A Dynamical Systems Approach for Most Probable Escape Paths over Periodic Boundaries
Emmanuel Fleurantin, Katherine Slyman, Blake Barker, Christopher K. R., T. Jones

TL;DR
This paper develops a geometric dynamical systems method to identify the most probable escape paths over periodic boundaries in stochastic systems, validated by simulations of the reversed van der Pol system.
Contribution
It introduces a novel approach combining the Maslov index and Onsager-Machlup functional to accurately predict escape paths over periodic boundaries.
Findings
OM-selected MPEP closely matches noisy trajectory escape paths
The approach isolates a subset of the unstable manifold called the River
Predictions are validated through Monte-Carlo simulations
Abstract
Analyzing when noisy trajectories, in the two dimensional plane, of a stochastic dynamical system exit the basin of attraction of a fixed point is specifically challenging when a periodic orbit forms the boundary of the basin of attraction. Our contention is that there is a distinguished Most Probable Escape Path (MPEP) crossing the periodic orbit which acts as a guide for noisy escaping paths in the case of small noise slightly away from the limit of vanishing noise. It is well known that, before exiting, noisy trajectories will tend to cycle around the periodic orbit as the noise vanishes, but we observe that the escaping paths are stubbornly resistant to cycling as soon as the noise becomes at all significant. Using a geometric dynamical systems approach, we isolate a subset of the unstable manifold of the fixed point in the Euler-Lagrange system, which we call the River. Using the…
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Taxonomy
TopicsEcosystem dynamics and resilience · Diffusion and Search Dynamics · Stochastic processes and statistical mechanics
