A comparison of cluster algorithms for the bond-diluted Ising model
Arnold H. Kole, Gerard T. Barkema, Lars Fritz

TL;DR
This paper compares the efficiency of Wolff and Swendsen-Wang cluster algorithms in the bond-diluted 2D Ising model, revealing that Wolff's correlation time is significantly longer due to isolated spins, while Swendsen-Wang remains efficient.
Contribution
It provides a detailed analysis of how bond dilution affects the dynamical scaling of cluster algorithms, highlighting the limitations of Wolff's algorithm in disordered systems.
Findings
Wolff algorithm's correlation time scales with system size as L^{z_w} with z_w≈1.75 for p<1.
Swendsen-Wang algorithm maintains a much shorter correlation time, with z_sw≈0.09 at p=0.6.
Wolff algorithm's inefficiency is caused by isolated spins rarely visited, increasing correlation times.
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 and of the Wolff and Swendsen-Wang cluster algorithms scale as a function of the system size 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 to be bounded from below by with a dynamical exponent for a bond concentration . Furthermore, we…
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