Averaging for stochastic perturbations of integrable systems
Guan Huang, Sergei Kuksin, Andrey Piatnitski

TL;DR
This paper proves averaging theorems for small stochastic perturbations of integrable systems, establishing convergence of solutions to averaged equations and constructing effective stochastic models, especially under mixing conditions.
Contribution
It introduces new averaging results for stochastic perturbations of integrable systems and constructs effective equations with uniform convergence under mixing assumptions.
Findings
Solutions of perturbed systems converge to averaged equations as perturbation vanishes.
Effective stochastic equations accurately describe the long-term behavior of perturbed systems.
Uniform convergence occurs when the averaged system exhibits mixing properties.
Abstract
We are concerned with averaging theorems for -small stochastic perturbations of integrable equations in and in , where is the vector of actions, . The vector-functions and are locally Lipschitz and non-degenerate. Perturbations of these equations are assumed to be locally Lipschitz and such that some few first moments of the norms of their solutions are bounded uniformly in , for . For -components of solutions for perturbations of (1) we establish their convergence in law…
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Taxonomy
TopicsStochastic processes and financial applications · Quantum chaos and dynamical systems · Stochastic processes and statistical mechanics
