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Statistical Physics of Particles
Statistical physics has its origins in attempts to describe the thermal properties of matter in terms of its constituent particles, and has played a fundamental role in the development of quantum mechanics. Based on lectures taught by Professor Kardar at MIT, this textbook introduces the central concepts and tools of statistical physics. It contains a chapter on probability and related issues such as the central limit theorem and information theory, and covers interacting particles, with an extensive description of the van der Waals equation and its derivation by mean field approximation. It also contains an integrated set of problems, with solutions to selected problems at the end of the book and a complete set of solutions is available to lecturers on a password protected website at www.cambridge.org/9780521873420. A companion volume, Statistical Physics of Fields, discusses non-mean field aspects of scaling and critical phenomena, through the perspective of renormalization group.
330 pages, Hardcover
First published May 31, 2007
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Displaying 1 - 5 of 5 reviews
December 8, 2023
If you are looking to learn graduate level statistical mechanics for the very first time: STAY. AWAY. Look elsewhere. Use David Tong’s lecture notes or a more traditional textbook like Kittel.
If you’ve already been through the wringer once and have to revisit stat mech: This is actually a really interesting presentation of statistical physics up until chapter 4. The first three chapters were great, and I learned a lot of useful techniques from chapter 2 in particular. Chapters 4 and beyond were less interesting, but fine. Be prepared to fill in most of the derivation details yourself.
If you’ve already been through the wringer once and have to revisit stat mech: This is actually a really interesting presentation of statistical physics up until chapter 4. The first three chapters were great, and I learned a lot of useful techniques from chapter 2 in particular. Chapters 4 and beyond were less interesting, but fine. Be prepared to fill in most of the derivation details yourself.
December 12, 2021
Finished the last two chapters with very quick and loose skimming for grading purposes.
For the most part, I think this book is very good in the sense that it gives high-level, detailed explanation of the various concepts. It also makes quite clear various hierarchy of scales (especially in the kinetic theory chapter). However, after finishing this I am still of the opinion that this book is too terse to use as a first course, or even second course. I think Pathria is too encyclopedic, but this is really too compact for people to fully grasp things easily. Chances are, you either have to read this many, many times, or you will end up complementing it with external sources. To even do this would also probably mean you have seen most things in statistical mechanics once before reading this.
I would have given this book a 3-star if not because the book itself gives some insights and understanding, physical interpretation that I have not seen/heard before, though it's possible some other sources have it. Overall, I think the problem is not lack of clarity per se, rather the terseness. I think this book could have added an extra 100 pages and still won't be too bulky (it's really only 200 pages, and the extra 100 pages are selected solutions, which is a nice feature).
Recommended for people who have energy and time to keep (re-)reading this, e.g. when taking graduate-level coursework. Note that you cannot really use this if you don't commit enough time, unless your mind works really well/quickly.
For the most part, I think this book is very good in the sense that it gives high-level, detailed explanation of the various concepts. It also makes quite clear various hierarchy of scales (especially in the kinetic theory chapter). However, after finishing this I am still of the opinion that this book is too terse to use as a first course, or even second course. I think Pathria is too encyclopedic, but this is really too compact for people to fully grasp things easily. Chances are, you either have to read this many, many times, or you will end up complementing it with external sources. To even do this would also probably mean you have seen most things in statistical mechanics once before reading this.
I would have given this book a 3-star if not because the book itself gives some insights and understanding, physical interpretation that I have not seen/heard before, though it's possible some other sources have it. Overall, I think the problem is not lack of clarity per se, rather the terseness. I think this book could have added an extra 100 pages and still won't be too bulky (it's really only 200 pages, and the extra 100 pages are selected solutions, which is a nice feature).
Recommended for people who have energy and time to keep (re-)reading this, e.g. when taking graduate-level coursework. Note that you cannot really use this if you don't commit enough time, unless your mind works really well/quickly.
August 25, 2023
well, the ensembles part is cool
however
if you go wikipedia
you have all the information you need
the quantum part gets a bit confusing, but there are some yt tutorials that explain it well
however
if you go wikipedia
you have all the information you need
the quantum part gets a bit confusing, but there are some yt tutorials that explain it well
December 6, 2017
I recall using this book in my fourth year of my undergraduate program for a graduate statistical physics course. The problems were excellent; challenging yet very insightful.
The text itself however was mediocre at best. It was written rather poorly with heavy emphasis on math (which I found rather scattered and hard to follow at the time) and less so on the physical meaning. Of course that's all good for a graduate level text, but with such lack of details and such, it was rather hard to follow.
Professor Kardar has his lectures online on the MIT OpenCourseWare site and it seems like the book was solely made as lecture notes to accompany his lectures. I watched each lecture (which were excellent, by the way) and found the book rather useful.
Perhaps going back to the book now would be a better experience (with an increase in mathematical maturity and a better grasp of physical systems), which I will most likely do after going through Pathria's Statistical Mechanics book as a review.
The text itself however was mediocre at best. It was written rather poorly with heavy emphasis on math (which I found rather scattered and hard to follow at the time) and less so on the physical meaning. Of course that's all good for a graduate level text, but with such lack of details and such, it was rather hard to follow.
Professor Kardar has his lectures online on the MIT OpenCourseWare site and it seems like the book was solely made as lecture notes to accompany his lectures. I watched each lecture (which were excellent, by the way) and found the book rather useful.
Perhaps going back to the book now would be a better experience (with an increase in mathematical maturity and a better grasp of physical systems), which I will most likely do after going through Pathria's Statistical Mechanics book as a review.
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August 8, 2020An EXTREMELY well-written book. The first chapter on classical thermodynamics was an absolute delight to read... Kardar managed to cover the essence of this topic in 50 pages with more clarity than most authors are able to do in 300. This trend continues on to the later chapters. All of them are devoid of unnecessary fluff. If you want a no-nonsense, well-motivated, carefully explained (and concise!) introduction to Statistical Physics, this is the book to read.
Displaying 1 - 5 of 5 reviews