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"Statistical Mechanics in a Nutshell offers a concise, self-contained advanced undergraduate to graduate level introduction to this rapidly developing field, requiring a background in elementary calculus and elementary mechanics. It starts with the basics, introduces the most important developments in classical statistical mechanics over the last thirty years, and guides readers to the very threshold of today's cutting-edge research. The author has revised the first 5 chapters (harmonizing the notation, improving the proofs, checking all exercises and adding a few additional interesting ones). He has also added a new chapter on stochastic thermodynamics, which finds its place after the 9th chapter. The appendices will also be completely rewritten, emphasizing the role of convexity and the Jensen inequality. Chapter 8 will be improved to include some important topics: namely, thermostats and fast algorithms. Chapter 9 will also be rewritten to modernize it and to transition to the new chapter on stochastic thermodynamics. Chapter 10 will be split in two, to focus on "disordered systems" and "complex systems," to emphasize applications (including neural networks and optimization algorithms), and to introduce some fundamental techniques (like the cavity method and message passing) at an elementary level. The goal of the new edition is to help the reader find her/his way into and through the vast, recent literature concerning statistical mechanics and to build a sense of the many fields in which the discipline has recently been applied"--
About the author
Luca Peliti is deputy director of the Santa Marinella Research Institute and professor emeritus of statistical mechanics at the University of Naples Federico II. He is the author (with Simone Pigolotti) of Stochastic Thermodynamics: An Introduction (Princeton).
Summary
The essential introduction to modern statistical mechanics—now completely updated and expanded
Statistical mechanics is one of the most exciting areas of physics today and has applications to subjects ranging from economics and social behavior to algorithmic theory and evolutionary biology. Statistical Mechanics in a Nutshell provides a self-contained introduction to this rapidly developing field. Starting with the basics of kinetic theory and requiring only a background in elementary calculus and mechanics, this concise book discusses the most important developments of recent decades and guides readers to the very threshold of today’s cutting-edge research.
- Features a new chapter on stochastic thermodynamics with an introduction to the thermodynamics of information—the first treatment of its kind in an introductory textbook
- Offers a more detailed account of numerical simulations, including simulated annealing and other accelerated Monte Carlo methods
- The chapter on complex systems now features an accessible introduction to the replica theory of spin glasses and the Hopfield theory of neural networks, with an emphasis on applications
- Provides a new discussion of defect-mediated transitions and their implications for two-dimensional melting
- An invaluable resource for graduate students and advanced undergraduates seeking a compact primer on the core ideas of statistical mechanics
- Solutions manual (available only to instructors)
Additional text
"Unlike typical textbooks . . . [Statistical Mechanics in a Nutshell] presents statistical mechanics as a more general theory with broader applications. . . . A graduate student or researcher who wants to explore the applications of statistical mechanics would be very well served by this book."
