This book is an introduction to the theory and applications of large deviations, a branch of probability theory that describes the probability of rare events in terms of variational problems. By focusing the theory, in Part A of the book, on random sequences, the author succeeds in conveying the main ideas behind large deviations without a need for technicalities, thus providing a concise and accessible entry to this challenging and captivating subject. The selection of modern applications, described in Part B of the book, offers a good sample of what large deviation theory is able to achieve in various different contexts: statistical hypothesis testing, random walk in random environment, heat conduction with random sources and sinks, polymer chains, and interacting diffusions. With its 60 exercises and solutions, this book can be used as a text for graduate students who have had some exposure to mathematical analysis and measure-theoretic probability.
Let o P 0 and h e C, (E), and assume that the comparison principle holds for subsolutions of (7.78) (I – ot" Hi) f = h, and supersolutions of (7.79) (I – O.T. Hi) f = h. ... LIMgno Vc = gove for each c e R implies (7.73), and LIMga.
Large deviations for an exchangeable system of reversible diffusions in [double-struck]R[superscript italic]d are investigated in the limit when the number of particles tends to infinity with the objective of providing a methodology to ...
MR1707339 Olle Häggström, Random-cluster representations in the study of phase transitions, Markov Process. ... MR517873 Naresh C. Jain, Large deviation lower bounds for additive functionals of Markov processes, Ann. Probab.