Review from previous edition In his innovative new text, Carnegie Mellon University physics professor Robert Swendsen presents the foundations of statistical mechanics with, as he puts it, a detour through thermodynamics. That's a desirable strategy because the statistical approach is more fundamental than the classical thermodynamics approach and has many applications to current research problems. [] The mathematical notation is carefully introduced and useful; the selected mathematical techniques are clearly explained in a conversational style that both graduate and advanced undergraduate students will find easy to follow. The author's subject organization and conceptual viewpoint address some of the shortcomings of conventional developments of thermal physics and will be helpful to students and researchers seeking a deep appreciation of statistical physics.
Physics Today, August 2013
Bob Swendsen's book is very well thought out, educationally sound, and more original than other texts.
Jan Tobochnik, Kalamazoo College, USA
Robert Swendsen is a well-respected researcher who has developed many novel algorithms that illustrate his deep understanding of statistical mechanics. His textbook reflects his deep understanding and will likely have a major impact on the way statistical mechanics and thermodynamics is taught. Particularly noteworthy is Swendsen's treatment of entropy, following Boltzmann's original definition in terms of probability, and his comprehensive discussion of the fundamental principles and applications of statistical mechanics and thermodynamics. Students and instructors will enjoy reading the book as much as Swendsen obviously enjoyed writing it.
Harvey Gould, Clark University, USA
In this reader-friendly, excellent text, the author provides a unique combination of the best of two worlds: traditional thermodynamics (following Callen's footsteps) and modern statistical mechanics (including VPython codes for simulations).
Royce Zia, Virginia Polytechnic Institute and State University, USA
Swendsen is famous for developing Monte Carlo algorithms which dramatically speed up the simulation of many systems near a phase transition. The ideas for those algorithms required deep understanding of statistical mechanics, an understanding which is now fully applied to this excellent textbook.
Peter Young, University of California, USA