Noise-induced chaos: A conditioned random dynamics perspective

What is it about?

A key question in the study of dynamical systems addresses the mechanisms through which chaos arises. To shed new light on this topic, we explore the shift to chaos in a noisy logistic map as the strength of the noise is increased. Our analysis employs conditioned random dynamics, focusing on expected escape times and conditioned Lyapunov exponents in a compartmental model that depicts the interplay between contracting and expanding behaviors. Unlike previous studies, our approach doesn't rely on assumptions of small noise or deterministic paradigms.

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Photo by Brett Jordan on Unsplash

Photo by Brett Jordan on Unsplash

Why is it important?

This paper successfully pilots conditioned dynamics as a mathematical framework to study bifurcations in random systems beyond the small noise setting.