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CUSTOMER REVIEWS (Average Customer Rating: 4.0 based on 6 reviews)

Deep, thoughtful, and beautiful introduction to the field

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.
March 01, 2008

A terrific, contemporary and courageous textbook

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.
January 08, 2008

Very good reference for Stat. Mech.

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.
October 28, 2007

Good for professors, not for students

This book is great, if you've already got an advanced physics degree and want a new/fresh look at Statistical Mechanics with a modern bent. The problems are very long and wordy, but that ususally means there's a lot of explanation...which is because none of it is explained in the text.
March 08, 2007

Excellent Advanced Statistical Mechanics Book

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.
October 20, 2006

SIMILAR PRODUCTS

Statistical Mechanics: Algorithms and Computations (Oxford Master Series in Statistical, Computational, and Theoretical Physics)
by Werner Krauth

Statistical Physics (Course of Theoretical Physics, Volume 5)
by Lev Davidovich Landau

Condensed Matter Field Theory
by Alexander Altland, Ben Simons

Renormalization Methods: A Guide For Beginners
by William David McComb

Introduction to Modern Statistical Mechanics
by David Chandler