Companion book to Huang's Statistical Mechanics

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SUMMARY

This discussion centers on recommendations for supplementary texts to Huang's "Statistical Mechanics" for better comprehension of the subject. Key suggestions include Landau and Lifshitz's "Course of Theoretical Physics Vol. 5," Sethna's "Statistical Mechanics: Entropy, Order Parameters and Complexity," and F. Reif's "Statistical Physics." Participants emphasize the importance of understanding quantum statistics first to avoid confusion with classical approaches, particularly regarding Gibbs's paradox. The conversation highlights various perspectives on teaching methodologies and the effectiveness of different texts in conveying complex statistical mechanics concepts.

PREREQUISITES
  • Familiarity with statistical mechanics concepts
  • Understanding of quantum mechanics fundamentals
  • Knowledge of thermodynamics principles
  • Experience with advanced physics texts
NEXT STEPS
  • Explore "Statistical Mechanics: Entropy, Order Parameters and Complexity" by Sethna
  • Read "Statistical Physics" by F. Reif for advanced insights
  • Investigate "Course of Theoretical Physics Vol. 5" by Landau and Lifshitz
  • Study "Statistical Physics of Particles" by Kardar for a different perspective
USEFUL FOR

Students and educators in physics, particularly those studying or teaching statistical mechanics, as well as researchers seeking to deepen their understanding of quantum statistics and its applications in thermodynamics.

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My professor will be using Huang's Statistical Mechanics next semester and I have been reading a lot of polarizing reviews. Does anyone recommend a book to read parallel to Huang's to better understand the material and that discusses the same topics in similar fashion?
 
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What's the point of having the topics explained in a similar fashion if you fear Huang's approach might not be 'good' enough?

When I had my undergrad course in statistical mechanics we used Huang as main reference: I have to admit I did not like it that much, but I would not go as far as to say it's a bad book. Anyway, here are a few other books you might want to look at:
Landau, Lifshitz - Course of theoretical physics vol. 5 (classic)
Sethna - Statistical Mechanics: Entropy, Order Parameters and Complexity (unusual approach with quite a lot of insights, I believe this is very good to use as a supplement)
Politi - Statistical Mechanics in a Nutshell (dense, somebody says terse, but I used to find it clear and straight to the point, haven't opened this in >2 years though)
Ma, Fung - Statistical Mechanics (this is a bit more advanced maybe but might be useful)

I think Sethna used to be freely available as a pdf, and you can surely find the others in your university's library.
 
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Landau Lifshitz 5 is among the best books on stat. mech. I know, but it's tough for the beginner. My favorite introductory undergrad book is

H. B. Callen, Thermodynamics and an Introduction to
Thermostatistics, John Wiley&Sons, New York, Chichester,
Brisbane, Toronto, Singapore, 2 ed. (1985).

though it's a bit too much emphasizing the phenomenological thermodynamics for my taste.

Another very good book is volume 5 of the Berkeley Physics course, written by F. Reif, who also wrote another famous more advanced book on the subject:

F. Reif, Statistical Physics, McGraw-Hill, New York, St.
Louis, San Francisco, London, Sydney (1965).

F. Reif, Fundamentals of statistical and thermal physics,
McGraw Hill Book Company, New York (1965).
 
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My favourite is "Statistical Physics and Thermodynamics: An Introduction to Key Concepts" by Jochen Rau. It uses QM from the beginning though. However I prefer that.
 
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Damn! I forgot this gem, written by a colleague of mine. I'm also an advocate of the "quantum-statistics-first approach", since classical statistics is much more problematic and cumbersome than quantum statistics and follows from the latter anyway without all the trouble of the traditional approach. Particularly Gibbs's paradoxon is not present from the very beginning.
 
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vanhees71 said:
Particularly Gibbs's paradoxon is not present from the very beginning.
I completely agree. I think Stat Mech is taught first because historically it came first, however related to what you said the resolution to Gibb's paradox of imposing indistinguishability is unmotivated classically. Reading Rau's book the whole subject just "flows" so much more easily. I actually find classical stat mech a bit confusing with all the "tricks" and ad hoc assumptions you have to juggle to avoid QM.
 
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In the theory course at our university Stat. Phys. is taught as the last module (Theory 5), i.e., the students have heard Newtonian + SRT Mechanics, Analytical Mechanics, Classical electromagnetics, Quantum Mechanics 1. So it's well possible to start with quantum statistics first. I've not given this lecture yet, but I'd start with the quantum case first, starting with "2nd quantization" of Schrödinger wave mechanics (i.e., non-relativistic QFT) to have the adequate tools for handling bosons and fermions in a lucid and clear way.

(For me it doesn't make sense to let the students antisymmetrize product states ("slater determinants") to begin with.)
 
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atyy said:
I don't believe in the quantum first approach. I like Kardar's Statistical Physics of Particles.
Kardar is a great book, I'd recommend it as well.
 
  • #10
Thanks for the tips. I'll start with Huang and if it doesn't go well I'll check out the books recommended.
 
  • #11
I’ll add an endorsement for Reif’s more advanced book, which is really quite readable. It was the text used in my thermo course.
 
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  • #12
Pathria/Beale is good at the graduate level.
Becker, Theory of Heat is good but it is old. This is grad level too, but might be easier than Pathria/Beale
Reif is good for upper level undergrad but it could be used for graduate too,
Zemansky s is OK for undergrad

Landau Lifshitz V is good too at grad level/

For a discursive treatment Sommerfeld (I think Volume 5) is also very good.
 
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  • #13
Indeed, Sommerfeld it particularly good in the Boltzmann-transport equation part, discussing Grad's method.
 
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