CS 837 Quantum Computing

Wednesdays, 6:10-9:10 pm, Video-conferenced between Pleasantville and NYC

Instructors: Dr. Charles Tappert, Goldstein Academic Center, Room 325, Pleasantville
Dr. Ronald Frank, Goldstein Academic Center, Room 325, Pleasantville
Adjunct Prof. Stephan Barabasi, IBM

Graduate Assistant: Sukun Li ("Luna") Email

Textbook: Quantum Computation and Quantum Information, Nielsen and Chuang, Cambridge
Other books of interest

Course Prerequisites: Doctoral student or permission of the instructors.

Course Rationale:
This will be a Pace University leading edge computing course for Computer Science PhD and advanced masters students. This quantum computing course will demonstrate that the Seidenberg School is providing a leading-edge computing technology education to its students, thus making Pace University competitive with major universities in the greater NYC area.

Course Description:
This course provides an introduction to the theory and practice of quantum computing. Topics covered include quantum computing circuits, particularly quantum gates, and comparison with classical computing gates and circuits; quantum algorithms; mathematical models of quantum computation; quantum error correcting codes; and quantum cryptography.

Course Methodology:
Drs. Tappert and Frank will cover the book and background material, and Prof. Barabasi will handle the tools and arangements with IBM. We will have student teams working on projects with the outcome of each project being a paper presented at the May 2018 Research Day Conference. All PhD students must make a presentation on some course material.

Course Website:
An extensive course website presents most of the course information. Some material, basically of internal nature, resides on Blackboard. Links in the left menu area of the course website are to:

Assessment:
Project work and presentations 50%, Qualifying/Final exam 50%

Learning Objectives:

  1. Learn the background material in computer science, mathematics, and physics necessary to comprehend quantum computing.
  2. Understand quantum computing circuits, particularly quantum gates, and comparison with classical computing gates and circuits.
  3. Understand quantum Fourier transform and its applications.
  4. Understand quantum search algorithms.
  5. Understand the physical realization of quantum computers.
  6. Understand quantum operations, quantum noise, and quantum error correction.
  7. Understand quantum information theory and its comparison to Shannon's entropy and traditional information theory.
  8. Understand in detail the central results of quantum computing.
  9. Develop a working understanding of the fundamental tools and design methods of quantum computing.
  10. Develop expertise in writing programming code for quantum computers.

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Student Responsibilities  Pace University Appropriate Use Policy for Information Technology

Incompletes: to be fair to those students completing the course in a timely manner, the grade of those students taking an incomplete will be reduced by a full letter grade for each semester, or portion thereof, that the incomplete is in effect.