ECE 730 Topic 33 - Spring 2016

ECE 730 Topic 33 - Noise Processes: Classical and Quantum Devices

Instructor

Professor Na Young Kim

Description

The course will introduce fundamentals of various noise processes in classical and quantum devices. Re- view of mathematical methods in classical and quantum statistical mechanics is given, on which the theoretical framework of noise processes is developed. Thermal, shot, quantum and 1/f noise processes are studied in macroscopic and mesoscopic electrical and optical devices. Measurement techniques of noise processes and the meanings of measurement accuracy are discussed in classical and quantum worlds. Introduction to coherence, decoherence and control theory is briefly given in closed and open systems.

Course Objective

The course is developed for students to

  • Review classical and quantum statistical mechanics and learn mathematical framework to describe noise processes.
  • Understand thermal, quantum, and 1/f noise in electrical devices and optical devices.
  • Study coherence and decoherence processes and the measurement and control effects. Expected Background: Basic understanding of statistical mechanics, quantum mechanics, solid-state electronics and photonics devices is recommended.

Syllabus

  • PART 1: Theoretical Foundations (2 weeks)
    1. Classical probability theory
    2. Principles of quantum statistics
    3. Mathematical framework of stochastic processes
  • PART 2: Stochastic Processes in Electrical Devices (4 weeks)
    1. Types of noises: thermal noise, shot noise, 1/f noise
    2. Classical and quantum circuit theory
    3. Macroscopic and mesoscopic conductors
    4. Oscillators and amplifiers
  • PART 3: Stochastic Processes in Optical Devices (4 weeks)
    1. Lasers
    2. Parametric oscillators and amplifiers
    3. Optical detectors
  • PART 4: Measurements, Decoherence and Open systems (2 weeks)
    1. Measurement limits in classical and quantum worlds
    2. Coherence and decoherence processes
    3. Closed and open systems

Textbook

None required. Article handouts provided and lecture notes will supplement course lectures.

Grade Distribution

  • Problem Sets : 30 %
  • Midterm : 20 %
  • Final : 50 %