Switching Exponent Scaling near Bifurcation Points for Non-Gaussian Noise

Lora Billings, Montclair State University
Ira Schwartz, US Naval Research Labratory
Mary McCrary, Montclair State University
A. Korotkrov, University of California, Riverside
M. Dykman, Michigan State University

Abstract

We study noise-induced switching of a system close to bifurcation parameter values where the number of stable states changes. For non-Gaussian noise, the switching exponent, which gives the logarithm of the switching rate, displays a non-power-law dependence on the distance to the bifurcation point. This dependence is found for Poisson noise. Even weak additional Gaussian noise dominates switching sufficiently close to the bifurcation point, leading to a crossover in the behavior of the switching exponent.