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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

This chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and…

Adaptation and Self-Organizing Systems · Physics 2013-08-01 Nelson Fernandez , Carlos Maldonado , Carlos Gershenson

The Kolmogorov complexity of a string is the length of its shortest description. We define a second quantised Kolmogorov complexity where the length of a description is defined to be the average length of its superposition. We discuss this…

Quantum Physics · Physics 2008-09-17 Caroline Rogers , Vlatko Vedral , Rajagopal Nagarajan

We present a complexity measure for any finite time series. This measure has invariance under any monotonic transformation of the time series, has a degree of robustness against noise, and has the adaptability of satisfying almost all the…

Chaotic Dynamics · Physics 2008-11-25 Da-Guan Ke , Qin-Ye Tong

We show that a family of random variables is uniformly integrable if and only if it is stochastically bounded in the increasing convex order by an integrable random variable. This result is complemented by proving analogous statements for…

Probability · Mathematics 2011-06-06 Lasse Leskelä , Matti Vihola

Certain deterministic non-linear systems may show chaotic behaviour. Time series derived from such systems seem stochastic when analyzed with linear techniques. However, uncovering the deterministic structure is important because it allows…

chao-dyn · Physics 2008-02-03 Dimitris Kugiumtzis , Bjoern Lillekjendlie , Nils Christophersen

Coherent structures emerge from the dynamics of many kinds of dissipative, externally driven, nonlinear systems, and continue to provoke new questions that challenge our physical and mathematical understanding. In one specific sub-class of…

Pattern Formation and Solitons · Physics 2010-08-24 Jonathan Dawes

Spread complexity uses the distribution of support of a time-evolving state in the Krylov basis to quantify dispersal across accessible dimensions of a Hilbert space. Here, we describe how variations in initial conditions, the Hamiltonian,…

High Energy Physics - Theory · Physics 2025-11-19 Vijay Balasubramanian , Pawel Caputa , Joan Simón

Noise modifies the behavior of chaotic systems in both quantitative and qualitative ways. To study these modifications, the present work compares the topological structure of the deterministic Lorenz (1963) attractor with its stochastically…

Chaotic Dynamics · Physics 2021-10-27 Gisela D. Charó , Mickaël D. Chekroun , Denisse Sciamarella , Michael Ghil

Adaptive dynamical systems arise in a multitude of contexts, e.g., optimization, control, communications, signal processing, and machine learning. A precise characterization of their fundamental limitations is therefore of paramount…

Information Theory · Computer Science 2010-10-13 Maxim Raginsky

Kolmogorov complexity measures the algorithmic complexity of a finite binary string $\sigma$ in terms of the length of the shortest description $\sigma^*$ of $\sigma$. Traditionally, the length of a string is taken to measure the amount of…

Computational Complexity · Computer Science 2019-06-14 Cameron Fraize , Christopher P. Porter

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are…

Disordered Systems and Neural Networks · Physics 2009-11-13 Kartik Anand , Tobias Galla

As no heat effect and mechanical work are observed, we have a simple experimental resolution of the Gibbs paradox: both the thermodynamic entropy of mixing and the Gibbs free energy change are zero during the formation of any ideal…

General Physics · Physics 2008-11-23 Shu-Kun Lin

Recent research has provided a wealth of evidence highlighting the pivotal role of high-order interdependencies in supporting the information-processing capabilities of distributed complex systems. These findings may suggest that high-order…

Adaptation and Self-Organizing Systems · Physics 2023-05-24 Patricio Orio , Pedro A. M. Mediano , Fernando E. Rosas

The unreduced, universally nonperturbative analysis of arbitrary interaction process, described by a quite general equation, provides the truly complete, "dynamically multivalued" general solution that leads to dynamically derived,…

General Physics · Physics 2007-05-23 Andrei P. Kirilyuk

Information (I) is defined as the amount of the data after data compression. The first law of information theory: the total amount of data L (the sum of entropy S and information I) of an isolated system remains unchanged. The second law of…

Chemical Physics · Physics 2008-03-19 Shu-Kun Lin

Here we deconstruct, and then in a reasoned way reconstruct, the concept of "entropy of a system," paying particular attention to where the randomness may be coming from. We start with the core concept of entropy as a COUNT associated with…

General Physics · Physics 2017-05-10 Tommaso Toffoli

A disordered solid, such as an athermal jammed packing of soft spheres, exists in a rugged potential-energy landscape in which there are a myriad of stable configurations that defy easy enumeration and characterization. Nevertheless, in…

Soft Condensed Matter · Physics 2024-03-26 Varda F. Hagh , Sidney R. Nagel

We consider the dynamical behavior of Martin-L\"of random points in dynamical systems over metric spaces with a computable dynamics and a computable invariant measure. We use computable partitions to define a sort of effective symbolic…

Dynamical Systems · Mathematics 2008-04-29 Stefano Galatolo , Mathieu Hoyrup , Cristobal Rojas

We introduce a uniform representation of general objects that captures the regularities with respect to their structure. It allows a representation of a general class of objects including geometric patterns and images in a sparse, modular,…

Computational Complexity · Computer Science 2008-06-12 Hiroshi Ishikawa
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