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This paper uses the generator approach of Stein's method to analyze the gap between steady-state distributions of Markov chains and diffusion processes. Until now, the standard way to invoke Stein's method for this problem was to use the…

Probability · Mathematics 2022-02-15 Anton Braverman

The scaling behaviour of the diffraction intensity near the origin is investigated for (partially) ordered systems, with an emphasis on illustrative, rigorous results. This is an established method to detect and quantify the fluctuation…

Metric Geometry · Mathematics 2021-06-15 Michael Baake , Uwe Grimm

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

In this paper we are concerned with hitting times of a family of density-dependent Markov chains. A moderate deviation principle of the hitting time is given. The proof of the main theorem relies heavily on moderate deviations of…

Probability · Mathematics 2022-06-15 Yuheng He , Xiaofeng Xue

Random metastability occurs when an externally forced or noisy system possesses more than one state of apparent equilibrium. This work investigates fluctuations in a class of random dynamical systems, arising from randomly perturbing a…

Dynamical Systems · Mathematics 2025-05-30 Cecilia González-Tokman , Joshua Peters

The article presents a novel variational calculus to analyze the stability and the propagation of chaos properties of nonlinear and interacting diffusions. This differential methodology combines gradient flow estimates with backward…

Probability · Mathematics 2019-01-30 Marc Arnaudon , Pierre Del Moral

The paper studies an improved estimate for the rate of convergence for nonlinear homogeneous discrete-time Markov chains. These processes are nonlinear in terms of the distribution law. Hence, the transition kernels are dependent on the…

Probability · Mathematics 2021-05-21 Aleksandr Shchegolev

This paper aims to provide a simple modelling of speculative bubbles and derive some quantitative properties of its dynamical evolution. Starting from a description of individual speculative behaviours, we build and study a second order…

Probability · Mathematics 2013-09-25 Sébastien Gadat , Laurent Miclo , Fabien Panloup

We propose a discrete time discrete space Markov chain approximation with a Brownian bridge correction for computing curvilinear boundary crossing probabilities of a general diffusion process on a finite time interval. For broad classes of…

Probability · Mathematics 2021-12-13 Vincent Liang , Konstantin Borovkov

In this thesis we deal with the specific collective phenomena in condensed matter - striped-structures formation. Such structures are observed in different branches of condensed matter physics, like surface physics or physics of…

Strongly Correlated Electrons · Physics 2007-05-23 Volodymyr Derzhko

We present linear stability analysis for a simple model of particle-laden pipe flow. The model consists of a continuum approximation for the particles two-way coupled to the fluid velocity field via Stokes drag (Saffman 1962). We extend…

Fluid Dynamics · Physics 2019-05-22 Anthony Rouquier , Alban Potherat , Chris Pringle

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

We consider a diffusion given by a small noise perturbation of a dynamical system driven by a potential function with a finite number of local minima. The classical results of Freidlin and Wentzell show that the time this diffusion spends…

Probability · Mathematics 2021-01-20 Thomas G. Kurtz , Jason Swanson

Physical notions of stochastic resonance for potential diffusions in periodically changing double-well potentials such as the spectral power amplification have proved to be defective. They are not robust for the passage to their effective…

Probability · Mathematics 2007-05-23 Samuel Herrmann , Peter Imkeller

We consider processes which are functions of finite-state Markov chains. It is well known that such processes are rarely Markov. However, such processes are often regular in the following sense: the distant past values of the process have…

Probability · Mathematics 2021-01-05 Steven Berghout , Evgeny Verbitskiy

The large deviations at Level 2.5 are applied to Markov processes with absorbing states in order to obtain the explicit extinction rate of metastable quasi-stationary states in terms of their empirical time-averaged density and of their…

Statistical Mechanics · Physics 2022-01-13 Cecile Monthus

Diffusion is a fundamental phenomenon that occurs ubiquitously in nature and remains the subject of continuous research interest. Understanding diffusion is a key to understanding leaving systems. In this Chapter, I discuss diffusion of…

Soft Condensed Matter · Physics 2018-10-15 Svyatoslav Kondrat

In this paper we study an asymptotic expansion for the distribution of a random motion of a particle driven by a Markov process in diffusion approximation. We show that the singularly perturbed equation of a Markovian random motion can be…

Probability · Mathematics 2012-03-21 A. Pogorui

The stability properties of matrix-valued Riccati diffusions are investigated. The matrix-valued Riccati diffusion processes considered in this work are of interest in their own right, as a rather prototypical model of a matrix-valued…

Probability · Mathematics 2020-02-04 Adrian N. Bishop , Pierre Del Moral

We consider a hidden Markov model, where the signal process, given by a diffusion, is only indirectly observed through some noisy measurements. The article develops a variational method for approximating the hidden states of the signal…

Optimization and Control · Mathematics 2016-10-26 Tobias Sutter , Arnab Ganguly , Heinz Koeppl