Abstract
Large deviations: General theory and i.i.d. processes Introductory discussion The large deviation principle Large deviations and asymptotics of integrals Convex analysis in large deviation theory Relative entropy and large deviations for empirical measures Process level large deviations for i.i.d. fields Statistical mechanics Formalism for classical lattice systems Large deviations and equilibrium statistical mechanics Phase transition in the Ising model Percolation approach to phase transition Additional large deviation topics Further asymptotics for i.i.d. random variables Large deviations through the limiting generating function Large deviations for Markov chains Convexity criterion for large deviations Nonstationary independent variables Random walk in a dynamical random environment Appendixes: Analysis Probability Inequalities from statistical mechanics Nonnegative matrices Bibliography Notation index Author index General index
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