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Related papers: Random-Cluster Dynamics in $\mathbb{Z}^2$

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Exponential random graph theory is the complex network analog of the canonical ensemble theory from statistical physics. While it has been particularly successful in modeling networks with specified degree distributions, a naive model of a…

Disordered Systems and Neural Networks · Physics 2016-01-12 Juyong Park , Soon-Hyung Yook

In a series of recent works, Boyd, Diaconis, and their co-authors have introduced a semidefinite programming approach for computing the fastest mixing Markov chain on a graph of allowed transitions, given a target stationary distribution.…

Probability · Mathematics 2011-09-07 S. Roch

This article studies the planar Potts model and its random-cluster representation. We show that the phase transition of the nearest-neighbor ferromagnetic $q$-state Potts model on $\mathbb Z^2$ is continuous for $q\in\{2,3,4\}$, in the…

Probability · Mathematics 2016-11-03 Hugo Duminil-Copin , Vladas Sidoravicius , Vincent Tassion

The exponential family of random graphs is among the most widely-studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice gas model with a finite Banach space norm. The system may then…

Mathematical Physics · Physics 2012-05-04 Mei Yin

Motivated by the `subgraphs world' view of the ferromagnetic Ising model, we develop a general approach to studying mixing times of Glauber dynamics based on subset expansion expressions for a class of graph polynomials. With a canonical…

Combinatorics · Mathematics 2015-10-29 Magnus Bordewich , Ross J. Kang

We study the effect of boundary conditions on the relaxation time of the Glauber dynamics for the hard-core model on the tree. The hard-core model is defined on the set of independent sets weighted by a parameter $\lambda$, called the…

Probability · Mathematics 2010-07-15 Ricardo Restrepo , Daniel Stefankovic , Juan C. Vera , Eric Vigoda , Linji Yang

Clustering mixtures of Gaussian distributions is a fundamental and challenging problem that is ubiquitous in various high-dimensional data processing tasks. While state-of-the-art work on learning Gaussian mixture models has focused…

Machine Learning · Computer Science 2018-03-05 Dan Kushnir , Shirin Jalali , Iraj Saniee

We show that atoms in tilted optical superlattices provide a platform for exploring coupled spin chains of forms that are not present in other systems. In particular, using a period-2 superlattice in 1D, we show that coupled Ising spin…

We consider coupled slow-fast stochastic processes, where the averaged slow motion is given by a two-dimensional Hamiltonian system with multiple critical points. On a proper time scale, the evolution of the first integral converges to a…

Probability · Mathematics 2024-08-07 Shuo Yan

Consider the complete graph on $n$ vertices. To each vertex assign an Ising spin that can take the values $-1$ or $+1$. Each spin $i \in [n]=\{1,2,\dots, n\}$ interacts with a magnetic field $h \in [0,\infty)$, while each pair of spins $i,j…

Probability · Mathematics 2022-04-28 Anton Bovier , Frank den Hollander , Saeda Marello

We study the Glauber dynamics of Ising spin models with random bonds, on finitely connected random graphs. We generalize a recent dynamical replica theory with which to predict the evolution of the joint spin-field distribution, to include…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. Mozeika , A. C. C. Coolen

We show polylogarithmic mixing time bounds for the alternating-scan sampler for positively weighted restricted Boltzmann machines. This is done via analysing the same chain and the Glauber dynamics for ferromagnetic two-spin systems, where…

Data Structures and Algorithms · Computer Science 2026-05-26 Weiming Feng , Heng Guo , Minji Yang

Glauber dynamics of a bond-diluted Ising model on a Bethe lattice (a random graph with fixed connectivity) is investigated by an approximate theory which provides exact results for equilibrium properties. The time-dependent solutions of the…

Statistical Mechanics · Physics 2015-05-18 Hiroki Ohta

We studied the critical behavior of the $J_{1}-J_{2}$ spin-{1/2} Ising model in the square lattice by considering $J_{1}$ fixed and $J_{2}$ as random interactions following discrete and continuous probability distribution functions. The…

Statistical Mechanics · Physics 2021-12-23 Octavio D. Rodriguez Salmon , Minos A. Neto , Thiago Lobo , Francisco Dinola Neto

Random walks on expanders play a crucial role in Markov Chain Monte Carlo algorithms, derandomization, graph theory, and distributed computing. A desirable property is that they are rapidly mixing, which is equivalent to having a spectral…

Probability · Mathematics 2024-12-18 Sam Olesker-Taylor , Thomas Sauerwald , John Sylvester

Sufficiently strong inter-site interactions in extended-Hubbard and XXZ spin models result in dynamically-bound clusters at neighboring sites. We show that the dynamics of these clusters in two-dimensional lattices is remarkably different…

Quantum Gases · Physics 2021-04-28 Wei-Han Li , Arya Dhar , Xiaolong Deng , Luis Santos

The singular subspaces perturbation theory is of fundamental importance in probability and statistics. It has various applications across different fields. We consider two arbitrary matrices where one is a leave-one-column-out submatrix of…

Statistics Theory · Mathematics 2024-01-17 Anderson Y. Zhang , Harrison H. Zhou

In this paper we investigate the relationship between the mixing times of the Glauber dynamics of a statistical mechanical system with its thermodynamic equilibrium structure. For this we consider the mean-field Blume-Capel model, one of…

Probability · Mathematics 2015-05-27 Yevgeniy Kovchegov , Peter T. Otto , Mathew Titus

We establish and generalise several bounds for various random walk quantities including the mixing time and the maximum hitting time. Unlike previous analyses, our derivations are based on rather intuitive notions of local expansion…

Probability · Mathematics 2019-03-05 Thomas Sauerwald , Luca Zanetti

Glauber dynamics is a powerful tool to generate randomized, approximate solutions to combinatorially difficult problems. Applications include Markov Chain Monte Carlo (MCMC) simulation and distributed scheduling for wireless networks. In…

Probability · Mathematics 2010-04-06 Mathieu Leconte , Jian Ni , R. Srikant