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Related papers: Burstiness and Memory in Complex Systems

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Many biological phenomena or social events critically depend on how information evolves in complex networks. However, a general theory to characterize information evolution is yet absent. Consequently, numerous unknowns remain about the…

Biological Physics · Physics 2022-07-20 Yang Tian , Guoqi Li , Pei Sun

Many natural phenomena exhibit power law behaviour in the distribution of event size. This scaling is successfully reproduced by Self Organized Criticality (SOC). On the other hand, temporal occurrence in SOC models has a Poisson-like…

Statistical Mechanics · Physics 2009-11-11 Eugenio Lippiello , Lucilla de Arcangelis , Cataldo Godano

Many astronomical phenomena, including Fast Radio Bursts and Soft Gamma Repeaters, consist of brief, separated, seemingly aperiodic events. The intervals between these events vary randomly, but there are epochs of greater activity, with…

High Energy Astrophysical Phenomena · Physics 2024-06-06 J. I. Katz

In many complex systems, we observe that `interesting behaviour' is often the consequence of a system exploiting the existence of an Information Bottleneck (IB). These bottlenecks can occur at different scales, between individuals or…

Physics and Society · Physics 2023-08-02 Michael Crosscombe , Hiroki Sato

Networks are universally considered as complex structures of interactions of large multi-component systems. In order to determine the role that each node has inside a complex network, several centrality measures have been developed. Such…

Physics and Society · Physics 2019-08-20 Malbor Asllani , Bruno Requiao da Cunha , Ernesto Estrada , James P. Gleeson

Bursting neurons are considered to be a potential cause of over-excitability and seizure susceptibility. The functional influence of these neurons in extended epileptic networks is still poorly understood. There is mounting evidence that…

Neurons and Cognition · Quantitative Biology 2016-10-07 Christian Geier , Alexander Rothkegel , Christian E. Elger , Klaus Lehnertz

Deep neural networks give us a powerful method to model the training dataset's relationship between input and output. We can regard that as a complex adaptive system consisting of many artificial neurons that work as an adaptive memory as a…

Disordered Systems and Neural Networks · Physics 2024-05-08 Kenichi Nakazato

Multistability-induced hysteresis has been widely studied in mechanical systems, but such behavior has proven more difficult to reproduce experimentally in flow networks. Natural flow networks like animal and plant vasculature can exhibit…

Soft Condensed Matter · Physics 2025-12-03 Lauren E. Altman , Nadia Aguilar , Douglas J. Durian , Miguel Ruiz-Garcia , Eleni Katifori

Multistability, the coexistence of multiple attractors in a dynamical system, is explored in bursting nerve cells. A modeling study is performed to show that a large class of bursting systems, as defined by a shared topology when…

Neurons and Cognition · Quantitative Biology 2010-06-29 J. P. Newman , R. J. Butera

Communication networks show the small-world property of short paths, but the spreading dynamics in them turns out slow. We follow the time evolution of information propagation through communication networks by using the SI model with…

Physics and Society · Physics 2011-02-25 M. Karsai , M. Kivelä , R. K. Pan , K. Kaski , J. Kertész , A. -L. Barabási , J. Saramäki

Human communication is commonly represented as a temporal social network, and evaluated in terms of its uniqueness. We propose a set of new entropy-based measures for human communication dynamics represented within the temporal social…

Social and Information Networks · Computer Science 2018-10-29 Marcin Kulisiewicz , Przemysław Kazienko , Bolesław K. Szymański , Radosław Michalski

The photoluminescence intermittency (blinking) of quantum dots is interesting because it is an easily-measured quantum process whose transition statistics cannot be explained by Fermi's Golden Rule. Commonly, the transition statistics are…

Mesoscale and Nanoscale Physics · Physics 2023-01-23 Roberto N. Munoz , Laszlo Frazer , Gangcheng Yuan , Paul Mulvaney , Felix A. Pollock , Kavan Modi

With the advent of high-performance computing, Bayesian methods are increasingly popular tools for the quantification of uncertainty throughout science and industry. Since these methods impact the making of sometimes critical decisions in…

Statistics Theory · Mathematics 2016-05-20 Houman Owhadi , Clint Scovel , Tim Sullivan

Complex coherent dynamics is present in a wide variety of neural systems. A typical example is the voltage transitions between up and down states observed in cortical areas in the brain. In this work, we study this phenomenon via a…

Neurons and Cognition · Quantitative Biology 2015-05-19 Jorge F. Mejias , Hilbert J. Kappen , Joaquin J. Torres

The information scrambling in many-body systems is closely related to quantum chaotic dynamics, complexity, and gravity. Here we propose a collision model to simulate the information dynamics in an all-optical system. In our model the…

Quantum Physics · Physics 2020-04-23 Yan Li , Xingli Li , Jiasen Jin

Large transformer-based models are able to perform in-context few-shot learning, without being explicitly trained for it. This observation raises the question: what aspects of the training regime lead to this emergent behavior? Here, we…

The observable behavior of a complex system reflects the mechanisms governing the internal interactions between the system's components and the effect of external perturbations. Here we show that by capturing the simultaneous activity of…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Argollo de Menezes , A. -L. Barabasi

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic…

Statistical Finance · Quantitative Finance 2017-05-24 V. Gontis , A. Kononovicius

Complex systems are often characterized by the interplay of multiple interconnected dynamical processes operating across a range of temporal scales. This phenomenon is widespread in both biological and artificial scenarios, making it…

Statistical Mechanics · Physics 2025-09-08 Giorgio Nicoletti , Daniel M. Busiello

In recent years, there has been an increased need for the use of active systems - systems required to act automatically based on events, or changes in the environment. Such systems span many areas, from active databases to applications that…

Artificial Intelligence · Computer Science 2012-07-09 Segev Wasserkrug , Avigdor Gal , Opher Etzion