Stochastic Processes in Classical and Quantum Physics and Engineering

Harish Parthasarathy received a 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 and 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.

• 1. Stability Theory of Nonlinear Systems Based on Taylor Approximations of the Nonlinearity 2. String Theory and Large Deviations 3. Ordinary, Partial and Stochastic Differential Equation Models for Biological Systems, Quantum Gravity, Hawking Radiation, Quantum Fluids, Statistical Signal Processing, Group Representations, Large Deviations in Statistical Physics 4. Research Topics on Representations 5. Some Problems in Quantum Information Theory 6. Lectures on Statistical Signal Processing 7. Some Aspects of Stochastic Processes 8. Problems in Electromagnetics and Gravitation 9. Some More Aspects of Quantum Information Theory 10. Lecture Plan for Statistical Signal Processing 11. My Commentary on the Ashtavakra Gita 12. LDP-UKF Based Controller 13. Abstracts for a Book on Quantum Signal Processing Using Quantum Field Theory 14. Quantum Neural Networks and Learning Using Mixed State Dynamics for Open Quantum Systems 15. Quantum Gate Design, Magnet Motion, Quantum Filtering, Wigner Distributions 16. Large Deviations for Markov Chains, Quantum Master Equation, Wigner Distribution for the Belavkin Filter 17. String and Field Theory with Large Deviations, Stochastic Algorithm Convergence