It is well known that the normal distribution is the most pleasant, one can even say, an exemplary object in the probability theory. It combines almost all conceivable nice properties that a distribution may ever have: symmetry, stability, indecomposability, a regular tail behavior, etc. Gaussian measures (the distributions of Gaussian random functions), as infinite-dimensional analogues of tht

Abstracts of dissertations and monographs in microform.

"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"--