Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems

被引:135
作者
Wu, LM [1 ]
机构
[1] Univ Blaise Pascal, Lab Math Appl, CNRS, UMR 6620, F-63177 Clermont Ferrand, France
[2] Wuhan Univ, Dept Math, Wuhan 430072, Peoples R China
关键词
stochastic Hamiltonian systems; large deviations; moderate deviations; exponential convergence; hyper-exponential recurrence;
D O I
10.1016/S0304-4149(00)00061-2
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A classical damping Hamiltonian system perturbed by a random force is considered. The locally uniform large deviation principle of Donsker and Varadhan is established for its occupation empirical measures for large time, under the condition, roughly speaking, that the force driven by the potential grows infinitely at infinity. Under the weaker condition that this force remains greater than some positive constant at infinity, we show that the system converges to its equilibrium measure with exponential rate, and obeys moreover the moderate deviation principle. Those results are obtained by constructing appropriate Lyapunov test functions, and are based on some results about large and moderate deviations and exponential convergence for general strong-Feller Markov processes. Moreover, these conditions on the potential are shown to be sharp. (C) 2001 Elsevier Science B.V. All rights reserved. MSC: 60F10; 93E15; 60W10; 70L05.
引用
收藏
页码:205 / 238
页数:34
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