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Related papers: Ergodic theory for SDEs with extrinsic memory

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We provide sign information for the top Lyapunov exponent for a stochastic differential equation driven by fractional Brownian motion. To this aim we analyze the stochastic dynamical system generated by such an equation, obtain a random…

Probability · Mathematics 2026-03-24 Alexandra Blessing Neamţu , Mazyar Ghani Varzaneh

We investigate synchronization by noise for stochastic differential equations (SDEs) driven by a fractional Brownian motion (fbm) with Hurst index $H\in(0,1)$. Provided that the SDE has a negative top Lyapunov exponent, we show that a weak…

Probability · Mathematics 2026-03-16 Alexandra Blessing , Mazyar Ghani Varzaneh

In this paper, we establish existence and uniqueness of strong solutions for a stochastic differential equation driven by an additive noise given by the sum of two correlated fractional Brownian sheets with different Hurst parameters. Our…

Probability · Mathematics 2026-03-11 Rachid Belfadli , Youssef Ouknine , Ercan Sönmez

We present a concise, but systematic, review of the ergodicity issue in strongly correlated systems. After giving a brief historical overview, we analyze the issue within the Green's function formalism by means of the equations of motion…

Strongly Correlated Electrons · Physics 2007-07-27 Adolfo Avella , Ferdinando Mancini , Evgeny Plekhanov

We establish a general criterion which ensures exponential mixing of parabolic Stochastic Partial Differential Equations (SPDE) driven by a non additive noise which is white in time and smooth in space. We apply this criterion on two…

Analysis of PDEs · Mathematics 2007-05-23 Cyril Odasso

We obtain a generalisation of the Stroock-Varadhan support theorem for a large class of systems of subcritical singular stochastic PDEs driven by a noise that is either white or approximately self-similar. The main problem that we face is…

Probability · Mathematics 2021-12-07 Martin Hairer , Philipp Schönbauer

In this paper we study ergodic backward stochastic differential equations (EBSDEs) dropping the strong dissipativity assumption needed in the previous work. In other words we do not need to require the uniform exponential decay of the…

Probability · Mathematics 2010-04-12 Arnaud Debussche , Ying Hu , Gianmario Tessitore

We study a new class of ergodic backward stochastic differential equations (EBSDEs for short) which is linked with semi-linear Neumann type boundary value problems related to ergodic phenomenas. The particularity of these problems is that…

Probability · Mathematics 2010-02-11 Adrien Richou

We provide deterministic controllability conditions that imply exponential mixing properties for randomly forced constrained dynamical systems with possibly unbounded state space. As an application, new ergodicity results are obtained for…

Optimization and Control · Mathematics 2025-11-07 Laurent Mertz , Vahagn Nersesyan , Manuel Rissel

This paper is devoted to the study of a stochastic process obtained by random switching between a finite collection of vector fields. Such processes have recently been the focus of much attention in the case where the switching times are…

Probability · Mathematics 2025-10-01 Tobias Hurth , Edouard Strickler

The concept of weak ergodicity breaking is defined and studied in the context of deterministic dynamics. We show that weak ergodicity breaking describes a weakly chaotic dynamical system: a nonlinear map which generates subdiffusion…

Chaotic Dynamics · Physics 2007-05-23 Golan Bel , Eli Barkai

We study functional stochastic differential equations with a locally unbounded, functional drift focusing on well-posedness, stability and the strong Feller property. Following the non-functional case, we only consider integrability…

Probability · Mathematics 2020-09-08 Stefan Bachmann

We study random dynamical systems of certain continuous functions on the unit interval. We use bounded variation to provide sufficient conditions for unique ergodicity of these systems. Several classes of examples are provided.

Dynamical Systems · Mathematics 2024-10-25 Sander C. Hille , Hanna Oppelmayer , Tomasz Szarek

Constructions of numerous approximate sampling algorithms are based on the well-known fact that certain Gibbs measures are stationary distributions of ergodic stochastic differential equations (SDEs) driven by the Brownian motion. However,…

Probability · Mathematics 2020-07-07 Lu-Jing Huang , Mateusz B. Majka , Jian Wang

This paper considers the problem of stabilizing a discrete-time non-linear stochastic system over a finite capacity noiseless channel. Our focus is on systems which decompose into a stable and unstable component, and the stability notion…

Optimization and Control · Mathematics 2021-09-07 Nicolás Garcia , Christoph Kawan , Serdar Yüksel

Based on some recent work of the author on stochastic approximation in non-markovian environments, the situation when the driving random process is non-ergodic in addition to being non-markovian is considered. Using this, we propose an…

Machine Learning · Statistics 2026-03-24 Vivek Shripad Borkar

In many applications, the common assumption that a driving noise process affecting a system is independent or Markovian may not be realistic, but the noise process may be assumed to be stationary. To study such problems, this paper…

Probability · Mathematics 2018-01-08 Serdar Yüksel

In this paper we prove strong well-posedness for a system of stochastic differential equations driven by a degenerate diffusion satisfying a weak-type H\"ormander condition, assuming H\"older regularity assumptions on the drift coefficient.…

Probability · Mathematics 2022-10-07 Giacomo Lucertini , Stefano Pagliarani , Andrea Pascucci

We prove existence of infinitely many stationary solutions as well as ergodic stationary solutions for the stochastic Navier-Stokes equations on $\mathbb{T}^2$ \begin{align*} \dif u+\div(u\otimes u)\dif t+\nabla p\dif t&=\Delta u\dif t +…

Probability · Mathematics 2024-02-22 Huaxiang Lü , Xiangchan Zhu

We prove the convergence at an exponential rate towards the invariant probability measure for a class of solutions of stochastic differential equations with finite delay. This is done, in this non-Markovian setting, using the cluster…

Probability · Mathematics 2016-07-11 Laure Pédèches
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