Pattern generation and symbolic dynamics in a nanocontact vortex oscillator

TL;DR

This paper investigates the nonlinear chaotic dynamics of a nanocontact vortex oscillator, revealing complex patterns and high entropy states that could be useful for unconventional information processing in spintronic devices.

Contribution

It is the first experimental characterization of symbolic dynamics and pattern generation in a nanocontact vortex oscillator, demonstrating its potential as a nanoscale entropy source.

Findings

Chaotic signals exhibit unpredictable pattern alternation linked to core-polarity switching.

Advanced filtering isolates nonlinear deterministic patterns from thermal noise.

Maximal entropy and complexity are observed in the incommensurate regime.

Abstract

Harnessing chaos or intrinsic nonlinear behaviours from dynamical systems is a promising avenue for the development of unconventional information processing technologies. However, the exploitation of such features in spintronic devices has not been attempted despite the many theoretical and experimental evidence of nonlinear behaviour of the magnetization dynamics in nanomagnetic systems. Here, we propose a first step in that direction by unveiling and characterizing the patterns and symbolic dynamics originating from the nonlinear chaotic time-resolved electrical signals generated experimentally by a nanocontact vortex oscillator (NCVO). We use advanced filtering methods to dissociate nonlinear deterministic patterns from thermal fluctuations and show that the emergence of chaos results in the unpredictable alternation of simple oscillatory patterns controlled by the NCVO's core-polarity switching. With phase-space reconstruction techniques, we perform a symbolic analysis of the time series to assess the level of complexity and entropy generated in the chaotic regime. We find that at the centre of its incommensurate region, it can exhibit maximal entropy and complexity. This suggests that NCVOs are promising nonlinear nanoscale source of entropy that could be harnessed for information processing.