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We formally introduce and study locally-balanced Markov jump processes (LBMJPs) defined on a general state space. These continuous-time stochastic processes with a user-specified limiting distribution are designed for sampling in settings…

Probability · Mathematics 2025-04-21 Samuel Livingstone , Giorgos Vasdekis , Giacomo Zanella

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 general method to derive the metastable behavior of weakly mixing Markov chains. This approach is based on properties of the resolvent equations and can be applied to metastable dynamics which do not satisfy the mixing…

Probability · Mathematics 2024-06-21 Claudio Landim , Diego Marcondes , Insuk Seo

We study a Markov process with two components: the first component evolves according to one of finitely many underlying Markovian dynamics, with a choice of dynamics that changes at the jump times of the second component. The second…

Probability · Mathematics 2015-04-14 Bertrand Cloez , Martin Hairer

For a system in contact with several reservoirs $r$ at different inverse-temperatures $\beta_r$, we describe how the Markov jump dynamics with the generalized detailed balance condition can be analyzed via a statistical physics approach of…

Statistical Mechanics · Physics 2021-05-12 Cecile Monthus

In this article, we prove the Eyring-Kramers formula for non-reversible metastable diffusion processes that have a Gibbs invariant measure. Our result indicates that non-reversible processes exhibit faster metastable transitions between…

Probability · Mathematics 2021-12-20 Jungkyoung Lee , Insuk Seo

We study rare events in the extreme value statistics of stochastic symmetric jump processes with power tails in the distributions of the jumps, using the big-jump principle. The principle states that in the presence of stochastic processes…

Statistical Mechanics · Physics 2024-09-04 Alberto Bassanoni , Alessandro Vezzani , Raffaella Burioni

Maximum entropy (maxEnt) inference of state probabilities using state-dependent constraints is popular in the study of complex systems. In stochastic dynamical systems, the effect of state space topology and path-dependent constraints on…

Statistical Mechanics · Physics 2015-10-28 Purushottam D. Dixit

We consider an irreducible pure jump Markov process with rates Q=(q(x,y)) on \Lambda\cup\{0\} with \Lambda countable and 0 an absorbing state. A quasi-stationary distribution (qsd) is a probability measure \nu on \Lambda that satisfies:…

Probability · Mathematics 2011-11-09 Pablo A. Ferrari , Nevena Maric

In this paper we first provide several conditional limit theorems for L\'evy processes with negative drift and regularly varying tail. Then we apply them to study the asymptotic behavior of expectations of some exponential functionals of…

Probability · Mathematics 2020-05-29 Wei Xu

We derive precursors of extreme dissipation events in a turbulent channel flow. Using a recently developed method that combines dynamics and statistics for the underlying attractor, we extract a characteristic state that precedes…

Fluid Dynamics · Physics 2019-06-10 Patrick J. Blonigan , Mohammad Farazmand , Themistoklis P. Sapsis

We consider the class of Piecewise Deterministic Markov Processes (PDMP), whose state space is $\R\_{+}^{*}$, that possess an increasing deterministic motion and that shrink deterministically when they jump. Well known examples for this…

Statistics Theory · Mathematics 2015-03-12 Nathalie Krell

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 investigate nonequilibrium steady-state dynamics in both continuous- and discrete-state stochastic processes. Our analysis focuses on planar diffusion dynamics and their coarse-grained approximations by discrete-state Markov chains.…

Statistical Mechanics · Physics 2026-05-12 Ramón Nartallo-Kaluarachchi , Renaud Lambiotte , Alain Goriely

A variety of enhanced statistical and numerical methods are now routinely used to extract comprehensible and relevant thermodynamic information from the vast amount of complex, high-dimensional data obtained from intensive molecular…

Soft Condensed Matter · Physics 2020-10-14 Francois Sicard , Vladimir Koskin , Alessia Annibale , Edina Rosta

We consider a Markov process $X$, which is the solution of a stochastic differential equation driven by a L\'{e}vy process $Z$ and an independent Wiener process $W$. Under some regularity conditions, including non-degeneracy of the…

Probability · Mathematics 2014-07-03 José E. Figueroa-López , Yankeng Luo , Cheng Ouyang

The problem of noise-induced transitions is often associated with Hendrik Kramers due to his seminal paper of 1940, where an archetypal example - one-dimensional potential system subject to linear damping and weak white noise - was…

Statistical Mechanics · Physics 2023-01-30 Stanislav M. Soskin , Tetiana L. Linnik

Markov processes with stochastic resetting towards the origin generically converge towards non-equilibrium steady-states. Long dynamical trajectories can be thus analyzed via the large deviations at Level 2.5 for the joint probability of…

Statistical Mechanics · Physics 2021-05-07 Cecile Monthus

In this paper, we derive a precise estimate for the mean extinction time of the contact process with a fixed infection rate on a star graph with $N$ leaves. Specifically, we determine not only the exponential main factor but also the exact…

Probability · Mathematics 2026-02-05 Younghun Jo

In this paper, we study McKean-Vlasov SDE living in $\mathbb{R}^d$ in the reversible case without assuming any type of convexity assumptions for confinement or interaction potentials. Kramers' type law for the exit-time from a domain of…

Probability · Mathematics 2023-11-01 Ashot Aleksian , Julian Tugaut
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