Global complexity signatures of solar cycles: A unified Entropy-Fractal survey of OMNI solar wind data (1964–2025)

Traditional solar-cycle studies emphasize amplitude- and duration-based indicators, overlooking the intrinsic complexity of heliospheric fluctuations. Entropy- and fractal-based descriptors offer complementary insight, but a cycle-resolved assessment across multiple observables has been missing. Usi...

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Vydáno v:Advances in space research Ročník 76; číslo 11; s. 7190 - 7204
Hlavní autoři: Sierra-Porta, D., Verdugo, Maximiliano Cañedo, Herrera Acevedo, Daniel David
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.12.2025
Témata:
Algorithmic complexity
Complexity analysis
Entropy
Fractal dimensions
Heliospheric medium
Solar cycles
28D20
28A80
85A35
Entropy
Heliospheric medium
Solar cycles
85A20
86A10
70K55
Complexity analysis
37B40
94A17
Algorithmic complexity
Fractal dimensions
37A60
ISSN:0273-1177
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Shrnutí:Traditional solar-cycle studies emphasize amplitude- and duration-based indicators, overlooking the intrinsic complexity of heliospheric fluctuations. Entropy- and fractal-based descriptors offer complementary insight, but a cycle-resolved assessment across multiple observables has been missing. Using daily OMNI-2 data (1964–2025), we segment each solar cycle (20–25) into ascending and descending phases and compute eleven global complexity measures per cycle–phase segment for ten solar-wind and geomagnetic observables. The metrics cover information content (Shannon, spectral), dynamical regularity (approximate, sample, permutation), geometric roughness (Higuchi, Katz, Petrosian), algorithmic novelty (Lempel–Ziv), and long-range memory (Hurst). We analyse redundancy and physical linkages via correlations and principal-component analysis (PCA), and quantify within-cycle phase contrasts using paired nonparametric tests with bootstrap effect sizes. Cycle parity is tested with permutation-based linear models controlling for the physical variable. Two orthogonal axes summarize the landscape: an amplitude–breadth direction (dominated by Shannon/spectral entropy) and a temporal-irregularity direction (ordinal entropies and Higuchi), while Lempel–Ziv forms an almost independent third dimension. Crucially, phase—not odd/even parity—organizes the dominant variability: ascending halves maximize multiscale roughness, whereas descending halves show broader amplitude dispersion and higher algorithmic novelty. Cross-metric–observable maps tie these facets to known regimes: fast streams and composition-rich intervals (e.g., larger α/p) raise ordinal richness and LZ; storm-time geomagnetic response (Dst, Kp) aligns with anti-persistence and space-filling trajectories. Global complexity metrics expose physically distinct regimes of the solar wind–magnetosphere system that are invisible to amplitude statistics. The phase-resolved design clarifies that cycle phase is the primary driver of global complexity, providing a compact feature space for sliding-window predictors in space-weather applications.
ISSN:0273-1177
DOI:10.1016/j.asr.2025.09.072