Complexity Science Digest

11-3-2012 11-02-44 AM

Strange Attractors:
Creating Patterns in Chaos


Complexity Science Digest

Dawn R. Gilpin, PhD
Arizona State University


Detecting Causality in Complex Ecosystems

George Sugihara, Robert May, Hao Ye, Chih-hao Hsieh, Ethan Deyle, Michael Fogarty, Stephan Munch Science 26 October 2012:

Vol. 338 no. 6106 pp. 496-500

Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. We introduce a method, based on nonlinear state space reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not covered by the current Granger causality paradigm). The approach is illustrated both by simple models (where, in contrast to the real world, we know the underlying equations/relations and so can check the validity of our method) and by application to real ecological systems, including the controversial sardine-anchovy-temperature problem.


Spontaneous network formation among cooperative RNA replicators

Nilesh Vaidya, Michael L. Manapat, Irene A. Chen, Ramon Xulvi-Brunet, Eric J. Hayden & Niles Lehman Nature 491, 72 77 (01 November 2012)

The origins of life on Earth required the establishment of self-replicating chemical systems capable of maintaining and evolving biological information. In an RNA world, single self-replicating RNAs would have faced the extreme challenge of possessing a mutation rate low enough both to sustain their own information and to compete successfully against molecular parasites with limited evolvability. Thus theoretical analyses suggest that networks of interacting molecules were more likely to develop and sustain life-like behaviour. Here we show that mixtures of RNA fragments that self-assemble into self-replicating ribozymes spontaneously form cooperative catalytic cycles and networks. We find that a specific three-membered network has highly cooperative growth dynamics. When such cooperative networks are competed directly against selfish autocatalytic cycles, the former grow faster, indicating an intrinsic ability of RNA populations to evolve greater complexity through cooperation. We can observe the evolvability of networks through in vitro selection. Our experiments highlight the advantages of cooperative behaviour even at the molecular stages of nascent life.


Stability analysis of financial contagion due to overlapping portfolios

Fabio Caccioli, Munik Shrestha, Cristopher Moore, J. Doyne Farmer

Common asset holdings are widely believed to have been the primary vector of contagion in the recent financial crisis. We develop a network approach to the amplification of financial contagion due to the combination of overlapping portfolios and leverage, and we show how it can be understood in terms of a generalized branching process. By studying a stylized model we estimate the circumstances under which systemic instabilities are likely to occur as a function of parameters such as leverage, market crowding, diversification, and market impact.

Although diversification may be good for individual institutions, it can create dangerous systemic effects, and as a result financial contagion gets worse with too much diversification. Under our model there is a critical threshold for leverage; below it financial networks are always stable, and above it the unstable region grows as leverage increases.

The financial system exhibits “robust yet fragile” behavior, with regions of theparameter space where contagion is rare but catastrophic whenever it occurs. Our model and methods of analysis can be calibrated to real data and provide simple yet powerful tools for macroprudential stress testing.


Guaranteeing global synchronization in networks with stochastic interactions

Johannes Klinglmayr et al 2012 New J. Phys. 14 073031

We design the interactions between oscillators communicating via variably delayed pulse coupling to guarantee their synchronization on arbitrary network topologies. We identify a class of response functions and prove convergence to network-wide synchrony from arbitrary initial conditions. Synchrony is achieved if the pulse emission is unreliable or intentionally probabilistic. These results support the design of scalable, reliable and energy-efficient communication protocols for fully distributed synchronization as needed, e.g., in mobile phone networks, embedded systems, sensor networks and autonomously interacting swarm robots.


The Implications of Interactions for Science and Philosophy

Carlos Gershenson



Reductionism has dominated science and philosophy for centuries.

Complexity has recently shown that interactions which reductionism neglects are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.


Computing Nature: A Network of Networks of Concurrent Information Processes

Gordana Dodig Crnkovic, Raffaela Giovagnoli

This text presents the research field of natural/unconventional computing as it appears in the book COMPUTING NATURE. The articles discussed consist a selection of works from the Symposium on Natural Computing at AISB-IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. The COMPUTING NATURE is about nature considered as the totality of physical existence, the universe. By physical we mean all phenomena, objects and processes, that are possible to detect either directly by our senses or via instruments. Historically, there have been many ways of describing the universe (cosmic egg, cosmic tree, theistic universe, mechanistic

universe) while a particularly prominent contemporary approach is computational universe, as discussed in this article.


Reconstructing complex networks from time series

Zoran Levnajic

Novel method of reconstructing the topology of dynamical networks from time series is proposed. By examining the variable–derivative correlation of the network node pairs, we derive a simple equation yielding the network adjacency matrix. Our key assumption is that the intra-network interaction functions are known. We illustrate the method on a simple example, and discuss the dependence of the reconstruction on the dynamical properties of time series. Our method is applicable to any weighted or directed network, in principle allowing for precision to be estimated.


Desynchronizing Networks Using Phase Resetting

J. Borresen, D. Broomhead

Understanding complex systems which exhibit desynchronization as an emergent property should have important implications, particularly in treating neurological disorders and designing efficient communication networks. Here were demonstrate how, using a system similar to the pulse coupling used to model firefly interactions, phase desynchronization can be achieved in pulse coupled oscillator systems, for a variety of network architectures, with symmetric and non symmetric internal oscillator frequencies and with both instantaneous and time delayed coupling.


The Emergence of Organizations and Markets

John F. Padgett, Walter W. Powell

Princeton University Press (October 14, 2012) See it on


, via CxBooks (

The social sciences have sophisticated models of choice and equilibrium but little understanding of the emergence of novelty. Where do new alternatives, new organizational forms, and new types of people come from? Combining biochemical insights about the origin of life with innovative and historically oriented social network analyses, John Padgett and Walter Powell develop a theory about the emergence of organizational, market, and biographical novelty from the coevolution of multiple social networks. They demonstrate that novelty arises from spillovers across intertwined networks in different domains. In the short run actors make relations, but in the long run relations make actors.

This theory of novelty emerging from intersecting production and biographical flows is developed through formal deductive modeling and through a wide range of original historical case studies. Padgett and Powell build on the biochemical concept of autocatalysis–the chemical definition of life–and then extend this autocatalytic reasoning to social processes of production and communication. Padgett and Powell, along with other colleagues, analyze a very wide range of cases of emergence. They look at the emergence of organizational novelty in early capitalism and state formation; they examine the transformation of communism; and they analyze with detailed network data contemporary science-based capitalism: the biotechnology industry, regional high-tech clusters, and the open source community.


When Networks Network

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When networks depend on other networks, such as a communications network that relies on a power grid, failure can cascade back and forth between the two. This behavior may explain sudden breakdowns in interacting systems. Thus, the effects of an attack on a single node can reduce an  bernetwork that starts with 12 operating nodes to just four.

Once studied solo, systems display surprising behavior when they interact.


Dawn R. Gilpin, PhD
Walter Cronkite School
Journalism & Mass Communication
Arizona State University @drgilpin

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