16 of 16 people found the following review helpful:
4.0 out of 5 stars
The best graduate text on statistical mechanics you'll find, June 19, 2007
This review is from: Statistical Mechanics, Second Edition (Paperback)
There are a number of lukewarm reviews of this textbook on this site, and few positive ones. I feel it deserves to be thrown into a better light, and will attempt to respond to some of these negative reviews.
First, I disagree wholeheartedly with the reviewer Fayngold. I find that this text is much more accessible than, for example, Huang. You do not need to be an expert in stat mech before picking up this book; rather, I found that it quite clearly elucidated the subject of stat mech in a pedagogical manner, and many of the derivations (for example, deriving the conditions for Bose-Einstein condensation) to be much shorter and simpler than those in other texts. Stat mech is by nature a very mathematical subject, and this is unavoidable (though Pathria did delegate much of the mathematical stuff -- like Guassian integrals, Gamma functions, etc -- to a few concise appendices). Perhaps the reviewer did not realize that this is a graduate level, rather than undergraduate, text book. I also disagree with the reviewer that this book is comprehensive (more on that below).
In response to many of the other reviewers, I think it's worth repeating: this is a graduate level textbook. Graduate texts, in my experience, rarely attempt to provide physical insight. Rather, they are focused on rigorously deriving the laws and equations that you need in order to perform physical calculations. I'm not saying I agree with this methodology, but it does seem to be the case more often than not. If you truly want to find a textbook that is a dense morass of mathematics, try Huang. Pathria is a breath of fresh air by comparison.
Prerequisite knowledge for this text would include at least an undergraduate class in quantum mechanics (familiarity with the operator notation, the operator version of Schrodinger's equation, as well as choice of space and momentum "representations") and an acquaintance with Hamilton's canonical equations (mainly the q and p variables). Without this background, much of the latter chapters might be hard to follow.
If you are looking for a gentler introduction to statistical mechanics, I can't recommend enough "Thermal Physics" by Kittel and Kroemer. This is the de facto standard for a first course in statistical mechanics. The only drawback I see with Kittel and Kroemer is that it is an entirely quantum-based approach to statistical mechanics, and that's not what everyone is looking for. Perhaps surprisingly, or perhaps not, the quantum approach does make the mathematics easier to follow (assuming a very passing acquaintance with quantum mechanics), since you deal only with sums rather than the more complicated integrals over phase space that are required for a classical treatment.
The Table of Contents is available above and gives a good overview of the topics covered in this book. It is a complete list of topics, though I found it lacking in a couple of ways. First, there is no mention of the Boltzmann Transport Equation. For this, I recommend borrowing Huang or another text from the library. And second, there is not an in-depth treatment of the Debye theory of phonons, though I have to admit it is as good as any I've seen.
I can't speak to the problems in this text, because I have not attempted them.
Overall, I think this is the best graduate level book in statistical mechanics that I've come across, far superior to Huang or Reichl. Feynman's and Landau's books, though dated, are also worth looking into, because it's hard to beat the master instructors of physics. From my conversations with other graduate students, I think most agree that this is one of the best graduate level stat mech books out there.
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14 of 18 people found the following review helpful:
3.0 out of 5 stars
good reference but mediocre textbook, August 28, 2004
This review is from: Statistical Mechanics, Second Edition (Paperback)
The book is very comprehensive, discusses all topics in Stat Mech and contains all the formulas you'll need. Unfortunately, it often neglects to mention the physical conditions for which this or that formula was derived. Reading the bood quickly becomes an exercise in mathematics. The problems are very hard and the student looking for a way to approach the problems will find no clue in the book whatsoever. Convenient for professors. Students who want to pass the course should look elsewhere for the discussion of the appropriate solution methods. Reading will be pleasant for those who already have a rock-solid understanding of Stat Mech. All the others will be left in the dust. Buy this book if it's a required text, if you want a good reference, or if you think you can solve any problem on Stat Mech. Read some other book first to understand the physics involved.
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5 of 6 people found the following review helpful:
4.0 out of 5 stars
Sufficient, not exactly outstanding, but extremely self sufficient, July 26, 2008
This review is from: Statistical Mechanics, Second Edition (Paperback)
This is a good book. As long as the person that picks it up is the audience that this book was meant for. It is not really heavy handed in mathematics. Quite clear and concise, as long as you engage the effort to work through it. The review questions are not exactly hard, just depends upon the amount of effort, from the previous line, engaged.
As a doctoral student and a lowly engineer, and not a whacko physicist (Don't get me wrong, I love physicists, they are just too brilliant to be described in mediocre effusion) this was the book I spent quite some time looking for.
Many other books, that I obtained, provide more of the author's personal research and efforts at generalization using complicated/esoteric mathematical frameworks which are not quite legible to non-math/app math/app physics people. And sometimes, the treatment is neither relevant to the purpose of a general textbook. I did not want to spend a month trying to learn what simple operators meant.
My objective was to dive into the topics that interested me the most. And this book has been, and is being quite good with that.
I refrain from 5 stars and give it 4 because there have been a few cases where the amount of effort spent in understanding some of the out-pops-jack-from-the-box equations (unexplained equations), which might be quite logical to smart people but not to me, seemed disproportionate to their final importance. e.g. the Langevin and fluctuation-dissipation explanations.
Another bone I have to pick with this book is that it does not quite build perspective/background well enough before diving into some concept. (For example, contrast with Morrison and Boyd for organic chemistry, another textbook, they spend days building perspective, but I guess that makes the book a back killer).
On the whole it is a book that gives you confidence as you sip coffee and stare at it staring back at you from your personal book shelf. :-) Cheers!
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