Ebook Free Equilibrium Statistical Physics: with Computer simulations in Python, by Dr. Leonard M. Sander
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Equilibrium Statistical Physics: with Computer simulations in Python, by Dr. Leonard M. Sander
Ebook Free Equilibrium Statistical Physics: with Computer simulations in Python, by Dr. Leonard M. Sander
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This is a graduate textbook in Statistical Physics intended for students in Physics, Biophysics, Chemistry, Materials Science, and Engineering. It is based on using computer simulations in Python as a learning tool. Many exercises involve simulations, and a set of listings of computer programs are given in the appendix. Algorithms discussed include molecular dynamics, Metropolis Monte Carlo, Gibbs ensemble, and the Wolff algorithm.
- Sales Rank: #1414159 in Books
- Published on: 2013-07-27
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .76" w x 6.00" l, .99 pounds
- Binding: Paperback
- 334 pages
About the Author
Leonard M. Sander is Professor of Physics and Complex Systems at the University of Michigan, Ann Arbor. His research interests include pattern formation, non-equilibrium statistical physics, and biophysics.
Most helpful customer reviews
2 of 2 people found the following review helpful.
It's an interesting idea, but needs a lot of refinement
By Alex T.
I'll start with the pro. The idea of teaching the class with an emphasis on using computation as a pedagogical tool to be able to visualize the physics of large numbers is good.
Unfortunately, aside from that, the book is in a very preliminary form. The subject is taught from a historical perspective, beginning with thermodynamics and phenomenology, and then using that to derive statistical mechanics proper. The level alternates between being an undergrad intro class and a graduate level course, often within the same chapter and problem. There is also very little continuity of derivations; rather, the author just jumps around sampling lots of topics qualitatively, and then asks some pretty derivation-heavy questions.
I'd like to see the ordering of this book redone so that the probabilistic approach, and canonical ensembles come first, and then thermodynamics is derived from those laws. I'd also like to see more emphasis on general models and theory, and less emphasis on specific systems. Finally, considering this is supposed to be a text for a graduate level course, a more in-depth explanation of the mathematical tools ad methods would not be amiss early on.
I give 2 stars because I can see how the book could be used well to supplement a longer, more theoretical text, and the price is reasonable to be a supplement. However, I would not recommend it as the only text used in a class -- even an undergrad level text like Kittel would be better.
0 of 0 people found the following review helpful.
Great book, even better simulations
By Juliette
The flow of the book is logical, and explanations are clear (including definitions of all variables, useful when h has varying meanings across topics). The questions are sometimes confusing, but working through them does help reinforce the material in the chapters. The most valuable thing is the computational exercises, which are really cool and help visualize large systems and large numbers of particles. I'm not sure why every StatMech book doesn't include computer simulations, but these ones are especially well created.
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