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Swendsen-Wang Dynamics


Swendsen-Wang dynamics is a Markov chain for sampling the ferromagnetic Potts model using cluster updates (Swendsen and Wang 1987). For a q-state configuration at inverse temperature beta>0, independently retain each graph edge whose endpoints have the same color with probability 1-e^(-beta), and delete every other graph edge. Give each connected component of the retained graph an independent uniformly chosen color from the q colors. This produces the next configuration.

For fixed integers q>=2 and Delta>=3, Blanca et al. (2026) prove that on a uniformly random Delta-regular graph with n vertices, the chain mixes in O(lnn) cluster updates with high probability for each fixed 0<beta<beta_u(q,T_Delta). Here beta_u(q,T_Delta) is the uniqueness threshold on the infinite Delta-regular tree. The result uses a dichotomy discovered with ChatGPT assistance.


See also

Glauber Dynamics, Markov Chain, Potts Model

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References

Blanca, A.; Gheissari, R.; Park, H.; and Zhang, X. "Rapid Mixing of Potts Glauber Dynamics Throughout Uniqueness." 30 Oct 2026. https://arxiv.org/abs/2610.42059v1.Swendsen, R. H. and Wang, J.-S. "Nonuniversal Critical Dynamics in Monte Carlo Simulations." Phys. Rev. Lett. 58, 86-88, 1987. https://doi.org/10.1103/PhysRevLett.58.86.

Cite this as:

Weisstein, Eric W. "Swendsen-Wang Dynamics." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/Swendsen-WangDynamics.html

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