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  Density-based recurrence measures from microstates

Lopes da Cruz, F. E., Prado, T. d. L., Lopes, S. R., Marwan, N., Kurths, J. (2025): Density-based recurrence measures from microstates. - Physical Review E, 111, 4, 044212.
https://doi.org/10.1103/PhysRevE.111.044212

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cruz_2025_PhysRevE.111.044212.pdf (Verlagsversion), 2MB
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Lopes da Cruz, Felipe Eduardo1, Autor           
Prado, Thiago de Lima2, Autor
Lopes, Sergio Roberto2, Autor
Marwan, Norbert1, Autor                 
Kurths, Jürgen1, Autor           
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Recurrence analysis is a powerful tool for nonlinear time series analysis deeply rooted in the theory of dynamical systems, finding applications across many areas of science. It works by mapping recurrences of a time series or phase space trajectory into a logical matrix. Recurrence quantification analyses (RQAs) are computed from its internal structures, such as recurrence density and the distribution of diagonal and vertical lines. Here, we link the density-based recurrence measures such as determinism and laminarity to the concept of microstates. We present a way to obtain the histogram of both diagonal and vertical lines from recurrence microstates, which are small square submatrices of the recurrence matrix. This approach opens up a line of research by reframing traditional RQAs in terms of microstates. Therefore, we establish a bridge between concepts of traditional lines-based RQA and recurrence microstates, and illustrate this for various paradigmatic systems.

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Sprache(n): eng - English
 Datum: 2025-04-172025-04-17
 Publikationsstatus: Final veröffentlicht
 Seiten: 11
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1103/PhysRevE.111.044212
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: Nonlinear Data Analysis
Model / method: Quantitative Methods
Model / method: Research Software Engineering (RSE)
OATYPE: Hybrid Open Access
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Titel: Physical Review E
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 111 (4) Artikelnummer: 044212 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/150218
Publisher: American Physical Society (APS)