Efficient Sampling from High-Entropy Initializations for Mean-Field Potts and Random-Cluster Models

High-entropy initializations, such as product measures, can overcome the slow mixing of Markov chains in multimodal energy landscapes by allowing the dynamics to quickly escape from saddle points separating dominant modes.