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Cutoff for the Swendsen-Wang dynamics on the complete graph

Published 28 Jul 2025 in math.PR | (2507.20482v1)

Abstract: We study the speed of convergence of the Swendsen-Wang (SW) dynamics for the qq-state ferromagnetic Potts model on the nn-vertex complete graph, known as the mean-field model. The SW dynamics was introduced as an attractive alternative to the local Glauber dynamics, often offering faster convergence rates to stationarity in a variety of settings. A series of works have characterized the asymptotic behavior of the speed of convergence of the mean-field SW dynamics for all q2q \ge 2 and all values of the inverse temperature parameter $\beta > 0$. In particular, it is known that when $\beta > q$ the mixing time of the SW dynamics is Θ(logn)\Theta(\log n). We strengthen this result by showing that for all $\beta > q$, there exists a constant $c(\beta,q) > 0$ such that the mixing time of the SW dynamics is c(β,q)logn+Θ(1)c(\beta,q) \log n + \Theta(1). This implies that the mean-field SW dynamics exhibits the cutoff phenomenon in this temperature regime, demonstrating that this Markov chain undergoes a sharp transition from ''far from stationarity'' to ''well-mixed'' within a narrow Θ(1)\Theta(1) time window. The presence of cutoff is algorithmically significant, as simulating the chain for fewer steps than its mixing time could lead to highly biased samples.

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