Part I. Introduction
   Brief Overview of Quantum Computing
   Basics of Quantum Mechanics and Mathematical/CS Background (2 lectures)
   Classical vs Quantum: positive and negative results; sample algorithms
   Basic examples of Quantum Circuits: adders, etc
   An overview of implementation technologies and implied constraints

Part II. Classical circuits
   Brute-force Synthesis of Optimal Classical Circuits; Basic Heuristics
   BDD-based Synthesis with Implicit representations 
   Basic ideas in circuit testing, ATPG, D-algorithm, redundancies, etc
   Don't cares in classical circuits, SPFDs and related
   Spectral ideas in circuit synthesis
   Fault-tolerance, ECC....
   Reversible circuits

Part III. Quantum Circuits
   The pivotal role of the Fourier transform in quantum computing
   Circuits for the Quantum Fourier transform
   Gate Libraries for Quantum Circuits
   Straighforward synthesis of quantum circuits (following Cybenko)
   Heuristics for minimization of quantum circuits
   Quantum Measurement and don't cares of quantum circuits
   Errors in quantum circuits, fault-tolerance, ECC

Part IV. Simulation of quantum circuits/algorithms
   Notations for quantum circuits and algorithms
   Basic challenges, best-case vs worst-case
   FFT-based and BDD-based simulation

Part V.  Research topics explored via student term projects.
   Each project will include a written report, a 30-min presentation
   as well as the design of software or logic circuits.