Statistical Mechanics: Entropy, Order Parameters and Complexity (Oxford Master Series in Physics) (Paperback)

by James P. Sethna (Author) "What is statistical mechanics?..." (more)
Key Phrases: Monte Carlo, Christopher Myers, Big Bang (more...)

Editorial Reviews

Review

"It would take quite a long time to list all the interesting subjects treated in this textbook, but overall, this is a very good starting point for an undergraduate student who is interested in pursuing a career in research and wants to have a global idea of the different problems that are currently developed in laboratories."--Mathematical Reviews
"Sethna's book provides am important service to students who want to learn modern statistical mechanics."-- Physics Today
"An extremely intelligent and elegant introduction to fundamental concepts, well suited for the beginning graduate level."--William Gelbart, University of California at Los Angeles
"The author's style, although quite concentrated, is simple to understand, and has many lovely visual examples to accompany formal ideas and concepts, which makes the exposition live and intuitively appealing."--Journal of Statistical Physics


Product Description
In each generation, scientists must redefine their fields: abstracting, simplifying and distilling the previous standard topics to make room for new advances and methods. Sethna's book takes this step for statistical mechanics--a field rooted in physics and chemistry whose ideas and methods are now central to information theory, complexity, and modern biology. Aimed at advanced undergraduates and early graduate students in all of these fields, Sethna limits his main presentation to the topics that future mathematicians and biologists, as well as physicists and chemists, will find fascinating and central to their work. The amazing breadth of the field is reflected in the author's large supply of carefully crafted exercises, each an introduction to a whole field of study: everything from chaos through information theory to life at the end of the universe.

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Product Details

• Paperback: 376 pages
• Publisher: Oxford University Press, USA; illustrated edition edition (June 1, 2006)
• Language: English
• ISBN-10: 0198566778
• ISBN-13: 978-0198566779
• Product Dimensions: 9.6 x 7.4 x 0.9 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)
• Average Customer Review: 4.3 out of 5 stars See all reviews (7 customer reviews)
• Amazon.com Sales Rank: #499,508 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

43 of 44 people found the following review helpful:

4.0 out of 5 stars Terrific breadth, but many grains of salt needed, June 17, 2006

By	A. J. Sutter (Tokyo, Japan) - See all my reviews (TOP 1000 REVIEWER)    (REAL NAME)

I haven't yet had a chance to read this book from cover to cover. However, after several hours with it, some of its strengths and weaknesses became evident. Many of these complement each other.

It covers an exciting range of contemporary applications -- take a look at the table of contents. The problems are long, discursive, and even more intriguing than the main text, covering topics like the cosmic microwave background, origami microstructures, Langevin equations, snowflakes, biochemical reaction rates and NP-completeness. The book is rich in illustrations, and in footnotes that give an informal commentary on the main text.

One downside is that, being so wide, the coverage is also a bit thin in places. Many of the most interesting contemporary topics, such as the statistical mechanics of networks, are covered *only* in exercises. Thermodynamics is dismissed in less than 10 pages in the middle of the book, owing to that subject's being "cluttered" with a "zoo of partial derivatives, transformations and relations."

The exercises look to be more fun and tempting than usual in books on this subject. So it's a definite bummer that the book neither includes answers or hints, nor states problems in closed form ("Show that this stuff = X"). The book's web site contains only some hints for computational exercises, plus a bunch of additional problems (again, without answers). If you're interested in self-study, this tease is frustrating - an automatic one-star deduction.

There's more good news/bad news with the author's aim to be relevant to fields outside traditional physics -- e.g. in econophysics and social science. This certainly makes the book up-to-date and attractive, and was one of the reasons I bought it. But applying physics to social science is a tricky business. There's a couple hundred years of failed attempts, because people blithely modeled stuff without thinking enough about the limits within which such an analogy might be appropriate. And many who do think about those limits when deriving a model often forget about them when applying it.

An example is the Black-Scholes model of option pricing. The model's results are "simply wrong" (B. Mandelbrot). Its assumptions about volatility and the structure of the option contract aren't empirically justified. Its blind application contributed to the 1987 stock market break. And the investment fund run by one of its Nobel-laureate inventors went bust in flames in 1998. In this book, there's an exercise that walks you through some of the underlying concepts of Black-Scholes (pp. 32-33). But the author only praises the model, without so much as a footnote mentioning its darker side.

Even when doing "traditional" physics, one ignores philosophical issues at one's peril. A lot of the great physicists of the past century weren't being stupid to fret over them. On the other hand, there are lots of folks like my QM professor in the 1970s, who explained that the only reason Bohr, Heisenberg and Einstein discussed philosophy was that they didn't understand QM, "but today we understand it very well, so we don't need to worry about that stuff."

Unfortunately, this book continues that gung-ho, what-me-worry tradition. A disappointing example is the discussion of information and entropy (pp. 85 ff). The author states that interpreting entropy "not as a property of the system, but of our knowledge of the system ... cleanly resolves many otherwise confusing issues" (@ 85). This "cleanly" is a bit disingenuous, since plenty of people wouldn't agree with this interpretation (see, e.g., J. Bricmont's 1995 paper "Science of Chaos, or Chaos in Science?", available on the arXiv). The discussion of the arrow of time (pp. 80-81) does mention a couple of nuggets of relevant history, but the level of treatment is more suitable for a pre-med physics survey class than for a graduate course in stat mech.

A couple of pages later (pp. 87-90), the author slides from a discussion of Shannon entropy to discussing an algorithm for helping your roommate find her keys by asking her questions. Without acknowledging it, he introduces the notion of meaning into "information" -- but meaning wasn't relevant for Shannon. Indeed, the historical background for why Shannon called his quantity "entropy" -- John von Neumann advised him to use the term because "nobody understands entropy" -- suggests one should be very cautious about mashing up the various scientific and colloquial meanings of "information".

It's just this kind of unreflective enthusiasm when applying physics techniques outside their usual domain that leads to so many junk "Physics and Society" papers on the arXiv. At least one-half star deduction, for an upper bound of 3.5 stars.

NOTE ADDED 2007/03/27: I recently received a very gracious email from the author addressing some of the above comments. I wasn't convinced by him about Black-Scholes or entropy (which he claimed to understand "in the broad context" better than Claude Shannon or J. Bricmont), but I do appreciate his engaging me on those points. He's also prepared an answer key to the exercises, though you'll need to write to him and convince him that you aren't taking the course for credit before he'll send them to you. (In my case my review apparently was credible evidence enough; not sure what it might take in yours, but from his note it sounds like it's not an impossible task.) I can't say that this materially changes my rating of the book, but I certainly give five stars to the author for his sincerity.

6 of 7 people found the following review helpful:

5.0 out of 5 stars Excellent Advanced Statistical Mechanics Book, October 20, 2006

By	Sammy (San Francisco, CA) - See all my reviews

I immensely enjoyed studying this statistical mechanics book. I think that the author, James Sethna, has a "Feynman-like" ability to explore his subject matter with much depth, insight, and many playfully creative excursions. The exercises cover such topics as the thermodynamics of Dyson Spheres and black holes; of how many shuffles it takes to fully randomize a card deck; and of whether an advanced, intelligent being or civilization can, from a thermodynamic standpoint, manage to process an infinite number of thoughts before the heat death of the universe, or whether they are limited to a finite number of thoughts. I think that there is a lot of wisdom and insights in this book which is missing in other books I've read on statistical mechanics and thermodynamics, where I often feel overwhelmed by a zoo of partial derivatives and thermodynamic equations with little guidance given on how the entire structure fits together. I strongly recommend this book for anyone who has studied some statistical mechanics and/or thermodynamics in a lower-level undergraduate course, and is looking for more advanced upper-level undergraduate or graduate-level text.

1 of 1 people found the following review helpful:

4.0 out of 5 stars Very good reference for Stat. Mech. , October 27, 2007

By	C.Zhang "Peterpan" (Lyon,FR) - See all my reviews

This books is reader friendly and very interesting. In the chapter about correlation function & linear response theory, the demonstration is very clear and self-consistent. As a student who is new to this topic, I think this chapter is even better than Chandler's book on this topic( I love Chandler's intro too). The problem set seems to be stimulating and may need more time than learning the main text. And more, the appendix is on Fourier Transform, a saver to the chemistry student like me.