensional Ising and XY models, for various values of the free parameter E 0 . For E 0 = − 1 we regain the Metropolis algorithm and for E 0 = 1 we regain the Wolff algorithm. For − 1 < E 0 < 1, we show that the mean size of the clusters of (possibly) turned spins initially grows with the linear size of the lattice, L , but eventually saturates at a given lattice size , which depends on E 0 . For , the Niedermayer algorithm is equivalent to the Metropolis one, i.e., they have the same dynamic exponent. For E 0 > 1, the autocorrelation time is always greater than for E 0 = 1 (Wolff) and, more important, it also grows faster than a power of L . Therefore, we show that the best choice of cluster algorithm is the Wolff one, when comparing against the Niedermayer generalization. We also obtain the dynamic behavior of the Wolff algorithm: although not conclusively, we propose a scaling law for the dependence of the autocorrelation time on L .
Recently we reported some interesting features of the Wolff algorithm behaviour when applied to the site-bond-correlated Ising model. Our main results were that a stronger correlation diminishes the autocorrelation time but it does not change or affect the critical dynamic exponent. In this work, we analyse the Wolff cluster structure and how it varies with the spatial correlation. The fractal dimensions are determined for several values of the magnetic atom concentration and spatial correlation, giving an estimation of the Wolff critical dynamic exponent.
Recently we reported some interesting features of the Wolff's algorithm behavior when applied to the site-bond-correlated Ising model.Our main results were that a stronger correlation diminishes the autocorrelation time but it does not change or affectthe critical dynamic exponent.In this paper, we analyse the Wolff's cluster structure and how it varies with the spatial correlation. The fractal dimensions are determined for several values of the magnetic atoms concentration and spacial correlation, giving an estimative of the critical dynamic exponent.
We formulate the Wolff algorithm as a site-bond percolation problem, apply it to the ferromagnetic and antiferromagnetic planar triangular spin models, and study the percolation critical behavior using finite-size scaling. In the former case the Wolff algorithm is successful as an accelerating algorithm, whereas in the latter case it is not. We found the percolation temperatures and the cluster exponents for both models. In the antiferromagnetic model, the percolation temperature is higher than the critical temperature of the spin system. The cluster exponents are found to be the same as the random two-dimensional (2D) percolation. In the ferromagnetic model, the percolation temperature agrees with the critical temperature, and the cluster exponents are different from the random 2D percolation, meaning that they are in different universal classes. For the ferromagnetic model we discuss the mechanism of the cluster growth in the regime of the Kosterlitz-Thouless transition. We also note a relation between the dynamic exponent and the percolation exponents.
Monte Carlo cluster algorithms are popular for their efficiency in studying the Ising model near its critical temperature. We might expect that this efficiency extends to the bond-diluted Ising model. We show, however, that this is not always the case by comparing how the correlation times τ_{w} and τ_{sw} of the Wolff and Swendsen-Wang cluster algorithms scale as a function of the system size L when applied to the two-dimensional bond-diluted Ising model. We demonstrate that the Wolff algorithm suffers from a much longer correlation time than in the pure Ising model, caused by isolated (groups of) spins which are infrequently visited by the algorithm. With a simple argument we prove that these cause the correlation time τ_{w} to be bounded from below by L^{z_{w}} with a dynamical exponent z_{w}=γ/ν≈1.75 for a bond concentration p<1. Furthermore, we numerically show that this lower bound is actually taken for several values of p in the range 0.5<p<1. Moreover, we show that the Swendsen-Wang algorithm does not suffer from the same problem. Consequently, it has a much shorter correlation time, shorter than in the pure Ising model even. Numerically at p=0.6, we find that its dynamical exponent is z_{sw}=0.09(4).