Large Deviations Applied To Classical A

This book deals with a variety of problems in Physics and Engineering where the large deviation principle of probability finds application. Large deviations is a branch of probability theory dealing with approximate computation of the probabilities of rare events.

It contains applications of the LDP to pattern recognition problems like analysis of the performance of the EM algorithm for optimal parameter estimation in the presence of weak noise, analysis and control of non-Abelian gauge fields in the presence of noise, and quantum gravity wherein we are concerned with perturbation to the quadratic component of the Einstein-Hilbert Hamiltonian caused by higher order nonlinear terms in the position fields and their effect on the Gibbs statistics and consequently quantum probabilities of events computed using the quantum Gibbs state. The reader will also find in this book applications of LDP to quantum filtering theory as developed by Belavkin based on the celebrated Hudson-Parthasarathy quantum stochastic calculus.

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Harish Parthasarathy received B.tech degree in Electrical Engineering from IIT Kanpur and his PhD degree in Signal Processing from IIT Delhi in 1994. He worked as a visiting fellow in the Indian Institute of Astro Physics, Bangalore, from 1993 to 1994. He has worked as a member of faculty in the Electrical Engineering departments at IIT Bombay and IIT Kanpur. Currently, he is a professor in the Electronics and Communication Division in NSIT, Delhi. He teaches courses on Signal processing, Electromagnetics, transmission lines, wave guides & antennas and electives in quantum field theory, quantum robotics & quantum stochastic processes to undergraduate and postgraduate students. He has published over 70 papers in international journals and conferences and he has also published 12 books on a variety of topics in mathematical physics, signal processing and antenna theory.