Scientists describe technique for extracting hierarchical structure of networks
May 1st, 2008Networks -- used throughout the sciences in the study of biological, technological, and social complexity -- can often be too complex to visualize or understand.
In a May 1 Nature paper, “Hierarchical structure and the prediction of missing links in networks,” Santa Fe Institute (SFI) researchers Aaron Clauset, Cristopher Moore, and Mark Newman show that many real-world networks can be understood as a hierarchy of modules, where nodes cluster together to form modules, which themselves cluster into larger modules -- arrangements similar to the organization of sports players into teams, teams into conferences, and conferences into leagues, for example.
This hierarchical organization, the researchers show, can simultaneously explain a number of patterns previously discovered in networks, such as the surprising heterogeneity in the number of connections some nodes have, or the prevalence of triangles in a network diagram. Their discovery suggests that hierarchy may, in fact, be a fundamental organizational principle for complex networks.
Unlike much previous work in this area, Clauset, Moore, and Newman propose a direct but flexible model of hierarchical structure, which they apply to networks using the tools of statistical physics and machine learning.
To demonstrate the practical utility of their model, they analyze networks from three disparate fields: the metabolic network of the spirochete Treponema pallidum (the bacteria that causes syphilis), a network of associations between terrorists, and a food web of grassland species. Even when only half of the connections in these networks were shown to their algorithm, the researchers found that hierarchical structure can predict missing connections with an accuracy of up to 80 percent.
“Many networks, particularly those in the biological sciences, are not well understood,” says Clauset, an SFI Postdoctoral Fellow. "But hierarchy offers a way to understand their large-scale organization and, from this, predict what interactions we might have missed.”
Source: Santa Fe Institute
Jun 17, 2009 |
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The system of 1D network behavior of foam, which means, every energy wave makes the system more dense temporarily and it spreads like less or more dense blob (wave packet) through foamy environment (the soap foam gets more dense during shaking). By AWT this simple mechanism results into particle-wave duality, mass/energy equivalence and all quantum mechanics phenomena.
http://superstrun...foam.gif
The idea, the neural network is behaving like quantum system is not very new, it was ad-hoced by Pribram and elaborated by Sir Penrose later. It basically means, electrochemical waves can circulate through neural network like quantum wave and it can exists here like mechanical objects, which can even exhibit an inertial action at the distance. Albeit this idea is still quite speculative, it fits perfectly many paranormal phenomena like telepathy, telekinesis, etc. But we know about some stable brain wave already, as they realize a internal clock for time interval estimation for us.
At the moment, the quantum character of brain waves will be confirmed, then the hiearchical structure is provided authomatically, because the dense wave packets in the foam can behave like independent system of particles, which can make another generation of foamy fluctuations and more complex nested structures by their true nature. By another words, this simple model can explain the hiearchical structure of human conciousness by the same way, like hiarchical structure of observable reality. We can say, the quantum foam of vacuum is behaving like neural network and vice-versa.
A) It's "an aether" although it's spelled ether.
B) Professor Penrose is not referred to as Sir Penrose, or Penny Henny, or Hey Jimbo.
http://www.britan...-Penrose
Professor is the name of occupation, which you can change anytime over life. Do you prefer to be titled as a Floor manager Jimbo or Rabbit feeder Henny?
I don't think so.
The "quantum" denomination means "stuff, whose density increases proportionally with energy density". Which is basically an insintric property of every foam, therefore the word "quantum" is redundant here.