[Paleopsych] Eshel, Joel, Paul, and Pavel--not to mention Ted and Greg

HowlBloom at aol.com HowlBloom at aol.com
Thu Sep 1 01:59:14 UTC 2005

Pavel, Joel, Paul, and Eshel— 
See if I’ve understood the  following article correctly.   
In this cosmos things don’t  follow the sort of random spread of 
probabilities Ludwig Boltzmann believed  in.  Instead, old patterns jump from  one level 
to another, showing up in new news.   
To understand the size and nature  of the jumps, we have to understand 
something even deeper—the search strategies  with which the cosmos explores what 
Stuart Kaufman calls “possibility  space”. 
The key quote from the article  below is this one:  “if physicists can 
adequately  understand the details of this ‘exploring behaviour’, they should be 
able to  predict values of q from first principles”. 
Now please bear with me.  What I’ve been digging into for many  decades is 
the manner in which the cosmos feels out her possibilities—the search  
strategies of nature. So have Eshel Ben-Jacob, Paul Werbos, Pavel Kurakin, and  Joel 
Pavel and I, in our paper  “Conversation (dialog) model of quantum transitions
” (arXiv.org) suggest that we  may find applications all up and down the 
scale of nature to one search strategy  in particular, that used by a cloud of 
20,000 smart particles—bees. 
Power laws help us move from the  human-scale to the very big.  They  help us 
understand how patterns visible on one scale—the scale of the spiral of  
water that flushes your toilet, for example, can be scaled up to hurricanes, to  
vortex of the Red Spot on the surface of Jupiter, to hurricanes on Jupiter the  
size of thirty earths, and to the spirals of billions of stars called  
galaxies.  Power laws or their  equivalent also allow us to predict that if we give 
the cosmos another six or  seven billion years, the spirals from your toilet 
will show up in swirls of  multitudes of galaxies—they will show up in today’s 
potato-shaped,  still-embryonic galaxy clusters.   
Power laws can be used in forward  or reverse.  In addition to going  from 
the small to the very big, they can help us move from the human-scale to  the 
very small.  Power laws help us  understand how the swirl in your bathtub shows 
up in the swizzles of electrons  twisting through a channel on a 
On the level of life, we can see  search patterns at work, search patterns in 
Dennis Bray’s clusters of receptors  on a cell wall, search patterns in Eshel 
Ben-Jacobs multi-trillion-member  bacterial colonies, search patterns in Tom 
Seeley’s colonies of bees, search  patterns in E.O. Wilson’s colonies of 
ants, and search patterns in colonies of  termites.  We can see search  patterns 
in the motions of birds, and in the way these patterns have been  modeled 
mathematically in Floys (mathematically-generated flocks of carnivorous  Boids—see 
http://www.aridolan.com/ofiles/JavaFloys.html). We can see search  patterns in 
Martha Sherwood’s vampire bats, and search patterns in the areas of  my 
fieldwork--human cultural fads and fashions and the multi-generational search  
patterns of art, religion, ideology, world-views, and science. 
If search patterns are the key to  understanding the factor q, if they are 
the key to comprehending the magic  factor that scales things up and down in 
giant, discontinuous leaps, then let’s  by all means take search patterns at the 
scale of life and apply them like  hell. 
That’s exactly what Pavel Kurakin  and I have done in our paper.  And  it’s 
what I’ve done in much of my work, including in a book that’s been growing  
in the Bloom computer for fifteen years-- A Universe In Search Of Herself—The  
Case of the Curious Cosmos. 
Now the question is this.  Have I misinterpreted the material  below?  And 
even if I’ve mangled it  utterly, could an understanding of search patterns at 
one scale in the cosmos  echo the patterns at other levels big and small?  If 
the search patterns of life are  reflected in the inanimate cosmos, do the 
search patterns of life in turn  reflect the search patterns of the particles and 
processes of which they are  made?  And do the search patterns of  an organism 
reflect the search patterns of her flock, her tribe, her culture,  and of the 
total team of biomass?   
To what extent are competing  search patterns a part of the cosmic process?  
Did competing search patterns only show  up 3.85 billion years ago with the 
advent of life (assuming that the advent of  life on earth took place at the 
same time as the advent of life—if there is  any—elsewhere in the universe)?  
Are  the gaps between competing search patterns also big ones, with their own 
chasms  and jumps spaced out by their own mysterious q? 
Biomass has been probing this  planet for 3.85 billion years now, and we are 
the fingers with which she feels  out her possibilities.  But we are  also the 
fingers through which social clusters of protons 13.7 billion years old  feel 
out their future.  Is q related  to the discipline of a probing strategy? 
Retrieved August 31, 2005, from the World Wide Web  
http://www.newscientist.com/channel/fundamentals/mg18725141.700  NewScientist.com  * HOME * |NEWS *  
|JOBS  Click to Print Entropy: The  new order  * 27 August 2005 * From New 
Scientist Print  Edition. Subscribe and get 4 free issues. * Mark Buchanan  
CONSTANTINO TSALLIS has a single  equation written on the blackboard in his office. It 
looks like one of the  most famous equations in physics, but look more 
closely and it's a little bit  different, decorated with some extra symbols and 
warped into a peculiar new  form.  Tsallis, based at the  Brazilian Centre for 
Research in Physics, Rio de  Janeiro, is excited to have created this new 
equation.  And no wonder: his unassuming arrangement of symbols has stimulated 
hundreds of researchers to  publish more than a thousand papers in the past decade, 
describing strange  patterns in fluid flows, in magnetic fields issuing from 
the sun and in the  subatomic debris created in particle accelerators. But 
there is something  even more remarkable about Tsallis's  equation: it came to him 
in a daydream.  In 1985, in a classroom in  Mexico City, Tsallis was 
listening  as a colleague explained something to a student. On the chalkboard they had 
 written a very ordinary algebraic expression, pq, representing some number p 
 raised to the power q In Tsallis's line of work - describing the collective  
properties of large numbers of particles - the letter "p" usually stands for  
probability: the probability that a particle will have a particular velocity, 
 say. Tsallis stared at the formula from a distance and his mind drifted off. 
 "There were these pqs all over the board," he recalls, "and it suddenly came 
to  my mind - like a flash - that with powers of probabilities one might do 
some  unusual but possibly quite interesting physics."  The physics involved 
may be more than  quite interesting, however. The standard  means of describing 
the collective properties of large numbers of particles -  known as 
statistical mechanics - has been hugely successful for more than a  century, but it has 
also been rather limited in its scope: you can only apply it  to a narrow 
range of systems. Now, with an insight plucked out of thin air,  Tsallis may have 
changed all that.  Developed in the 19th century,  statistical mechanics 
enabled physicists to overcome an imposing problem.  Ordinary materials such as 
water, iron or glass are made of myriad atoms. But  since it is impossible to 
calculate in perfect detail how every individual atom  or molecule will move, it 
seems as if it might never be possible to understand  the behaviour of such 
substances at the atomic level.  The solution, as first suggested by the  
Austrian physicist Ludwig Boltzmann, lay in giving up hope of perfect  understanding 
and working with probabilities instead. Boltzmann argued that  knowing the 
probabilities for the particles to be in any of their various  possible 
configurations would enable someone to work out the overall properties  of the system. 
Going one step further, he also made a bold and insightful guess  about these 
probabilities - that any of the many conceivable configurations for  the 
particles would be equally probable. Deeper beauty  Boltzmann's idea works, and 
has enabled  physicists to make mathematical models of thousands of real 
materials, from  simple crystals to superconductors. But his work also has a deeper 
beauty. For a  start, it reflects the fact that many quantities in nature - 
such as the  velocities of molecules in a gas - follow "normal" statistics. That 
is, they are  closely grouped around the average value, with a "bell curve" 
distribution.  The theory also explains why, if left to  their own devices, 
systems tend to get disorganised. Boltzmann argued that any  system that can be in 
several different configurations is most likely to be in  the more spread out 
and disorganised condition. Air molecules in a box, for  example, can gather 
neatly in a corner, but are more likely to fill the space  evenly. That's 
because there are  overwhelmingly more arrangements of the particles that will 
produce the spread  out, jumbled state than arrangements that will concentrate 
the molecules in a  corner. This way of thinking led to the famous notion of 
entropy - a measure  of the amount of disorder in a system. In its most elegant 
formulation, Boltzmann's statistical mechanics, which  was later developed 
mathematically by the American physicist Josiah Willard  Gibbs, asserts that, 
under many conditions, a physical system will act so as to  maximise its entropy.  
And yet  Boltzmann and Gibbs's statistical mechanics doesn't explain 
everything: a great  swathe of nature eludes its grasp entirely. Boltzmann's guess 
about equal  probabilities only works for systems that have settled down to 
equilibrium,  enjoying, for example, the same temperature throughout. The theory 
fails in any system where  destabilising external sources of energy are at work, 
such as the haphazard  motion of turbulent fluids or the fluctuating energies 
of cosmic rays. These  systems don't follow normal statistics, but another 
pattern instead.  If you repeatedly measure the difference in  fluid velocity at 
two distinct points in a turbulent fluid, for instance, the  probability of 
finding a particular velocity difference is roughly proportional  to the amount 
of that difference raised to the power of some exponent. This  pattern is 
known as a "power law", and such patterns turn up in many other areas  of 
physics, from the distribution of energies of cosmic rays to the fluctuations  of 
river levels or wind speeds over a desert. Because ordinary statistical  
mechanics doesn't explain power laws, their atomic-level origins remain largely  
mysterious, which is why many physicists find Tsallis's mathematics so  enticing.  
In Mexico City, coming out of his reverie, Tsallis  wrote up some notes on his 
idea, and soon came to a formula that looked  something like the standard 
formula for the Boltzmann-Gibbs entropy - but with a  subtle difference. If he 
set q to 1 in  the formula - so that pq became the probability p - the new 
formula reduced to  the old one. But if q was not equal to 1, it made the formula 
produce  something else. This led Tsallis to a  new definition of entropy. He 
called it q entropy.  Back then, Tsallis had no idea what q  might actually 
signify, but the way this new entropy worked mathematically  suggested he might 
be on to something. In particular, the power-law pattern tumbles out of the  
theory quite naturally. Over the past decade, researchers have shown that  
Tsallis's mathematics seem to describe power-law behaviour accurately in a wide  
range of phenomena, from fluid turbulence to the debris created in the  
collisions of high-energy particles. But while the idea of maximising q  entropy seems 
to work empirically, allowing people to fit their data to  power-law curves 
and come up with a value of q for individual systems, it has  also landed 
Tsallis in some hot water. The new mathematics seems to work, yet no one knows what 
the q entropy really  represents, or why any physical system should maximise 
it. Degrees of  chaos  And for this reason, many  physicists remain sceptical, 
or worse. "I have to say that I don't buy it at  all," says physicist Cosma 
Shalizi of the  University of  Michigan in Ann  Arbor, who criticises the 
mathematical foundations of  Tsallis's approach. As he points out, the usual 
Boltzmann procedure for  maximising the entropy in statistical mechanics assumes a 
fixed value for the  average energy of a system, a natural idea. But to make 
things work out within  the Tsallis framework, researchers have to fix the value 
of another quantity - a  "generalised" energy - that has no clear physical 
interpretation. "I have  yet to encounter anyone," says Shalizi, "who can 
explain why this should be  natural."  To his critics, Tsallis's  success is little 
more than sleight of hand: the equation may simply provide a  convenient way 
to generate power laws, which researchers can then fit to data by  choosing the 
right value of q "My impression," says Guido Caldarelli of La  Sapienza 
University in Rome, "is that the method really just fits data by  adjusting a 
parameter. I'm not yet convinced there's new physics here."  Physicist Peter 
Grassberger of the  University of  Wuppertal in  Germany goes  further. "It is all 
nonsense," he says. "It has led to no new predictions, nor  is it based on 
rational arguments."  The problem is that most work applying Tsallis's ideas has 
simply chosen  a value of q to make the theory fit empirical data, without 
tying q to the real  dynamics of the system in any deeper way: there's nothing to 
show why these  dynamics depart from Boltzmann's picture of equal 
probabilities. Tsallis, who is  now at the Santa Fe Institute in New  Mexico, acknowledges 
this is a limitation, but suggests  that a more fundamental explanation is 
already on its way.  Power laws, he argues, should tend to arise  in "weakly 
chaotic" systems. In this kind of system, small perturbations might  not be 
enough to alter the arrangement of molecules. As a result, the system  won't 
"explore" all possible configurations over time. In a properly chaotic  system, on 
the other hand, even tiny perturbations will keep sending the system  into new 
configurations, allowing it to explore all its states as required for  
Boltzmann statistics.  Tsallis  argues that if  physicists can adequately understand 
the details of this "exploring behaviour",  they should be able to predict 
values of q from first principles. In  particular, he proposes, some as yet 
unknown single parameter - closely akin to  q - should describe the degree of chaos 
in any system. Working out its value by  studying a system's basic dynamics 
would then let physicists predict the value  of q that then emerges in its 
statistics.  Other theoretical work seems to support this possibility. For 
example, in  a paper soon to appear in Physical Review E, physicist Alberto Robledo 
of the  National Autonomous University of Mexico in Mexico  City has examined 
several classic models that physicists have used to  explore the phenomenon of 
chaos. What makes these models useful is that they  can be tuned to be more or 
less  chaotic - and so used to explore the transition from one kind of 
behaviour  to another. Using these model systems, Robledo has been able to carry out 
 Tsallis's prescription, deriving a value of q just from studying the 
system's  fundamental dynamics. That value of q then reproduces intricate power-law  
properties for these systems at the threshold of chaos. "This work shows that 
q  can be deduced from first principles," Tsallis says.  While Robledo has 
tackled theoretical  issues, other researchers have made the same point with real 
observations. In a paper just published, Leonard Burlaga  and Adolfo Vinas at 
NASA's Goddard Space Flight Center in Greenbelt, Maryland,  study 
fluctuations in the properties of the solar wind - the stream of charged  particles that 
flows outward from the sun - and show that they conform to  Tsallis's ideas. 
They have found that the dynamics of the solar wind, as  seen in changes in its 
velocity and magnetic field strength, display weak chaos  of the type 
envisioned by Tsallis. Burlaga and Vinas have also found that the  fluctuations of 
the magnetic field follow power laws that fit Tsallis's  framework with q set to 
1.75 (Physica A, vol 356, p 275).  The chance that a more comprehensive  
formulation of Tsallis's q entropy might eventually be found intrigues physicist  
Ezequiel Cohen of the Rockefeller University in New York City. "I think a good 
 part of the establishment takes an unfair position towards Tsallis's work," 
he  says. "The critique that all he does is 'curve fitting' is, in my opinion, 
 misplaced."  Cohen has also started  building his own work on Tsallis's 
foundations. Two years ago, with Christian Beck of Queen  Mary, University of 
London, he proposed an idea known as  "superstatistics" that would incorporate the 
statistics of both Boltzmann and  Tsallis within a larger framework.  In this 
work they revisited the limitation of Boltzmann's statistical  mechanics. 
Boltzmann's models cannot cope with any system in which external  forces churn up 
differences such as variations in temperature. A particle moving  through 
such a system would experience many temperatures for short periods and  its 
fluctuations would reflect an average of the ordinary Boltzmann statistics  for all 
those different temperatures. Cohen and Beck showed that such averaged  
statistics, emerging out of the messy non-uniformity of real systems, take the  
very same form as Tsallis statistics, and lead to power laws. In one striking  
example, Beck showed how the distribution of the energies of cosmic rays could  
emerge from random fluctuations in the temperature of the hot matter where 
they  were originally created.  Cohen  thinks that, if nothing else, Tsallis's 
powers of probabilities have served to  reawaken physicists to fundamental 
questions they have never quite answered.  After all Boltzmann's idea, though  
successful, was also based on a  guess; Albert Einstein disliked Boltzmann's 
arbitrary assumption of "equal  probabilities" and insisted that a proper theory of 
matter had to rest on a deep  understanding of the real dynamics of 
particles.  That understanding still eludes us, but  Tsallis may have taken us closer. 
It is possible that, in his mysterious q  entropy, Tsallis has discovered a 
kind  of entropy just as useful as Boltzmann's and especially suited to the 
real-world  systems in which the traditional theory fails. "Tsallis made the first 
 attempt to go beyond Boltzmann," says Cohen. The door is now open for others 
to  follow. Close this window Printed on Thu Sep 01 01:17:25 BST 2005 
Howard  Bloom
Author of The Lucifer Principle: A Scientific Expedition Into the  Forces of 
History and Global Brain: The Evolution of Mass Mind From The Big Bang  to the 
21st Century
Recent Visiting Scholar-Graduate Psychology Department,  New York University; 
Core Faculty Member, The Graduate  Institute
Founder:  International Paleopsychology Project; founding board member: Epic 
of Evolution  Society; founding board member, The Darwin Project; founder: The 
Big Bang Tango  Media Lab; member: New York Academy of Sciences, American 
Association for the  Advancement of Science, American Psychological Society, 
Academy of Political  Science, Human Behavior and Evolution Society, International 
Society for Human  Ethology; advisory board member: Institute for 
Accelerating Change ; executive  editor -- New Paradigm book series.
For information on The International  Paleopsychology Project, see: 
for two chapters from  
The Lucifer Principle: A Scientific Expedition Into the Forces of History,  
see www.howardbloom.net/lucifer
For information on Global Brain: The  Evolution of Mass Mind from the Big 
Bang to the 21st Century, see  www.howardbloom.net

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