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The irreducibility is fundamental for the study of ergodicity of stochastic dynamical systems. The existing methods on the irreducibility of stochastic partial differential equations (SPDEs) and stochastic differential equations (SDEs)…

Probability · Mathematics 2025-05-27 Jian Wang , Hao Yang , Jianliang Zhai , Tusheng Zhang

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

We show the strong well-posedness of SDEs driven by general multiplicative L\'evy noises with Sobolev diffusion and jump coefficients and integrable drift. Moreover, we also study the strong Feller property, irreducibility as well as the…

Probability · Mathematics 2017-05-23 Longjie Xie , Xicheng Zhang

In this work, we study ergodicity of continuous time Markov processes on state space $\mathbb{R}_{\geq 0} := [0,\infty)$ obtained as unique strong solutions to stochastic equations with jumps. Our first main result establishes exponential…

Probability · Mathematics 2019-02-11 Martin Friesen , Peng Jin , Jonas Kremer , Barbara Rüdiger

We develop a general framework for studying ergodicity of order-preserving Markov semigroups. We establish natural and in a certain sense optimal conditions for existence and uniqueness of the invariant measure and exponential convergence…

Probability · Mathematics 2020-10-28 Oleg Butkovsky , Michael Scheutzow

In this paper we show irreducibility and the strong Feller property for transition probabilities of stochastic differential equations with jumps and monotone coefficients. Thus, exponential ergodicity and the spectral gap for the…

Probability · Mathematics 2012-07-12 Huijie Qiao

Conditions sufficient for the transience of the process have been established for the Markov diffusion model with switching and two modes, transient and ergodic, with intensities bounded away from zero. This paper shows limitations on the…

Probability · Mathematics 2024-06-26 Kirill Mosievich

We develop a theory of ergodicity for a class of random dynamical systems where the driving noise is not white. The two main tools of our analysis are the strong Feller property and topological irreducibility, introduced in this work for a…

Probability · Mathematics 2011-11-09 M. Hairer , A. Ohashi

We prove exponential convergence to the invariant measure, in the total variation norm, for solutions of SDEs driven by $\alpha$-stable noises in finite and in infinite dimensions. Two approaches are used. The first one is based on Harris…

Analysis of PDEs · Mathematics 2011-04-27 E. Priola , A. Shirikyan , L. Xu , J. Zabczyk

Considering irreducibility is fundamental for studying the ergodicity of stochastic dynamical systems. In this paper, we establish the irreducibility of stochastic complex Ginzburg-Laudau equations driven by pure jump noise. Our results are…

Probability · Mathematics 2022-10-04 Hao Yang , Jian Wang , Jianliang Zhai

We consider SDEs driven by multiplicative pure jump L\'{e}vy noises, where L\'evy processes are not necessarily comparable to $\alpha$-stable-like processes. By assuming that the SDE has a unique solution, we obtain gradient estimates of…

Probability · Mathematics 2018-01-19 Mingjie Liang , Jian Wang

This paper aims to develop the stability theory for singular stochastic Markov jump systems with state-dependent noise, including both continuous- and discrete-time cases. The sufficient conditions for the existence and uniqueness of a…

Optimization and Control · Mathematics 2015-09-04 Yong Zhao , Weihai Zhang

By using the coupling technique, we present sufficient conditions for the exponential ergodicity of general continuous-state nonlinear branching processes in both the $L^1$-Wasserstein distance and the total variation norm, where the drift…

Probability · Mathematics 2019-09-16 Pei-Sen Li , Jian Wang

In this paper, we study the weak irreducibility of stochastic delay differential equations(SDDEs) driven by pure jump noise. The main contribution of this paper is to provide a concise proof of weak irreducibility, releasing condition…

Probability · Mathematics 2025-09-03 Hao Yang , Jian Wang

This paper focuses on stochastic partial differential equations (SPDEs) under two-time-scale formulation. Distinct from the work in the existing literature, the systems are driven by $\alpha$-stable processes with $\alpha \in(1,2)$. In…

Statistics Theory · Mathematics 2016-09-30 Jianhai Bao , George Yin , Chenggui Yuan

In this paper, we investigate the exponential ergodicity in a Wasserstein-type distance for a damping Hamiltonian dynamics with state-dependent and non-local collisions, which indeed is a special case of piecewise deterministic Markov…

Probability · Mathematics 2022-04-05 Jianhai Bao , Jian Wang

We study the ergodic property of a continuous-state branching process with immigration and competition. The exponential ergodicity in a weighted total variation distance is proved under natural assumptions. The main theorem applies to…

Probability · Mathematics 2023-09-06 Pei-Sen Li , Zenghu Li , Jian Wang , Xiaowen Zhou

In this paper, we first show the well-posedness of the SDEs driven by L\'{e}vy noises under mild conditions. Then, we consider the existence and uniqueness of periodic solutions of the SDEs. To establish the ergodicity and uniqueness of…

Probability · Mathematics 2019-06-20 Xiao-Xia Guo , Wei Sun

We establish verifiable general sufficient conditions for exponential or subexponential ergodicity of Markov processes that may lack the strong Feller property. We apply the obtained results to show exponential ergodicity of a variety of…

Probability · Mathematics 2019-03-27 Oleg Butkovsky , Alexei Kulik , Michael Scheutzow

This paper investigates the ergodicity of stochastic functional differential equations with jumps under the Wasserstein distance by the generalized coupling method. Two key conditions are verified. The first is verified by establishing an…

Probability · Mathematics 2026-05-07 Mingkun Ye , Yafei Zhai , Zuozheng Zhang
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