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Exactly scale-free scale-free networks

There is mounting evidence of the apparent ubiquity of scale-free networks among complex systems. Many natural and physical systems exhibit patterns of interconnection that conform, approximately, to the structure expected of a scale-free network. We propose an efficient algorithm to generate representative samples from the space of all networks defined by a particular (scale-free) degree distribution. Using this algorithm we are able to systematically explore that space with some surprising results: in particular, we find that preferential attachment growth models do not yield typical realizations and that there is a certain latent structure among such networks --- which we loosely term "hub-centric". We provide a method to generate or remove this latent hub-centric bias --- thereby demonstrating exactly which features of preferential attachment networks are atypical of the broader class of scale free networks. Based on these results we are also able to statistically determine whether experimentally observed networks are really typical realizations of a given degree distribution (scale-free degree being the example which we explore). In so doing we propose a surrogate generation method for complex networks, exactly analogous the the widely used surrogate tests of nonlinear time series analysis.


Via Bernard Ryefield
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Complejidad y aleatoriedad

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Exact Complexity: The Spectral Decomposition of Intrinsic Computation

We give exact formulae for a wide family of complexity measures that capture the organization of hidden nonlinear processes. The spectral decomposition of operator-valued functions leads to closed-form expressions involving the full eigenvalue spectrum of the mixed-state presentation of a process's epsilon-machine causal-state dynamic. Measures include correlation functions, power spectra, past-future mutual information, transient and synchronization informations, and many others. As a result, a direct and complete analysis of intrinsic computation is now available for the temporal organization of finitary hidden Markov models and nonlinear dynamical systems with generating partitions and for the spatial organization in one-dimensional systems, including spin systems, cellular automata, and complex materials via chaotic crystallography.

 

Exact Complexity: The Spectral Decomposition of Intrinsic Computation
James P. Crutchfield, Christopher J. Ellison, Paul M. Riechers

http://arxiv.org/abs/1309.3792


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Rescooped by Complejidady Economía from Complex World
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Most Influential Emotions On Social Networks Revealed

Most Influential Emotions On Social Networks Revealed | Sistemas complejos | Scoop.it
Anger spreads faster and more broadly than joy, say computer scientists who have analysed sentiment on the Chinese Twitter-like service Weibo

Via Claudia Mihai
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[1301.3698] Modeling human dynamics of face-to-face interaction networks

Complejidady Economía's insight:

Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents which perform a random walk in a two dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

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Researchers develop new method for understanding network connections - MIT News Office

Researchers develop new method for understanding network connections - MIT News Office | Sistemas complejos | Scoop.it
Technique could be applied to the study of disease, social networks and other diverse fields.
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¿Qué es complejidad? - Dr. Rafael Ángel Barrio

La mirada holística implica abordar el conocimiento como un proceso que es a la vez biológico, cultural, social e histórico. El Dr. Rafael Ángel Barrio obtuv...
Complejidady Economía's insight:

Excelente entrevista disponible en  Youtube por Felipe Flores

 

Felipe Flores

Vídeos científicos, culturales y recreativos propios o de terceras personas.

 twitter.com/#!/FelipeFloresMX facebook.com/profile.php?id=519526219 
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Una aproximación a los sistemas complejos. Revista Ciencias (UNAM) número 59 julio-septiembre 2000

Una aproximación a los sistemas complejos.                                              Revista Ciencias (UNAM) número 59 julio-septiembre 2000 | Sistemas complejos | Scoop.it
Revista ciencias de la Facultad de Ciencias de la Universidad Nacional Autónoma de México

 

Los llamados sistemas complejos proporcionan modelos analogías y metáforas capaces de llevar por nuevos senderos a la investigación en las ciencias físicas, biológicas, atmosféricas, económicas, sociales, lingüísticas y otras más. (editorial)

 

Recomendación:

Una aproximación a los sistemas complejos

 

 

Gustavo Martínez Mekler

 

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On the necessity of complexity

On the necessity of complexity | Sistemas complejos | Scoop.it

Wolfram's Principle of Computational Equivalence (PCE) implies that universal complexity abounds in nature. This paper comprises three sections. In the first section we consider the question why there are so many universal phenomena around. So, in a sense, we week a driving force behind the PCE if any. We postulate a principle GNS that we call the Generalized Natural Selection Principle that together with the Church-Turing Thesis is seen to be equivalent to a weak version of PCE. In the second section we ask the question why we do not observe any phenomena that are complex but not-universal. We choose a cognitive setting to embark on this question and make some analogies with formal logic. In the third and final section we report on a case study where we see rich structures arise everywhere.

 

On the necessity of complexity

Joost J. Joosten

http://arxiv.org/abs/1211.1878


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How Facebook ‘Contagion’ Spreads

How Facebook ‘Contagion’ Spreads | Sistemas complejos | Scoop.it
By Sarah C.P. Williams, ScienceNOW

To join Facebook or not to join Facebook? You might think the decision depends on how many of your friends...


Via Frédéric Amblard
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Teoría de sistemas, sistemas complejos adaptativos y dialéctica: Mapa mental

Teoría de sistemas, sistemas complejos adaptativos y dialéctica: Mapa mental | Sistemas complejos | Scoop.it
(c) 2009 Txema Laullon. Copyleft, All rights reversed.
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Social Factors in Epidemiology

Despite the invention of control measures like vaccines, infectious diseases remain part of human existence. Ideas, sentiments, or information can also be contagious. Such social contagion is akin to biological contagion: Both spread through a replication process that is blind to the consequences for the individual or population, and if each person transmits to more than one person, the explosive power of exponential growth creates an epidemic. Social contagions may cause irrational “fever.” Isaac Newton, having lost £20,000 in the speculative South Sea Bubble, commented that he could “calculate the movement of the stars, but not the madness of men”. Systems in which both contagion types are coupled to one another—an infectious disease spreading by biological contagion and a social contagion concerning the disease—offer unique scientific challenges and are increasingly important for public health.

 

Social Factors in Epidemiology

Chris T. Bauch, Alison P. Galvani

Science 4 October 2013:
Vol. 342 no. 6154 pp. 47-49
http://dx.doi.org/10.1126/science.1244492


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Arjen ten Have's curator insight, October 8, 2013 12:04 PM

likely a better model of how ideas spread thru society than memes as genes

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A genetic map for complex diseases

A genetic map for complex diseases | Sistemas complejos | Scoop.it

University of Chicago scientists have created one of the most expansive analyses to date of the genetic factors at play in complex diseases such as autism and heart disease by using diseases with known genetic causes to guide them.

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Nonlinear-map model for the control of an airplane schedule

We study the dynamics and control of an airplane in air transportation between two airports. The dynamic models are presented for the airplane schedule. The dynamics of an airplane is described by the piecewise map and delayed map models. The characteristics of the nonlinear maps are studied analytically and numerically. The airplane displays the complex motion in the unstable region. The motion of the airplane depends on the quantity of goods, the control method, and the delay. It is shown that the control delay has an important effect on the motion.

 

Nonlinear-map model for the control of an airplane schedule
Takashi Nagatani

Physica A

http://dx.doi.org/10.1016/j.physa.2013.08.076


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Física de las reuniones sociales

Física de las reuniones sociales | Sistemas complejos | Scoop.it
Un modelo muy sencillo logra predecir los patrones de movilidad de las personas que toman parte en un evento colectivo.
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Rescooped by Complejidady Economía from Complex Networks Everywhere
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Generating functionals for guided self-organization

Time evolution equations for dynamical systems can often be derived from generating functionals. Examples are Newton's equations of motion in classical dynamics which can be generated within the Lagrange or the Hamiltonian formalism. We propose that generating functionals for self-organizing complex systems offer several advantages. Generating functionals allow to formulate complex dynamical systems systematically and the results obtained are typically valid for classes of complex systems, as defined by the type of their respective generating functionals. The generated dynamical systems tend, in addition, to be minimal, containing only few free and undetermined parameters. We point out that two or more generating functionals may be used to define a complex system and that multiple generating function may not, and should not, be combined into a single overall objective function. We provide and discuss examples in terms of adapting neural networks.


Via Ashish Umre, Alejandro J. Alvarez S.
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Complex Adaptive Systems Modeling: A multidisciplinary Roadmap

I would like to start by extending a very warm welcome from the editorial board of Complex Adaptive Systems Modeling (CASM) journal, a new and exciting SpringerOpen/BioMed Central project. This article is the opening editorial and a call for papers for CASM. It also provides a gentle introduction to CASM as well as serves as a concise multidisciplinary roadmap and survey for CASM readership. The primary goal is to assist multidisciplinary researchers with an interest in modeling complex systems in finding more about relevant helpful resources and the numerous exciting ways in which other colleague researchers use modeling approaches in their respective disciplines. Finally I also provide advice for prospective authors regarding the preparation of manuscripts in a style appropriate to the highly multidisciplinary CASM readership. It is hoped that this will help seed fruitful cross‐fertilization of ideas transgressing disciplinary boundaries.

 

Complex Adaptive Systems Modeling: A multidisciplinary Roadmap
Muaz A Niazi

Complex Adaptive Systems Modeling 2013, 1:1 http://dx.doi.org/10.1186/2194-3206-1-1


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Sistemas Complejos como instrumentos de conocimiento y transformación del mundo

Sistemas Complejos como instrumentos de conocimiento y transformación del mundo | Sistemas complejos | Scoop.it
Complejidady Economía's insight:

Miramontes, O
"Los sistemas complejos como instrumentos de conocimiento y transformación del mundo".
En Ramírez, S. (editor), Perspectivas sobre la teoría de sistemas. Centro de Investigaciones Interdisciplinarias en Ciencias y Humanidades,
UNAM-Siglo XXI, México (1999)

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Keynote - Edgar Morin - Complex thinking for a complex world

Our world is at crisis. Global challenges abound. However, they have a "dark" and a "bright" side. The dark side is the imminent danger of the breakdown of interdependent societies with the perspective of extermination of civilised human life. The bright side marks a possible entrance to a new stage of evolution of humanity, to the self-organisation of a humane world society. Cybernetics, systems research, the sciences of complexity -- all of them have the potential to endow the subjects of history with guidance and a means for mastering the current transformation.


Via Complexity Digest
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Rescooped by Complejidady Economía from CxConferences
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II Congreso Mexicano en Ciencias de la Complejidad

II Congreso Mexicano en Ciencias de la Complejidad | Sistemas complejos | Scoop.it

CMCC2012
II Congreso Mexicano de Ciencias de la Complejidad
Ciudad de México, Octubre 22-24, 2012

 

C3-2012 es un congreso clave en México para el año 2012. Busca reunir a la comunidad nacional de interesados en la investigación, docencia y práctica de los Sistemas Complejos.
El evento durará tres dias con sesiones de conferencias, mesas redondas y carteles.


Via Complexity Digest
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A Biased Review of Sociophysics

Una revisión parcial de la Sociofísica
Varios aspectos de la investigación reciente en sociofísica se revisan en breve: el modelo de Schelling como un ejemplo de la falta de cooperación interdisciplinaria, la dinámica de opinión, el combate, y las estadísticas de citas como un ejemplo de la interdisciplinariedad fuerte

 

Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.

 

A Biased Review of Sociophysics

Dietrich Stauffer

http://arxiv.org/abs/1207.6178


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How complex are cities, mathematically speaking?

How complex are cities, mathematically speaking? | Sistemas complejos | Scoop.it
How complex are cities, mathematically speaking?

Via DECUGIS Bernard
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