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Physics > Physics and Society

arXiv:2203.10702 (physics)
[Submitted on 21 Mar 2022 (v1), last revised 12 Sep 2022 (this
version, v2)]

Title:Unveiling the higher-order organization of multivariate time
series

Authors:Andrea Santoro, Federico Battiston, Giovanni Petri, Enrico
Amico
Download PDF

    Abstract: Time series analysis has proven to be a powerful method
    to characterize several phenomena in biology, neuroscience and
    economics, and to understand some of their underlying dynamical
    features. Despite a plethora of methods have been proposed for
    the analysis of multivariate time series, most of them neglect
    the effect of non-pairwise interactions on the emerging dynamics.
    Here, we propose a novel framework to characterize the temporal
    evolution of higher-order dependencies within multivariate time
    series. Using network analysis and topology, we show that, unlike
    traditional tools based on pairwise statistics, our framework
    robustly differentiates various spatiotemporal regimes of coupled
    chaotic maps, including chaotic dynamical phases and various
    types of synchronization. Hence, using the higher-order
    co-fluctuation patterns in simulated dynamical processes as a
    guide, we highlight and quantify signatures of higher-order
    patterns in data from brain functional activity, financial
    markets, and epidemics. Overall, our approach sheds new light on
    the higher-order organization of multivariate time series,
    allowing a better characterization of dynamical group
    dependencies inherent to real-world data.

Comments: 16 pages, 5 figures. Supplementary Information (16 figures,
          2 tables)
          Physics and Society (physics.soc-ph); Social and
Subjects: Information Networks (cs.SI); Neurons and Cognition
          (q-bio.NC)
Cite as:  arXiv:2203.10702 [physics.soc-ph]
          (or arXiv:2203.10702v2 [physics.soc-ph] for this version)
          https://doi.org/10.48550/arXiv.2203.10702
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Andrea Santoro [view email]
[v1] Mon, 21 Mar 2022 02:02:13 UTC (7,890 KB)
[v2] Mon, 12 Sep 2022 14:24:05 UTC (27,320 KB)
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