Metastability of the Potts Ferromagnet on Random Regular Graphs

Author:

Coja-Oghlan Amin,Galanis Andreas,Goldberg Leslie Ann,Ravelomanana Jean Bernoulli,Štefankovič Daniel,Vigoda Eric

Abstract

AbstractWe study the performance of Markov chains for theq-state ferromagnetic Potts model on random regular graphs. While the cases of the grid and the complete graph are by now well-understood, the case of random regular graphs has resisted a detailed analysis and, in fact, even analysing the properties of the Potts distribution has remained elusive. It is conjectured that the performance of Markov chains is dictated by metastability phenomena, i.e., the presence of “phases” (clusters) in the sample space where Markov chains with local update rules, such as the Glauber dynamics, are bound to take exponential time to escape, and therefore cause slow mixing. The phases that are believed to drive these metastability phenomena in the case of the Potts model emerge as local, rather than global, maxima of the so-called Bethe functional, and previous approaches of analysing these phases based on optimisation arguments fall short of the task. Our first contribution is to detail the emergence of the two relevant phases for theq-state Potts model on thed-regular random graph for all integers$$q,d\ge 3$$q,d3, and establish that for an interval of temperatures, delineated by the uniqueness and a broadcasting threshold on thed-regular tree, the two phases coexist (as possible metastable states). The proofs are based on a conceptual connection between spatial properties and the structure of the Potts distribution on the random regular graph, rather than complicated moment calculations. This significantly refines earlier results by Helmuth, Jenssen, and Perkins who had established phase coexistence for a small interval around the so-called ordered-disordered threshold (via different arguments) that applied for largeqand$$d\ge 5$$d5. Based on our new structural understanding of the model, our second contribution is to obtain metastability results for two classical Markov chains for the Potts model. We first complement recent fast mixing results for Glauber dynamics by Blanca and Gheissari below the uniqueness threshold, by showing an exponential lower bound on the mixing time above the uniqueness threshold. Then, we obtain tight results even for the non-local and more elaborate Swendsen–Wang chain, where we establish slow mixing/metastability for the whole interval of temperatures where the chain is conjectured to mix slowly on the random regular graph. The key is to bound the conductance of the chains using a random graph “planting” argument combined with delicate bounds on random-graph percolation.

Funder

Deutsche Forschungsgemeinschaft

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Mathematical Physics,Statistical and Nonlinear Physics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sampling from the Potts model at low temperatures via Swendsen–Wang dynamics;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

2. The Swendsen–Wang dynamics on trees;Random Structures & Algorithms;2022-11-08

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