Random Cluster Model on Regular Graphs

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=OeOObs1I2xo


Duration: 51:51
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6

Péter Csikvári (Eötvös Loránd University)
https://simons.berkeley.edu/node/22587
Graph Limits, Nonparametric Models, and Estimation

In this talk we study the random cluster model on essentially large girth and random regular graphs. We give explicit formula for the limiting free entropy of the random cluster model. Our result extends the work of Dembo, Montanari, Sly and Sun for the Potts model, and we prove a conjecture of Helmuth, Jenssen and Perkins about the phase transition of the random cluster model. This is joint work with Ferenc Bencs and Márton Borbényi.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Graph Limits Nonparametric Models and Estimation
Péter Csikvári