Credits: 3

Description

Prerequisites: Minimum grade of C- in ENEE324, and a minimum grade of C- in one of the following: ENEE290, ENEE461, or MATH240.

We will explore the fundamental limits of the efficiency with which one can encode information in light in the contexts of communications and sensing. Students will learn essential concepts from information theory, estimation theory, detection theory, the mathematical description of orthogonal optical modes, optical interference and noise in photo detection. We will not assume any background in optics, stochastic processes, quantum mechanics, or information theory. However,a strong mathematical background and proficiency in complex numbers, calculus, probability theory, and linear algebra (vectors and matrices) will be required.

Semesters Offered

Spring 2025

Learning Objectives

The objective of this course is for the students to appreciate how treating light as a quantum mechanical object one can glean richer information than what is possible when treating light as a classical electromagnetic wave. The course stops short of developing into the full-fledged mathematical theory of quantum optics, to be covered in a future advanced graduate course. The primary goal behind this course is to equip students coming from a broad engineering background who may be considering taking on theoretical or experimental research in quantum enhanced photonic information processing in the future, with deep intuitions on a systematic way to approach optical detection, and to develop an appreciation of: (1) the value of a full quantum treatment of light to find fundamental limits of encoding information in the photon, and (2) how pre-detection manipulation of the information-bearing light can help dispose it information favorably with respect to the inevitable irreversible detection noise. This course will not assume any background in optics, stochastic processes, quantum mechanics, information theory or estimation theory. However, an undergraduate mathematical background and proficiency in complex numbers, probability theory, and linear algebra (vectors and matrices) will be assumed.