Frontmatter -- Preface -- Contents -- Introduction -- Part I. General theory and basic examples -- Chapter 1 Specifications of random fields -- Chapter 2 Gibbsian specifications -- Chapter 3 Finite state Markov chains as Gibbs measures -- Chapter 4 The existence problem -- Chapter 5 Specifications with symmetries -- Chapter 6 Three examples of symmetry breaking -- Chapter 7 Extreme Gibbs measures -- Chapter 8 Uniqueness -- Chapter 9 Absence of symmetry breaking. Non-existence -- Part II. Markov chains and Gauss fields as Gibbs measures -- Chapter 10 Markov fields on the integers I -- Chapter 11 Markov fields on the integers II -- Chapter 12 Markov fields on trees -- Chapter 13 Gaussian fields -- Part III. Shift-invariant Gibbs measures -- Chapter 14 Ergodicity -- Chapter 15 The specific free energy and its minimization -- Chapter 16 Convex geometry and the phase diagram -- Part IV. Phase transitions in reflection positive models -- Chapter 17 Reflection positivity -- Chapter 18 Low energy oceans and discrete symmetry breaking -- Chapter 19 Phase transitions without symmetry breaking -- Chapter 20 Continuous symmetry breaking in N-vector models -- Bibliographical Notes -- Further Progress -- References -- References to the Second Edition -- List of Symbols -- Index
Hans-Otto Georgii, Ludwig-Maximilians-Universität Munich, Germany.
"This book is much more than an introduction to the subject of its title. It covers in depth a broad range of topics in the mathematical theory of phase transition in statistical mechanics and as an up to date reference in its chosen topics it is a work of outstanding scholarship. It is in fact one of the author's stated aims that this comprehensive monograph should serve both as an introductory text and as a reference for the expert. In its latter function it informs the reader about the state of the art in several directions. It is introductory in the sense that it does not assume any prior knowledge of statistical mechanics and is accessible to a general readership of mathematicians with a basic knowledge of measure theory and probability. As such it should contribute considerably to the further growth of the already lively interest in statistical mechanics on the part of probabilists and other mathematicians."Fredos Papangelou, Zentralblatt MATH
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