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NIMBioS will host an Investigative Workshop on Information and Entropy Topic: Information and entropy in biological systems Meeting dates: April 810, 2015 Location: NIMBioS at the University of Tennessee, Knoxville Organizers: John Baez, Mathematics, Univ. of California, RiversideMarc Harper, Educational and biotechnology consultantJohn Harte, Environmental Science, Policy and Management, Univ. of California, Berkeley
IBM and http://IBMblr.Tumblr.com celebrate the life of Benoit B. Mandelbrot, IBM Fellow Emeritus and Fractal Pioneer. In this final interview shot by filmmaker Erol Morris, Mandelbrot shares his love for mathematics and how it led him to his wondrous discovery of fractals. His work lives on today in many innovations in science, design, telecommunications, medicine, renewable energy, film (special effects), gaming (computer graphics) and more.
Via Bernard Ryefield, Complexity Digest
The fractal dimension (FD) image is generated by considering each pixel in the original CT image as a single fractal dimension estimated from its 7x7 neighbours. The FD generated image remarkably enhances the tissue ...
It’s hard to believe it has been three decades since a group from LANL devised a plan that would revolutionize science.
The PyCX Project aims to develop an online repository of simple, crude, yet easytounderstand Python sample codes for dynamic complex systems simulations, including iterative maps, cellular automata, dynamical networks and agentbased models.
Via Hiroki Sayama, Complexity Digest, Complexity Institute
The Genetic and Evolutionary Computation Conference (GECCO 2014) will present the latest highquality results in genetic and evolutionary computation. Topics include: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, memetic algorithms, hyper heuristics, realworld applications, evolutionary machine learning, evolvable hardware, artificial life, adaptive behaviour, ant colony optimization, swarm intelligence, biological applications, evolutionary robotics, coevolution, artificial immune systems, and more. July 1216, 2014, Vancouver, BC, Canada http://www.sigevo.org/gecco2014/
Via Complexity Digest
If the truth be told, few physicists have ever really felt comfortable with quantum theory. Having lived with it now for more than a century, they have managed to forge a good working relationship; physicists now routinely use the mathematics of quantum behaviour to make stunningly accurate calculations about molecular structure, highenergy particle collisions, semiconductor behaviour, spectral emissions and much more. But the interactions tend to be strictly formal. As soon as researchers try to get behind the mask and ask what the mathematics mean, they run straight into a seemingly impenetrable wall of paradoxes. Can something really be a particle and a wave at the same time? Is Schrödinger's cat really both alive and dead? Is it true that even the gentlest conceivable measurement can somehow have an effect on particles halfway across the Universe?
Physics: Quantum quest Philip Ball http://www.nature.com/news/physicsquantumquest1.13711
Via Complexity Digest
New York Times A Strange Computer Promises Great Speed New York Times Ray Johnson, Lockheed's chief technical officer, said his company would use the quantum computer to create and test complex radar, space and aircraft systems.
Via Alejandro J. Alvarez S.
Scientific American (blog) Stephen Hawking's advice for twentyfirst century grads: Embrace complexity Scientific American (blog) Hawking replied that in his opinion the twentyfirst century would be the “century of complexity”.
Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization, but no formal physical relationship between them has yet been established. Here, we explicitly propose a first step toward such a relationship in the form of a causal generalization of entropic forces that we find can cause two defining behaviors of the human “cognitive niche”—tool use and social cooperation—to spontaneously emerge in simple physical systems. Our results suggest a potentially general thermodynamic model of adaptive behavior as a nonequilibrium process in open systems. Causal Entropic Forces A. D. WissnerGross and C. E. Freer Phys. Rev. Lett. 110, 168702 (2013) http://dx.doi.org/10.1103/PhysRevLett.110.168702
Via Complexity Digest
RABBIT provides an easy way to explore natural phenomena such as pattern formation, selforganization, emergence, nonlinearity. Rabbit helps architects and designers to analyze and integrate these models of organization in their own designs.
Via Ignacio López Busón

TOMAEQ14: Topological Matter out of Equilibrium Focus Workshop — 27  29 March 2014 Max Planck Institute for the Physics of Complex Systems Dresden, Germany Much of the work on nonequilibrium statistical mechanics has relied on the notion of a local order parameter, absent in topological phases. Conversely, studies of topological phenomena have focused on equilibrium and groundstate properties. The intersection of these fields remains largely uncharted territory.
This workshop brings together theorists from both groups, as well as experimentalists studying dynamical phenomena in a variety of systems, covering topics such as topological phenomena in driven systems, hydrodynamic descriptions of phases with emergent gauge fields, ultrafast and inelastic spectral probes of quantum matter, the development of numerical methods, and finally potential experiments in the solid state and ultracold atomic gases. http://www.pks.mpg.de/~tomaeq14/announce.html
Shuichi Kinoshita, "Pattern Formations and Oscillatory Phenomena" English  ISBN: 0123970148  2013  280 pages  PDF  31 MB Patterns and their formations appear throughout nature, and are studied to.
New Complexity MOOC Started iProgrammer Introduction to Dynamical Systems and Chaos, the second course to be offered through the Santa Fe Institute's Complexity Explorer project started on January 6th and enrollment is still open.
We give exact formulae for a wide family of complexity measures that capture the organization of hidden nonlinear processes. The spectral decomposition of operatorvalued functions leads to closedform expressions involving the full eigenvalue spectrum of the mixedstate presentation of a process's epsilonmachine causalstate dynamic. Measures include correlation functions, power spectra, pastfuture 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 onedimensional 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
Via Complexity Digest, Complejidady Economía
ECAL 2013, the twelfth European Conference on Artificial Life, presents the current state of the art of a mature and autonomous discipline collocated at the intersection of a theoretical perspective (the scientific explanations of different levels of life organizations, e.g., molecules, compartments, cells, tissues, organs, organisms, societies, collective and social phenomena) and advanced technological applications (bioinspired algorithms and techniques to buildingup concrete solutions such as in robotics, data analysis, search engines, gaming). Advances in Artificial Life, ECAL 2013 Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems Edited by Pietro Liò, Orazio Miglino, Giuseppe Nicosia, Stefano Nolfi and Mario Pavone http://mitpress.mit.edu/books/advancesartificiallifeecal2013
Via Complexity Digest
The hallmark of deterministic chaos is that it creates informationthe rate being given by the KolmogorovSinai metric entropy. Since its introduction half a century ago, the metric entropy has been used as a unitary quantity to measure a system's intrinsic unpredictability. Here, we show that it naturally decomposes into two structurally meaningful components: A portion of the created informationthe ephemeral informationis forgotten and a portionthe bound informationis remembered. The bound information is a new kind of intrinsic computation that differs fundamentally from information creation: it measures the rate of active information storage. We show that it can be directly and accurately calculated via symbolic dynamics, revealing a hitherto unknown richness in how dynamical systems compute.
Via Bernard Ryefield, John Symons
Ever since Darwin a great deal of the conceptual history of biology may be read as a struggle between two philosophical positions: reductionism and holism. On the one hand, we have the reductionist claim that evolution has to be understood in terms of changes at the fundamental causal level of the gene. As Richard Dawkins famously put it, organisms are just ‘lumbering robots’ in the service of their genetic masters. On the other hand, there is a long holistic tradition that focuses on the complexity of developmental systems, on the nonlinearity of gene– environment interactions, and on multilevel selective processes to argue that the full story of biology is a bit more complicated than that. Reductionism can marshal on its behalf the spectacular successes of genetics and molecular biology throughout the 20th and 21st centuries. Holism has built on the development of entirely new disciplines and conceptual frameworks over the past few decades, including evodevo and phenotypic plasticity. Yet, a number of biologists are still actively looking for a way out of the reductionism–holism counterposition, often mentioning the word ‘emergence’ as a way to deal with the conundrum. This paper briefly examines the philosophical history of the concept of emergence, distinguishes between epistemic and ontological accounts of it, and comments on conceptions of emergence that can actually be useful for practising evolutionary biologists. Between holism and reductionism: a philosophical primer on emergence Massimo Pigliucci Biological Journal of the Linnean Society (2013) http://philpapers.org/rec/PIGBHA
Via Complexity Digest
A few years ago, Hawking was asked what he thought of the common opinion that the twentieth century was that of biology and the twentyfirst century would be that of physics. Hawking replied that in his opinion the twentyfirst century would be the “century of complexity”. That remark probably holds more useful advice for contemporary students than they realize since it points to at least two skills which are going to be essential for new college grads in the age of complexity: statistics and data visualization.
Via Complexity Digest, Eugene Ch'ng
Chaos theory deals with the description of motion (in a general sense) which cannot be predicted in the long term although produced by deterministic system, as well exemplified by meteorological phenomena. It directly comes from the Lunar theory  a threebody problem  and the difficulty encountered by astronomers to accurately predict the longterm evolution of the Moon using "Newtonian" mechanics. Henri Poincare's deep intuitions were at the origin of chaos theory. They also led the meteorologist Edward Lorenz to draw the first chaotic attractor ever published. But the main idea consists of plotting a curve representative of the system evolution rather than finding an analytical solution as commonly done in classical mechanics. Such a novel approach allows the description of population interactions and the solar activity as well. Using the original sources, the book draws on the history of the concepts underlying chaos theory from the 17th century to the last decade, and by various examples, show how general is this theory in a wide range of applications: meteorology, chemistry, populations, astrophysics, biomedicine, etc.
Via Complexity Digest, Eugene Ch'ng
Call it the ultimate nature documentary. Scientists have recorded atomic motions in real time, offering a glimpse into the very essence of chemistry and biology at the atomic level.
Via ComplexInsight
27th  29th June 2013 Warszawa, Poland Complex systems are pervasive in many fields of science and we encounter them everyday and everywhere in our life. Their examples include financial markets, highway transportation networks, telecommunication networks, human economies, social networks, immunological systems, living organisms, ant colonies, ect. The key feature of a complex system is that it is composed of large number of interconnected and interacting entities exhibiting much richer dynamical properties on global scale than they could be inferred from the properties and behaviors of its individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. An important part of these interdisciplinary studies forms discrete modeling. These models can be seen as the simplest laboratories to study phenomena exhibited by complex systems like selforganization processes, pattern formation, cooperation, adaptation, competition, attractors, or multiscaling phenomena. The objective of this conference is to bring together researchers working on discrete modeling of complex systems and to provide a forum for exchange of ideas and presentation of results of their research.
Via Complexity Digest
