We study the performance of Markov chains for the q-state ferromagnetic Potts model on random regular graphs. While the cases of the grid and the complete graph are by now well …
A common obstruction to efficient sampling from high-dimensional distributions with Markov chains is the multimodality of the target distribution because they may get trapped far from …
A Blanca, P Caputo, D Parisi, A Sinclair… - Proceedings of the 53rd …, 2021 - dl.acm.org
We study the mixing time of the Swendsen-Wang dynamics for the ferromagnetic Ising and Potts models on the integer lattice ℤ d. This dynamics is a widely used Markov chain that …
A Blanca, R Gheissari - 2023 IEEE 64th Annual Symposium on …, 2023 - ieeexplore.ieee.org
Sampling from the q-state ferromagnetic Potts model is a fundamental question in statistical physics, probability theory, and theoretical computer science. On general graphs, this …
We study the q‐state ferromagnetic Potts model on the n‐vertex complete graph known as the mean‐field (Curie‐Weiss) model. We analyze the Swendsen‐Wang algorithm which is a …
FR Nardi, A Zocca - Stochastic Processes and their Applications, 2019 - Elsevier
We consider the ferromagnetic q-state Potts model with zero external field in a finite volume and assume that its stochastic evolution is described by a Glauber-type dynamics …
AJ Izenman - Journal of the American Statistical Association, 2021 - Taylor & Francis
Discrete Markov random fields are undirected graphical models in which the nodes of a graph are discrete random variables with values usually represented by colors. Typically …
A Blanca, R Gheissari - Communications in Mathematical Physics, 2021 - Springer
We establish rapid mixing of the random-cluster Glauber dynamics on random\varDelta Δ- regular graphs for all q ≥ 1 q≥ 1 and p< p_u (q,\varDelta) p< pu (q, Δ), where the threshold …
A Blanca, A Sinclair, X Zhang - Combinatorics, Probability and …, 2022 - cambridge.org
The random-cluster model is a unifying framework for studying random graphs, spin systems and electrical networks that plays a fundamental role in designing efficient Markov Chain …