English

Most probable transition paths in piecewise-smooth stochastic differential equations

Dynamical Systems 2022-11-08 v3 Probability

Abstract

We develop a path integral framework for determining most probable paths in a class of systems of stochastic differential equations with piecewise-smooth drift and additive noise. This approach extends the Freidlin-Wentzell theory of large deviations to cases where the system is piecewise-smooth and may be non-autonomous. In particular, we consider an nn-dimensional system with a switching manifold in the drift that forms an (n1)(n-1)-dimensional hyperplane and investigate noise-induced transitions between metastable states on either side of the switching manifold. To do this, we mollify the drift and use Γ\Gamma-convergence to derive an appropriate rate functional for the system in the piecewise-smooth limit. The resulting functional consists of the standard Freidlin-Wentzell rate functional, with an additional contribution due to times when the most probable path slides in a crossing region of the switching manifold. We explore implications of the derived functional through two case studies, which exhibit notable phenomena such as non-unique most probable paths and noise-induced sliding in a crossing region.

Keywords

Cite

@article{arxiv.2112.12958,
  title  = {Most probable transition paths in piecewise-smooth stochastic differential equations},
  author = {Kaitlin Hill and Jessica Zanetell and John A Gemmer},
  journal= {arXiv preprint arXiv:2112.12958},
  year   = {2022}
}

Comments

38 pages, 9 figures

R2 v1 2026-06-24T08:30:43.820Z