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We study a large class of reversible Markov chains with discrete state space and transition matrix $P_N$. We define the notion of a set of {\it metastable points} as a subset of the state space $\G_N$ such that (i) this set is reached from…

Probability · Mathematics 2007-05-23 A. Bovier , M. Eckhoff , V. Gayrard , M. Klein

In this paper we consider Markov chains with transition rates that depend on a small parameter $\varepsilon$. Under a mild assumption on the asymptotics of these transition rates, we describe the behavior of the chain at various…

Probability · Mathematics 2017-04-26 Mark Freidlin , Leonid Koralov

Metastability is a physical phenomenon ubiquitous in first order phase transitions. A fruitful mathematical way to approach this phenomenon is the study of rare transitions Markov chains. For Metropolis chains associated with Statistical…

Probability · Mathematics 2015-09-30 Emilio Cirillo , Francesca Nardi , Julien Sohier

We consider continuous-space, discrete-time Markov chains on $\mathbb{R}^d$, that admit a finite number $N$ of metastable states. Our main motivation for investigating these processes is to analyse random Poincar\'e maps, which describe…

Probability · Mathematics 2025-08-19 Nils Berglund

We consider a simple but important class of metastable discrete time Markov chains, which we call perturbed Markov chains. Basically, we assume that the transition matrices depend on a parameter $\varepsilon$, and converge as $\varepsilon$.…

Probability · Mathematics 2014-12-23 Volker Betz , Stéphane Le Roux

We propose a new definition of metastability of Markov processes on countable state spaces. We obtain sufficient conditions for a sequence of processes to be metastable. In the reversible case these conditions are expressed in terms of the…

Probability · Mathematics 2015-05-14 Johel Beltrán , Claudio Landim

A definition of metastable states applicable to arbitrary finite state Markov processes satisfying detailed balance is discussed. In particular, we identify a crucial condition that distinguishes genuine metastable states from other types…

Statistical Mechanics · Physics 2016-08-31 Francois Leyvraz , Hernan Larralde , David P. Sanders

We consider continuous-time Markov chains which display a family of wells at the same depth. We provide sufficient conditions which entail the convergence of the finite-dimensional distributions of the order parameter to the ones of a…

Probability · Mathematics 2019-10-03 Claudio Landim , Michail Loulakis , Mustapha Mourragui

A perturbation framework is developed to analyze metastable behavior in stochastic processes with random internal and external states. The process is assumed to be under weak noise conditions, and the case where the deterministic limit is…

Analysis of PDEs · Mathematics 2013-09-23 Jay Newby , Jon Chapman

In this paper, we consider semi-Markov processes whose transition times and transition probabilities depend on a small parameter $\varepsilon$. Understanding the asymptotic behavior of such processes is needed in order to study the…

Probability · Mathematics 2024-11-08 Leonid Koralov , Ishfaaq Mohammed Imtiyas

We establish metastability in the sense of Lebowitz and Penrose under practical and simple hypothesis for (families of) Markov chains on finite configuration space in some asymptotic regime, including the case of configuration space size…

Probability · Mathematics 2017-01-31 Alessandra Bianchi , Alexandre Gaudillière

We consider a random walk with catastrophes which was introduced to model population biology. It is known that this Markov chain gets eventually absorbed at $0$ for all parameter values. Recently, it has been shown that this chain exhibits…

Probability · Mathematics 2019-07-12 Luiz Renato Fontes , Rinaldo B. Schinazi

We review recent results on the metastable behavior of continuous-time Markov chains derived through the characterization of Markov chains as unique solutions of martingale problems.

Probability · Mathematics 2018-07-12 C. Landim

It is known that state-dependent, multi-step Lyapunov bounds lead to greatly simplified verification theorems for stability for large classes of Markov chain models. This is one component of the "fluid model" approach to stability of…

Optimization and Control · Mathematics 2012-05-18 Serdar Yüksel , Sean P. Meyn

We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obtain results on the sensitivity of the stationary distribution and other statistical quantities with respect to perturbations of the…

Probability · Mathematics 2007-05-23 Eilon Solan , Nicolas Vieille

Understanding and predicting how complex systems respond to external perturbations is a central challenge in nonequilibrium statistical physics. Here we consider continuous-time Markov networks, which we subject to perturbations along a…

Statistical Mechanics · Physics 2026-02-25 Robin Bebon , Thomas Speck

We prove the metastable behavior of reversible Markov processes on finite state spaces under minimal conditions on the jump rates. To illustrate the result we deduce the metastable behavior of the Ising model with a small magnetic field at…

Probability · Mathematics 2010-09-22 Johel Beltran , Claudio Landim

We present a formalism to describe slowly decaying systems in the context of finite Markov chains obeying detailed balance. We show that phase space can be partitioned into approximately decoupled regions, in which one may introduce…

Statistical Mechanics · Physics 2007-05-23 Hernan Larralde , Francois Leyvraz , David P. Sanders

We presented in \cite{bl2,bl7} an approach to derive the metastable behavior of continuous-time Markov chains. We assumed in these articles that the Markov chains visit points in the time scale in which it jumps among the metastable sets.…

Probability · Mathematics 2013-05-28 J. Beltrán , C. Landim

We examine two analytical characterisation of the metastable behavior of a Markov chain. The first one expressed in terms of its transition probabilities, and the second one in terms of its large deviations rate functional. Consider a…

Probability · Mathematics 2022-07-07 L. Bertini , D. Gabrielli , C. Landim
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