# Sur la convergence sous-exponentielle de processus de Markov

Abstract : My Ph.D dissertation mainly focuses on long time behavior of Markov processes, functional inequalities and related techniques. More specifically, I will present the computable sub-exponential convergence rate of the Markov process in two approaches : Meyn-Tweedie’s method and (weak) hypocoercivity. The paper consists of three parts. In the first part, I will introduce some important results and related knowledge. Firstly, overviews of my research field are given. Exponential (or subexponential) convergence of Markov chains and (continuous time) Markov processes is a hot issue in probability. The traditional method - Meyn-Tweedie’s approach is widely applied for this problem. Most of the results about convergence rate is not explicit, and some of them will be introduced briefly. In addition,Lyapunov function is crucial in Meyn-Tweendie’s aproach, and it is also related to some functional inequalities (for example, Poincar´e inequality). The relationship of them will be given with results in L2 sense. Furthermore, as a example of kinetic Fokker-Planck equation, a computable result of exponential convergence of the solution of it will be introduced in Villani’ way - hypocoercivity. These contents are foundations of my work, and my destination is to study the sub-exponential decay. In the second part, it is my article cooperated with others about subexponential convergence rate of continuous time Markov processes. As we all know, the explicit results of convergence rate is about the exponential case. We extend them to sub-exponential case in Meyn-Tweedie’s approach. The key of the proof is the estimation of the hitting time to small set which was got by Douc, Fort and Guillin, for which we also propose an alternative simpler proof. We also use coupling construction as others and give a quantitative sub-exponential ergodicity. At last, we give some calculations for examples. In the last part, my second article deal with the kinetic Fokker-Planck equation. I extend the hypocoercivity to weak hypocoercivity which correspond to weak Poincar´e inequality. Through the extension, one can get the computable rate of convergence of the solution, which is also sub-exponential case. The convergence is in H1 sense and in L2 sense. In the end of this paper, I study the relative entropy case as C.Villani, and get convergence in entropy. Finally, I give two examples for potentials that implies weak Poincar´e inequality or weak logarithmic Sobolve inequality for invarient measure.
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### Citation

Xinyu Wang. Sur la convergence sous-exponentielle de processus de Markov. Mathématiques générales [math.GM]. Université Blaise Pascal - Clermont-Ferrand II, 2012. Français. ⟨NNT : 2012CLF22253⟩. ⟨tel-00840858⟩

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