Scaling Concepts in Periodically Modulated Noisy Systems

TL;DR

This paper demonstrates how scaling arguments and symmetry analysis can predict complex behaviors like stochastic resonance in periodically modulated noisy systems, providing insights into the interplay between noise and signals.

Contribution

It introduces a scaling approach to analyze the dynamics of noisy systems under periodic modulation, highlighting the role of symmetries in predicting phenomena like stochastic resonance.

Findings

Predicts stochastic resonance and related phenomena through symmetry analysis

Shows how signal-to-noise ratio varies with noise levels

Provides a framework for understanding noise-signal interactions in complex systems

Abstract

We show that scaling arguments are very useful to analyze the dynamics of periodically modulated noisy systems. Information about the behavior of the relevant quantities, such as the signal-to-noise ratio, upon variations of the noise level, can be obtained by analyzing the symmetries and invariances of the system. In this way, it is possible to predict diverse physical manifestations of the cooperative behavior between noise and input signal, as for instance stochastic resonance, spatiotemporal stochastic resonance, and stochastic multiresonance.