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Related papers: Path Coupling and Aggregate Path Coupling

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In this paper, we present a novel extension to the classical path coupling method to statistical mechanical models which we refer to as aggregate path coupling. In conjunction with large deviations estimates, we use this aggregate path…

Probability · Mathematics 2015-08-13 Yevgeniy Kovchegov , Peter T. Otto

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

In this paper, we derive the large deviations principle for the Potts model on the complete bipartite graph $K_{n,n}$ as $n$ increases to infinity. Next, for the Potts model on $K_{n,n}$, we provide an extension of the method of aggregate…

Probability · Mathematics 2017-04-05 Jose C. Hernandez , Yevgeniy Kovchegov , Peter T. Otto

The Curie-Weiss model is used to study phase transitions in statistical mechanics and has been the object of rigorous analysis in mathematical physics. We analyse the problem of reconstructing the probability measure of a multi-group…

Probability · Mathematics 2025-05-29 Miguel Ballesteros , Ramsés H. Mena , Arno Siri-Jégousse , Gabor Toth

We use coupling to study the time taken until the distribution of a statistic on a Markov chain is close to its stationary distribution. Coupling is a common technique used to obtain upper bounds on mixing times of Markov chains, and we…

Probability · Mathematics 2019-10-09 Graham White

We survey existing techniques to bound the mixing time of Markov chains. The mixing time is related to a geometric parameter called conductance which is a measure of edge-expansion. Bounds on conductance are typically obtained by a…

Data Structures and Algorithms · Computer Science 2016-03-07 Venkatesan Guruswami

Coupling is a widely used technique in the theoretical study of interacting stochastic processes. In this paper I present an example demonstrating its usefulness also in the efficient computer simulation of such processes. I first describe…

Populations and Evolution · Quantitative Biology 2012-04-16 Ilmari Karonen

The Curie-Weiss model, originally used to study phase transitions in statistical mechanics, has been adapted to model phenomena in social sciences where many agents interact with each other. Reconstructing the probability measure of a…

Statistics Theory · Mathematics 2025-07-24 Miguel Ballesteros , Ivan Naumkin , Gabor Toth

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

The hardcore model is a fundamental probabilistic model extensively studied in statistical physics, probability theory, and computer science. For graphs of maximum degree $\Delta$, a well-known computational phase transition occurs at the…

Data Structures and Algorithms · Computer Science 2025-11-13 Xiaoyu Chen , Zejia Chen , Zongchen Chen , Yitong Yin , Xinyuan Zhang

We show that the Potts model on a graph can be approximated by a sequence of independent and identically distributed spins in terms of Wasserstein distance at high temperatures. We prove a similar result for the Curie--Weiss--Potts model on…

Probability · Mathematics 2026-01-14 Roxanne He , Jackie Lok

In this review, a model (the Random Coupling Model) that gives a statistical description of the coupling of radiation into and out of large enclosures through localized and/or distributed channels is presented. The Random Coupling Model…

Chaotic Dynamics · Physics 2013-03-27 Gabriele Gradoni , Jen-Hao Yeh , Bo Xiao , Thomas M. Antonsen , Steven M. Anlage , Edward Ott

Sampling from Gibbs distribution is a central problem in computer science as well as in statistical physics. In this work we focus on the k-colouring model} and the hard-core model with fugacity \lambda when the underlying graph is an…

Discrete Mathematics · Computer Science 2017-01-24 Charilaos Efthymiou

The Metropolis-Hastings method is often used to construct a Markov chain with a given $\pi$ as its stationary distribution. The method works even if $\pi$ is known only up to an intractable constant of proportionality. Polynomial time…

Statistics Theory · Mathematics 2019-09-27 David Pollard , Dana Yang

Bifurcations in a system of coupled maps are investigated. Using symbolic dynamics it is proven that for coupled shift maps the well known space--time--mixing attractor becomes unstable at a critical coupling strength in favour of a…

chao-dyn · Physics 2016-08-14 Wolfram Just

In this paper, several fundamental facts, especially the existence and uniqueness of an absolutely continuous ergodic measure with an exponential mixing rate, are derived for smooth expanding circle maps. Although the results are classical,…

Dynamical Systems · Mathematics 2013-03-12 Henri Sulku

In this work we introduce a mixture of GPs to address the data association problem, i.e. to label a group of observations according to the sources that generated them. Unlike several previously proposed GP mixtures, the novel mixture has…

Machine Learning · Statistics 2011-08-18 Miguel Lázaro-Gredilla , Steven Van Vaerenbergh , Neil Lawrence

A model Hamiltonian describing a two-level system with a crossing plus a pairing force is investigated using technique of large-amplitude collective motion. The collective path, which is determined by the decoupling conditions, is found to…

Nuclear Theory · Physics 2009-10-30 Takashi Nakatsukasa , Niels R. Walet

We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models…

Machine Learning · Computer Science 2016-11-23 Lars Mescheder , Sebastian Nowozin , Andreas Geiger

We study random walks on dynamically evolving graphs, where the environment is given by a time-dependent subset of the edges of an underlying graph. Concretely, following the recently introduced framework of Lelli and Stauffer, we consider…

Probability · Mathematics 2026-05-08 Andreas Galanis , Leslie Ann Goldberg , Xandru Mifsud
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