Long-term behaviour of asymptotically autonomous Hamiltonian systems with multiplicative noise

TL;DR

This paper analyzes how multiplicative noise affects the long-term behavior of asymptotically Hamiltonian systems, revealing conditions for stability, equilibrium convergence, or emergence of new stable states.

Contribution

It introduces a novel analysis combining averaging and stochastic Lyapunov functions to study long-term dynamics under decaying multiplicative noise.

Findings

Trajectories may tend to the limiting system's equilibrium or to new stable states.

The decay rate of noise influences the system's asymptotic behavior.

Application to parametric autoresonance demonstrates practical implications.

Abstract

The influence of multiplicative stochastic perturbations on the class of asymptotically Hamiltonian systems on the plane is investigated. It is assumed that disturbances do not preserve the equilibrium of the corresponding limiting system and their intensity decays in time with power-law asymptotics. The paper discusses the long-term asymptotic behaviour of solutions and its dependence on the structure and parameters of perturbations. In particular, it is shown that perturbed trajectories can tend to the equilibrium of the limiting system or new stochastically stable states can arise. The proposed analysis is based on a combination of the averaging method and the construction of stochastic Lyapunov functions. The results obtained are applied to the problem of capture into parametric autoresonance in the presence of noise.