Litcius/Paper detail

Anticipating synchrony in dynamical systems using information theory

Anupam Ghosh, Samadhan A. Pawar, R. I. Sujith

2022Chaos An Interdisciplinary Journal of Nonlinear Science11 citationsDOI

Abstract

Synchronization in coupled dynamical systems has been a well-known phenomenon in the field of nonlinear dynamics for a long time. This phenomenon has been investigated extensively both analytically and experimentally. Although synchronization is observed in different areas of our real life, in some cases, this phenomenon is harmful; consequently, an early warning of synchronization becomes an unavoidable requirement. This paper focuses on this issue and proposes a reliable measure ( R), from the perspective of the information theory, to detect complete and generalized synchronizations early in the context of interacting oscillators. The proposed measure R is an explicit function of the joint entropy and mutual information of the coupled oscillators. The applicability of R to anticipate generalized and complete synchronizations is justified using numerical analysis of mathematical models and experimental data. Mathematical models involve the interaction of two low-dimensional, autonomous, chaotic oscillators and a network of coupled Rössler and van der Pol oscillators. The experimental data are generated from laboratory-scale turbulent thermoacoustic systems.

Topics & Concepts

Synchronization (alternating current)Computer scienceMutual informationDynamical systems theoryMeasure (data warehouse)Statistical physicsInformation theoryNonlinear systemSynchronization of chaosContext (archaeology)ChaoticSynchronization networksPhenomenonPhysicsControl theory (sociology)MathematicsArtificial intelligenceData miningQuantum mechanicsComputer networkBiologyPaleontologyControl (management)Channel (broadcasting)StatisticsNonlinear Dynamics and Pattern FormationNeural dynamics and brain functionstochastic dynamics and bifurcation