I asked and was permitted to create this course for Fall 2020. This semester (F2021) is the 2nd running.

Based on a suggestion from Dr. Chandrasekhar Narayanaswami, Distinguished Research Staff Member, Member IBM Academy of Technology, Member IBM Industry Academy, Thomas J. Watson Research Center, Yorktown Heights.

1. my former PhD student.

2. now on the ECSE advisory board.

It replaced ECSE-4750 Computer Graphics, which I'd taught for about 40 years.

It's not the 1st or 2nd quantum course at RPI, but might be in the SoE.

Like all my courses, QCP has a blog: https://wrf.ecse.rpi.edu/Teaching/quantum-f2021/

1. that runs on my virtual web server: wrf.ecse.rpi.edu

   1. hosted by ECSE

   2. I'm root, and update and manage it.

   3. This takes my time, but I can configure it as I want.

   4. RPI is protected from any security problems I might introduce.

   5. although historically I'm more secure than RPI.

2. the blog is readable by anyone.

   that's only fair since I use so much free material.

3. created with Nikola, https://getnikola.com/, a static site generator.

this year's running of the course:

1. 16 students: 9 undergrad, 7 grad.

2. from 6 different majors:

   1. AERO

   2. CBIO

   3. CSCI

   4. CSYS

   5. ELEC

   6. MATH

The idea was not to compete with, but to supplement the other courses.

I assume that the physicists will deliver ever better quantum computers

1. how to use them?

2. hence the title: Quantum Computer Programming.

Catalog:

Intro to quantum mechanics. Various physical realizations of quantum computing, such as transmon qubit (IBM Q), trapped ion (IonQ), and quantum annealing (D-Wave). Quantum states and qubits. Quantum gates including Hadamard, Pauli-XYZ, Toffoli, Fredkin. Qiskit. Quantum algorithms such as Grover, and Shor. Programming quantum computers using IBM qiskit and Microsoft Quantum.

Pre-requisites:

1. ECSE-2610 (CPTR COMPONENTS & OPER),

2. CSCI-2200 (FOUNDATIONS OF COMPUTER SCI), and

3. PHYS-1200 (PHYSICS II) or permission.

The prereqs select for ECSE seniors. Maybe they could be relaxed.

Source material:

1. Suggested textbooks:

   1. Noson S. Yanofsky and Mirco A. Mannucci, Quantum Computing for Computer Scientists, 2008;

   2. Abraham Asfaw et al, Learn Quantum Computation using Qiskit, http://community.qiskit.org/textbook, 2020

      There's an old and a new version. The old version was more comprehensive.

   3. 14. David Mermin, Quantum Computer Science An Introduction, 2006.

   We used pieces from each of them.

2. Web sites:

   1. IBM's detailed online stuff. Not just qiskit but algorithms etc.

   2. Other universities provided inspiration.

   3. Misc quantum research centers, like Delft

   4. Many videos.

3. I tried to show the principals themselves describing their work and their opinions. E.g., Peter Shor talking about his algorithm and about quantum computing in general.

4. My main job was to be a curator selecting the best material for the class.

Learning Outcomes:

1. Demonstrate proficiency with the mathematics behind quantum computing.

2. Understand important quantum computing algorithms.

3. Understand the three main quantum platforms: transmon qubit, trapped ion, and quantum annealing.

4. Apply that to write and run programs on those platforms.

Lecture technique: primarily show videos and ask questions. Approx 4 of 28 classes were student presentations.

Course content, by lecture

1. Intro to quantum physics, qubit, state as complex vector, superposition, reversibility, no cloning, measurement, entanglement, history.

2. 1 and 2 qubit operators, quantum computation vs classical circuits

3. more on math, operators, no cloning

4. more on entanglement with Toffoli gate, complexity theory, history of theoretical CS, intro to hw

5. abstract computation models, complexity classes, theory preceded implementation, hw, IBM qiskit

6. IBM quantum computing

7. quantum computing 2021 update, misc from qiskit textbook

8. Grover's algorithm

9. Student presentations

10. Student presentations ctd

11. Student presentations ctd, Shor's algorithm

12. Shor's algorithm, ctd

13. Qiskit applied algorithms: HHL to solve linear systems

14. Qiskit applied algorithms ctd: simulating chemistry, image processing

15. Amazon Braket

16. Amazon Braket ctd, D-Wave, IonQ

17. D-Wave ctd

18. D-Wave ctd, quantum compution compiler optimization

19. quantum compution compiler optimization ctd, quantum commununication

20. quantum commununication ctd, secret sharing

21. What can Quantum do for AI?

22. Quantum machine learning

23. cryo-CMOS control, IonQ

24. IBM Quantum State of the Union, quantum computers in financial risk analysis

25. NYU reaction to IBM Eagle, Tristan Meunier slides (which start by nicely summarizing quantum computing)

26. student presentations etc

27. student presentations

28. student presentations

Lectures contain many links to current news stories.

Homeworks:

1. math etc

2. programming actual quantum computers of three architectures:

   1. IBM with qiskit

   2. D-wave and IonQ on Amazon Braket

Grades: many homeworks, in class presentation, final project with writeup and presentation

Extra work for 6000 level: more research content in project, documented.