Unveiling causal interactions in complex systems.

Abstract:

:Throughout time, operational laws and concepts from complex systems have been employed to quantitatively model important aspects and interactions in nature and society. Nevertheless, it remains enigmatic and challenging, yet inspiring, to predict the actual interdependencies that comprise the structure of such systems, particularly when the causal interactions observed in real-world phenomena might be persistently hidden. In this article, we propose a robust methodology for detecting the latent and elusive structure of dynamic complex systems. Our treatment utilizes short-term predictions from information embedded in reconstructed state space. In this regard, using a broad class of real-world applications from ecology, neurology, and finance, we explore and are able to demonstrate our method's power and accuracy to reconstruct the fundamental structure of these complex systems, and simultaneously highlight their most fundamental operations.

authors

Stavroglou SK,Pantelous AA,Stanley HE,Zuev KM

doi

10.1073/pnas.1918269117

subject

Has Abstract

pub_date

2020-04-07 00:00:00

pages

7599-7605

issue

14

eissn

0027-8424

issn

1091-6490

pii

1918269117

journal_volume

117

pub_type

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