Self-organized criticality is an elegant explanation of how complex structures emerge and persist throughout nature, and why such structures often exhibit similar scale-invariant properties. Although self-organized criticality is sometimes captured by simple models that feature a critical point as an attractor for the dynamics, the connection to real-world systems is exceptionally hard to test quantitatively. Here we observe three key signatures of self-organized criticality in the dynamics of a driven-dissipative gas of ultracold potassium atoms: self-organization to a stationary state that is largely independent of the initial conditions; scale-invariance of the final density characterized by a unique scaling function; and large fluctuations of the number of excited atoms (avalanches) obeying a characteristic power-law distribution. This work establishes a well-controlled platform for investigating self-organization phenomena and non-equilibrium criticality, with experimental access to the underlying microscopic details of the system.
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http://dx.doi.org/10.1038/s41586-019-1908-6 | DOI Listing |
Zh Nevrol Psikhiatr Im S S Korsakova
January 2025
Pirogov Russian National Research Medical University (Pirogov University), Moscow, Russia.
Stroke is the main cause of disability among neurological diseases. There are questions of the accuracy of topical diagnosis and rehabilitation prognosis in clinical practice. Answers to these questions may be given by an approach to the study of the nervous system as a dynamic network consisting of a set of brain regions with anatomical and functional connections between them.
View Article and Find Full Text PDFPhys Rev E
November 2024
Earthquake Research Institute, University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-0032, Japan.
We examine the conditions for the emergence of self-organized criticality in the Olami-Feder-Christensen model by introducing a single defect under periodic boundary conditions. Our findings reveal that strong localized energy dissipation is crucial for self-organized criticality emergence, while weak localized or global energy dissipation leads to its disappearance in this model. Furthermore, slight dissipation perturbations to a system in a self-organized criticality reveal a novel state characterized by a limit cycle of distinct configurations.
View Article and Find Full Text PDFPhys Rev E
November 2024
Institute of Earthquake Prediction Theory and Mathematical Geophysics, RAS, Profsoyuznaya 84/32, 117997 Moscow, Russia.
We study two prototypical models of self-organized criticality, namely sandpile automata with deterministic (Bak-Tang-Wiesenfeld) and probabilistic (Manna model) dynamical rules, focusing on the nature of stress fluctuations induced by driving-adding grains during avalanche propagation, and dissipation through avalanches that hit the system boundary. Our analysis of stress evolution time series reveals robust cyclical trends modulated by collective fluctuations with dissipative avalanches. These modulated cycles attain higher harmonics, characterized by multifractal measures within a broad range of timescales.
View Article and Find Full Text PDFSci Rep
November 2024
Institute of Earthquake Prediction Theory and Mathematical Geophysics RAS, Profsoyuznaya 84/32, Moscow, 117997, Russia.
The state-of-the-art in the theory of self-organized criticality reveals that a certain inactivity precedes extreme events, which are located on the tail of the event probability distribution with respect to their sizes. The existence of the inactivity allows for the prediction of these events in advance. In this work, we explore the predictability of the Bak-Tang-Wiesenfeld (BTW) and Manna models on the square lattice as a function of the lattice length.
View Article and Find Full Text PDFFront Neural Circuits
September 2024
Complexity Science Group, Department of Physics and Astronomy, Faculty of Science, University of Calgary, Calgary, AB, Canada.
The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow.
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