DJ's Reviews > The Quark and the Jaguar: Adventures in the Simple and the Complex

The Quark and the Jaguar by Murray Gell-Mann
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's review
Apr 17, 2008

it was ok
bookshelves: popular-physics
Recommended for: anyone interested in information & complexity or an introduction ot modern physics
Read in July, 2008

Gell-Mann is a very intelligent man with wide-ranging interests but his attempts to treat so many of these interests at once really hinder ‘The Quark and The Jaguar’.

At times, this book presents fascinating and powerful new ways of looking at the world. Gell-Mann shines when he’s in his element. His introduction to complexity & randomness and complex adaptive systems is excellent and has given me a new lens to view the world through. Also, his introduction to modern physics (Gell-Mann is a Nobel Prize winner who basically built QCD, an essential piece of the current standard model) is one of the clearest I have encountered and debunks the pop culture misinterpretations of quantum mechanics that pervade most discussions.

At other times, I felt like I was in one of those dreams where you’re sitting in class minding your own business and, suddenly… your pants are gone! In trying to jump from interest to interest so often, Gell-Mann has to drop introductions to the fundamental background needed to understand what he’s discussing, leading to confusing situations in which the reader has no idea where they are and how they got there.

There are certainly interesting nuggets here but this book could do with some editing.

Note: 2 stars doesn’t mean I thought this book was “bad”. I follow Goodreads convention and 2 stars means “it was ok”. If I believed in inflated scores for every book, it’d be on Amazon right now.

Book Notes

* Defining Complexity
o coarse/fine grain - level of detail
o length of description - possible measure
o context dependent - f(vocab, shared knowledge)
o algorithmic info content (AIC) - shortest program that produces a string
+ compressibility - inverse of randomness
+ AIC = measure of randomness, not complexity
* Meaning of Random
1. incompressible (defined by result)
2. generated by chance (defined by process)
o let’s call 1 random and 2 stochastic
o pseudorandom - generated using chaotic or messy process to imitate chance
* Complex Adaptive Systems
o Method
+ old data –> construct theory
+ present data –> predict
+ new data –> test & revise
o compress regularities in observation into schema
o revise defn. of complexity by length of schema (since only regularities produce schema)
o external complexity - book description (good approximation but subject to academic tone, audience experience, etc)
o internal effective complexity - brain representation [in native speaker] (better approximation as it is truer to the source)
o usefulness = f(observer skill & size of observed set)
o regularities identified by class (no algorithm can identify all regularities - Godel?)
o high complexity = balance between order & disorder and simple & random (mid-range AIC)
o species learning - mutations (variation) present before challenge
o brain learning - ideas (variation) created in response to challenge
* More on Complexity & Randomness
o self-organized criticality - natural attraction of a system to a critical value
o depth - difficulty of moving from compressed program/schema –> full description of result
o crypticity - difficulty of moving from full description of result –> compressed program/schema
o individuality - bits to describe object > bits to enumerate group
* Intro to Modern Physics
o bootstrap principle - assume particles are already there and they give rise to and sustain themselves (*like recursive programming in Scheme!)
o QCD differs from QED because gluons are electrically charged and interact with each other unlike photons (so color force doesn’t die with distance and traps quarks)
o photons/gravitons transfer energy/motion while W+- bosons seem only to transform particles into their antiparticles
o charged particles interact through photons
o colored particles interact through gluons
o flavored particles interact through W bosons
o weak force (W bosons) change flavor AND charge (since W bosons are electrically charged)
o renormalization - isolating a portion of a theory to stand on its own as a good approximation (can lead to arbitrary constants dependent upon rest of theory)
o superpartners - fermions for bosons & bosons for fermions
o supergap - mass difference between superpartners caused by SSB
o force unity - extrapolate experiments and gluonic, EM, and weak interactions almost converse at high energies (early BB perhaps?)
o action [=] energy * time
* Time
o frozen accident - chance events with many long-term consequences
+ more of universe’s AIC and effective complexity results from accidents than laws
+ can lead to SSB when chance occurrence is one among a symmetrical set of possibilities
+ provide regularity –> higher effective complexity
+ responsible for many environmental & biological conditions
o coarse-grained history - class of all fine-grained histories that meet its class reqs (equivalence of properties in focus, set of all possible alternatives for properties ignored)
+ ignored properties are ’summed over’
+ when interference terms disappear, histories ‘decohere’
+ asymmetry between past & future:
# radiation (energy flows out)
# records (only of past)
# entropy (energy of macrostate = bits to represent a microstate)
* Biology, Evolution, and Fitness
o evolution (intermingling of species & environment) can be modeled as a movement toward equilibrium of information (like the intermingling of hot & cold gases)
o gateway events - dramatic biological events that open new options (photosynthesis, eukaryotes, etc)
o fitness landscape - topological representation of biological fitness (as depth)
+ local minima similar to potential wells (false optimization)
+ noisy, random path allows movement in/out of wells
+ basin of attraction - watershed for a well
o inclusive fitness - factors in survival/reproduction of related organisms, weighting the most related most heavily (related to the selfish gene)

* How does the nuclear force arise from the color force?
* How does gluon interaction result in the color force not dying with distance?
* Do W bosons transfer a ‘force’ or just transform particles to antiparticles?
* What makes the fundamental units fundamental? (i.e. fundamental length, mass, etc)
* What is Hawking’s ‘initial condition of the universe’ that Gell-Mann repeatedly refers to?
* Has anyone made a program that evolves its strategy intelligently based on a predictive brain algorithm?
* What about a system that meta-evolves its strategy (i.e. evolves it process for evolving)? Perhaps it shifts from neural net to genetic algorithm, etc.

* I’m still rooting for Einstein’s ‘hidden variables’ alternative to QM
* Complexity is not a well-defined idea but its a very alluring topic and this offers a nice framework to begin thinking about it
* ‘Fitness landscapes’ are an incredibly fun way to look at biology through the lens of someone trained in physics but show how reliant we are on space for our models and analogies. This may be a fault for certain problems but heck, I’m a sucker for geometric interpretations.
* The deeper you go, the simpler & more elegant physics gets
* I still don’t understand entropy nor am I convinced of the second law. I will (skeptically) read more.
* Frozen accidents are ubiquitous mysteries peppered throughout our world (and identifying them is a great way to entertain yourself).
* Complex adaptive schema are very powerful and should be a fun thing to toy with when I improve my programming.
* Coarse-graining is another ubiquitous principle that I’ve overlooked. Graining is a built-in assumption that we make at all times and must be considered in any analysis.
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