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  Recurrence-based characterization of model shadowability in the presence of unstable dimension variability

Fávaro, V. H. A., Marwan, N., Kurths, J., Grebogi, C., Viana, R. L. (2025): Recurrence-based characterization of model shadowability in the presence of unstable dimension variability. - EPL (Europhysics Letters), 152, 6, 61002.
https://doi.org/10.1209/0295-5075/ae2cc4

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Fávaro, Vitor H. A.1, Author
Marwan, Norbert2, Author                 
Kurths, Jürgen2, Author           
Grebogi, Celso1, Author
Viana, Ricardo L.1, Author
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Unstable dimension variability is an extreme form of non-hyperbolic behavior, causing severe obstructions to shadowability of numerically generated trajectories of chaotic systems. It has been argued that, in spite of the poor model shadowability of systems with unstable dimension variability, ensembles of chaotic numerical trajectories may still be useful for statistical calculations. The kicked double rotor is a four-dimensional map exhibiting unstable dimension variability for a large parameter interval. By exploring the recurrence properties, we confirm previous claims that, despite the unpredictability of individual trajectories in the kicked double rotor due to unstable dimension variability, statistical measures and recurrence properties remain stable, suggesting their robustness in characterizing the system. While these findings are specific to this system and do not constitute a general proof, a sliding window analysis further confirms the temporal consistency of recurrence measures, supporting their reliability in studying complex chaotic dynamics and encouraging further exploration of their role in hyperchaotic regimes.

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Language(s): eng - English
 Dates: 2025-12-292025-12-29
 Publication Status: Finally published
 Pages: 7
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1209/0295-5075/ae2cc4
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
Research topic keyword: Nonlinear Dynamics
Model / method: Quantitative Methods
Model / method: Nonlinear Data Analysis
 Degree: -

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Title: EPL (Europhysics Letters)
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 152 (6) Sequence Number: 61002 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals132
Publisher: IOP Publishing