| Statistical Mechanics: Entropy, Order Parameters and Complexity (Oxford Master Series in Physics) |  | Author: James P. Sethna
Publisher: Oxford University Press, USA
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Rating:  9 reviews
Media: Paperback
Edition: illustrated edition
Pages: 376
Number Of Items: 1
Shipping Weight (lbs): 1.9
Dimensions (in): 9.6 x 7.4 x 0.9
ISBN: 0198566778
Dewey Decimal Number: 530.13
EAN: 9780198566779
ASIN: 0198566778
Publication Date: June 1, 2006
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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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| Customer Reviews:
Showing reviews 1-5 of 9
 Not good July 24, 2010
Srikumar Sandeep (Boulder,CO)
This book is good only if you already know the subject from other books (like Donald Macquire or Pathria).
 Short on info, long on problems June 1, 2010
Andre Somogyi
Overall, this is not a really bad book, the problem is the text is really short on explanations, and has virtually no examples. The author assumes that most of the learning will be done through the problems. Problem is most people don't have that kind of time to waste with problems.
If you like working problems, this is the book for you, if you want an informative text, than this is definitely not the book for you.
I really would like an updated version of Kerson Huang's truly excellent text. Statistical Mechanics, 2nd Edition
 Great book, got me into the subject March 5, 2009
Tiago Victor Gehring (Munich, Germany)
I'm studying for my final physics exams and - after having a look at a half-dozen or so other statistical mechanics book in the library - (none got me really involved) I have just to say that I'm really glad that I decided to buy this book!
It's really a joy and fun to read! I think that the other reviewers already gave a good description of the book and about the exercises I can confirm that there are lots of them with many topics being covered there. I personally think this is good, specially for self study - better do-it-yourself, the majority of them are very well elaborated and interesting.
I only wish also that some solutions would have been provided... (although I guess all of them together would fill another 300 pages book);
In any case highly recommended!
Deep, thoughtful, and beautiful introduction to the field March 1, 2008
Daniel A. Beard
This advanced undergraduate or introductory graduate level text on statistical mechanics is clearly written by a master and perhaps visionary teacher. Statistical mechanics remains, in my opinion, the only truly rigorous science of emergent phenomena. As the scientific community in general focuses more on complex systems, it is likely that the techniques developed for the theoretical study of the statistical thermodynamic properties of matter will find widespread applications from biology to banking. In this spirit, this book is written to educate the next generation of scientists rather than as a text focused solely on existing applications.
While the subject matter of this book easily devolves into mathematical gymnastics, this text is wonderfully written to simultaneously build up an intuitive grasp along with proficiency with mathematical concepts. Introductory chapters on "What is statistical mechanics?" and "Random walks and emergent properties" are deceptively simple: the mathematical techniques employed in these chapters should be immediately accessible to senior level physics and engineering students. Yet by the end of Chapter 2, one finds oneself deriving a simple one-dimensional Fokker-Planck equation--a nontrivial application in statistical mechanics with applications in chemical kinetics, transport phenomena, mathematical biology, and finance.
This appeal to potentially broad applications is part of what makes this book unique. While a great number of important physical concepts are developed, this is really not an ordinary physics book. Instead, the tools and techniques of statistical mechanics are developed from an exceptionally broad perspective.
While I have worked very few of the problems, the end-of-chapter problems sets present deep and detailed questions that are critically integrated into the text. A reader who has the time and dedication to do the problems will gain much more than one who does not.
A terrific, contemporary and courageous textbook January 8, 2008
Alex Antonelli (Campinas, Sao Paulo Brazil)
5 out of 5 found this review helpful
The book Statistical Mechanics: Entropy, Order Parameters and Complexity by James Sethna is excellent. I have used it as the main textbook in my course on Statistical Physics for first year graduate students at the Universidade Estadual de Campinas (UNICAMP) in Brazil. The students and I liked it very much.
I think that the main quality of the book is that it presents Statistical Physics as a very dynamical subject, interconnected with several subjects within physics, as well as outside it.
Since the book is aimed for a one semester course on the subject, the author had to make important choices. I really liked his choices. For instance, the book does not discuss approximate methods used to treat systems with interacting particles, instead the author has chosen to have a chapter on Calculation and Computation. Although these methods have played an important role in the past, nowadays the study of the relevant problems in the field require computer simulations. The chapter on Computer Simulation is excellent. Instead of only discussing how to perform a Monte Carlo simulation, it proofs mathematically in detail (except for the Perron-Frobenius theorem) why one ends up with an equilibrium probability distribution after a number of Monte Carlo steps. Another important subject covered in the book is that of Abrupt Phase Transitions. For most Statistical Physics books, only Second Order or Continuous Transitions exist. The exercises are also another very important and interesting choice made by the author. They are very different from the usual exercises one can find in a regular textbook on Statistical Physics. The exercises are in general very intelligent and they appear in a broad range of difficulty, from those which can be solved by inspection to those that are small projects. I recall two great examples, exercises 5.7 and 5.10, where it is shown in a very clear and clever way that, when we know the system from a microscopic point of view, its entropy does not increase, whereas if we know only a coarse-grained description of it, then its entropy does increase. Some exercises lead the reader, in a secure way, through aspects of the theory that are not covered in the text. For instance, Landau's theory for phase transitions is presented in a very nice way in exercise 9.5.
Perhaps, the aspect that I have enjoyed most in the book is that the author does not shy away from discussing one of the thorniest points in the fundamentals of Statistical Physics: what entropy really is. The book discusses in some detail Phase Space Dynamics and Ergodicity. It presents some physical situations where the ergodic hypothesis breaks down. Usually this problem with the theory is swept under the rug in most textbooks. One very interesting case is that of the entropy of glasses. A subject the author himself has worked on. If a liquid is cooled down very fast it may become a glass, undergoing what is called a glass transition. When the system is in the liquid phase its atoms are diffusing and the system goes through all different possible configurations, that is believed to be the cause for its entropy (ergodicity). When the liquid undergoes a glass transition, the atoms cease diffusing and the system is jammed in one (a single one) structure of the liquid that generated it. If the system is not anymore going through all the possible configurations available what has happened to its entropy? No heat is released in this transition, therefore, one does not expect a change in its entropy. A hardcore purist would answer that the glass is not a system in equilibrium and, therefore, the entropy is not well defined. The point is, it may take much more than the age of the Universe for the glass to reach the final equilibrium and become a crystal (reported changes in glasses of ancient churches are urban legends). The question about what has happened to the entropy of the liquid remains there, despite the purist's answer. The experimentalists can measure very well the residual entropy of a glass. For the author, for me and fortunately nowadays for many others, the satisfactory answer is that the entropy of a glass is the missing information about the system. Another example of residual entropy can be found in the ice cubes in your refrigerator.
At last but not least, I would like to comment on a misconception of a previous reviewer about Shannon's Information Theory. The entropy proposed by Shannon is a measure of the uncertainty of a set of possible messages that can be exchanged, regardless the content of each message. Therefore, this entropy is related to the probability distribution associated with the ensemble of possible messages, regardless of their content. If there are any doubts, I would suggest reading the first chapter of the book Mathematical Foundations of Information Theory by A. Ya. Khinchin. In section 5.3.2 of the book, the author is just analyzing the properties of the Shannon entropy of a probability distribution using a humorous example. The probability distribution can be associated with anything, even with a key lost by a careless room-mate. This entropy is a property of the probability distribution, independent of any possible meaning attributed to it by a human being.
Showing reviews 1-5 of 9
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