A comparison of cluster algorithms for the bond-diluted Ising model

Abstract

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 $\tau_w$ and $\tau_{\rm sw}$ 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. These cause the correlation time to scale as $\tau_w \sim L^{z_w}$ with a dynamical exponent $z_w=\gamma / \nu\approx 1.75$ independent of the bond concentration $p$ for $0.5 < p < 1$. 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 $z_{\rm sw} = 0.09(4)$. Lastly, we tested a novel way of determining the dynamical exponent for the Metropolis algorithm and confirmed that it worked properly. With this method we determined that $z_m = 3.337(3)$ at $p = 0.6$.