Exploring the complex dynamics of a Duffing oscillator with ordinal patterns analysis
Maximillian Trostel, Moses Misplon, Andr\'es Aragoneses, and Arjendu, Pattanayak

TL;DR
This paper investigates the complex dynamics of a Duffing oscillator using ordinal pattern analysis, revealing new dynamical regimes and correlations with chaos indicators that are not detectable by traditional methods.
Contribution
It introduces ordinal pattern analysis to study the Duffing oscillator's dynamics, uncovering regimes and transitions in chaos not seen with conventional statistical tools.
Findings
Different dynamical regimes within chaos identified
Correlation between Lyapunov exponent and permutation entropy established
Dips in Lyapunov exponent linked to dynamical transitions
Abstract
The driven double-well Duffing oscillator is a well-studied system that manifests a wide variety of dynamics, from periodic behavior to chaos, and describing a diverse array of physical systems. It has been shown to be relevant in understanding chaos in the classical to quantum transition. Here we explore the complexity of its dynamics in the classical and semi-classical regimes, using the technique of ordinal pattern analysis. This is of particular relevance to potential experiments in the semi-classical regime. We unveil different dynamical regimes within the chaotic range, which cannot be detected with more traditional statistical tools. These regimes are characterized by different hierarchies and probabilities of the ordinal patterns. Correlation between the Lyapunov exponent and the permutation entropy is revealed that leads to interpret dips in the Lyapunov exponent as transitions…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsChaos control and synchronization · Complex Systems and Time Series Analysis · Mathematical Dynamics and Fractals
