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Study Finds Similar Structures In the Universe, Internet, and Brain
SternisheFan writes "The structure of the universe and the laws that govern its growth may be more similar than previously thought to the structure and growth of the human brain and other complex networks, such as the Internet or a social network of trust relationships between people, according to a new study. 'By no means do we claim that the universe is a global brain or a computer,' said Dmitri Krioukov, co-author of the paper, published by the Cooperative Association for Internet Data Analysis (CAIDA), based at the San Diego Supercomputer Center (SDSC) at the University of California, San Diego.'But the discovered equivalence between the growth of the universe and complex networks strongly suggests that unexpectedly similar laws govern the dynamics of these very different complex systems,' Krioukov noted."
I have learned after studying many differing fields of science and engineering, that as you master one field you gain insight into many others. There are certain patterns of organization that repeat throughout nature, and mimicked by man, and if you study anything long enough you are certain to see these patterns. The more you learn, the easier it becomes to learn more because natural things are mostly variations on a finite set of themes that, whether you are aware of them or not, you will discover them and from that point forward, notice them much more quickly.
This is one example. There are many more.
#fuckbeta #iamslashdot #dicemustdie
Maybe this is just because we use the same neural mechanisms we think with to phrase scientific theories and build models of networks? Just a thought.
Myu:
Those repeating patterns are signs of the same math in the background. Sadly, with most mathemathicians doing more abstract work the aren't many who study them. Theoreticists try to fill the void left by the mathematicians and they do a goo job but most of them can't really think outside of their own field.
Come on...we have all read the book. This is not news! :-)
#find
Just yesterday I read this 2007 review of Hofstadter's Strange Loop by Gardner, and it starts
When I read this I thought, as much as I admire Martin Gardner, what a stupid thing to say. How can a galaxy, i.e. something that contains solar systems that contain at least one biosphere that contains billions of human brains, be less complex than a human brain. This assertion could only be true if you use some measure of complexity that discounts smaller dimensions, that regards complexity only on the outer layers of something. Now I see he might be wrong even on the galactic level.
There are certain constraints for the most efficient transfer of energy. Systems designed or evolved to take advantage of more efficient designs should exhibit similarities.
If video games influenced behavior the Pac Man generation would be eating pills and running away from their problems.
Maybe this is just because we use the same neural mechanisms we think with to phrase scientific theories and build models of networks? Just a thought.
If you look at enough phenomena, and generalize the description adequately, you'll find equivalences in a variety of strange places. The XKCD strip from friday is a good example. Also, If I see a picture of Jesus in my toast, can I get funding for a study? Seems to be the same "phenomena" at work.
- Nec Impar Pluribus, or so I'm told.
...which, when you think about it, doesn't mean there isn't a conscious force at work trying to brute-force a recipe for life, it just means we don't know either way. Personally, I like the image of a deity who is analogous to a frustrated graduate student trying to grow a crystal for X-ray diffraction.
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!
I'm going to have to look up the original paper published by Krioukov, but what was mentioned in the article itself is not news. I imagine this is a consequence of Krioukov trying to explain his findings in laymen's terms.
What the article actually says is a pretty basic exposition of the findings of network science and complex systems theory over the past few years. For those interested in but unfamiliar with these matters, I recommend a volume written a couple of years ago by the physicist Albert-László Barabási called Linked: The New Science of Networks . It is written for a wide audience and is a very readable introduction to the subject. Barabási's based argument is that these common network patterns we see in so many environments is a consequence both growth and preferential attachment in systems. Of course, growth and preferential attachment are going to be present in biological and social systems, as well as things like computer networks, and this is at the heart of why we see similar patterns forming (esp. scale-free topologies).
As a historian, I find the findings of network science as its been applied to social systems particularly useful. It helps to explain societal changes in ways that older theories of history, whether deriving from Marxian, Annaliste, Weberian, or other schools of thought, would have difficulty. Further, the study of networks and complex systems is inherently interdisciplinary--and this in a refreshingly honest way rather than the mere "interdisciplinarity" rhetoric that's been present in the academy over the years. For those interested in the application of network science to the social sciences, there is a very nice collection of seminal articles for the field edited by Gernot Grabher and Walter Powell.
What's funny is that the anthropic principle by definition doesn't have much meaning. You can restate it as "the universe is the way we see it, because we are seeing it be that way."
The weak anthropic principle always boils down to simple tautology, while the strong anthropic principle flys in the face of biology and works out to puddle thinking. The universe isn't tuned for us, we tuned ourselves for living in the universe through evolution.
Hectice, baby, Mercator says hello to you
The article is disappointingly vague and hand-wavy. Either the science is bullshit, or this summary is. Given that it's from India, I am leaning towards guessing the former; there's a lot of great research that happens in the country, but there's also a lot of pseudoscience that happens that's designed to give warm fuzzies to Indian nationalists who think they can undo the horrors of colonialisation and recapture national pride by beating the drum of "Vedic Math". Some of their flashier salesmen make it to the US and sell it to deluded new-agers and the other uneducated, portraying it as exotic deep knowledge "from the East".
I find it hard to believe that claims like this are supportable as good science at this point.
For every problem, there is at least one solution that is simple, neat, and wrong.
ok, i don't know if anyone else has spotted this, but there's a link between avogadro's constant, background radiation, and golden mean ratio.
take the background radiation (number of hydrogen atoms per square metre). divide by golden mean ratio cubed. invert. the number, completely coincidentally, comes out to around 6.023e23.
amazing, huh?
Joking aside, there's actually some truth to this.
Turns out complex systems with a scale-free topology (the node density of which follows a power law rather than a gaussian function), of the kind we find in ecosystems, power-grids, computer networks, DNA, etc., all have similar strengths and vulnerabilities. Unlike random distributions, scale-free topologies are highly resistant to random failure: i.e. random deaths of animals of different sorts do not cause an ecosystem failure or random power stations failing does not necessarily cause a grid to collapse. This is what network and complex systems theorists call robustness. Scale-free topologies are, however, very vulnerable to directed attacks. Turns out certain creatures occupy more important spaces in ecosystems than others (they're hubs, with a high density of connections). Kill these off and an entire ecosystem can collapse. Likewise, hit certain power stations with high density of connections and you'll see cascading failures. A few random genes are damaged, chances are that a creature will survive and reproduce without problems. Screw around with the TP53 gene in humans, however, and expect some nasty results.
Finding similarities in abstractions is what humans do. If humans can describe something based on patterns that humans are capable of processing, then we will probably find them elsewhere! Abstraction doesn't give us mystical powers that allow us to divine the "true nature" of the universe (let alone understand what that questions means).
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