1. Experience Teaching Quantum Computing
Charles C. Tappert, Ronald I. Frank, Istvan Barabasi, Avery M. Leider, Daniel Evans, and Lewis Westfall
Seidenberg School of CSIS

2. Agenda Introduction Teaching a Graduate Course in Quantum Computing
Teaching the Projects Component of the Graduate Course
Teaching High School Students
Quantum computing is a rich area with opportunity
for teaching courses
for funding from the federal government
for employment for our students
for strengthening our nation’s economic future

3. Quantum Computing Race
There is a quantum computing race among the tech giants Google, IBM, and Microsoft, and to a lesser extent Amazon and China’s Alibaba.
IBM has heavy usage on their Q Experience quantum simulator with more than 90,000 users who have run 5,000 experiments and published 110 papers.
Governments, particularly America and China, are funding work in the area with the concern that quantum-computers may soon become large enough to crack current cryptosystems, specifically RSA, giving the country that gets there first a major advantage

4. University Activity and Degrees
91 universities worldwide have some activity in quantum computing
None currently offers a degree specifically in quantum computing, rather making it an elective course, or at most a specialization in their physics or mathematics programs
Some universities are planning future investment in the area
The McMahon Lab at Cornell University which emphasizes quantum computation, will officially begin operation in July 2019
In MIT News, there was recent article about MIT’s quantum computing effort being inhibited by a shortage of quantum knowledge workers

5. Funding in Quantum Computing
There is considerable funding now available
In the U.S. in January 2019, the National Quantum Initiative Act, authorizing $1.2 billion in investment over the next 5-10 years, was signed into law, and is being organized now into different areas that researchers can apply to for funding in quantum computing

6. Advanced Quantum Computing Course
For the last two years, we have offered a quantum computing course for Computer Science PhD and advanced M.S. students
This high-level course demonstrates that our computing school provides a leading-edge technology education to our students
The course meets for three hours weekly, in the evening so working students can attend, for a semester total of 14 weeks
Realizing the need for additional math instruction, we hold separate weekly hour-long sessions of math instruction
Textbooks:
Quantum Computing: A Gentle Introduction (Rieffel & Polak, 2014)
Problems and Solutions in Quantum Computing (Steeb & Hardy, 2018)
Mastering Quantum Computing with IBM QX (Moran, 2019)

7. Advanced Quantum Computing Course
The course provides students with 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 techniques
and quantum cryptography
We also spend almost a full day sometime during the semester visiting the IBM’s T.J. Watson Research Center to see actual quantum computers and hear related presentations

8. Advanced Quantum Computing Course
Ten to twenty students take the course – the majority are PhD in Computer Science (CS) students with a few advanced CS Masters students.
Assessment is based on
the project work and student presentations 40%
midterm exam 20%
final exam 40% (this exam also serves as a qualifying exam for the PhD students)

9. Advanced Quantum Computing Course
The learning objectives of the course are:
Learn the background material in computer science, mathematics, and physics necessary to comprehend quantum computing
Understand quantum computing circuits, particularly quantum gates, and comparison with classical computing gates and circuits
Understand quantum Fourier transform and its applications
Understand quantum search algorithms
Understand the physical realization of quantum computers
Understand quantum operations, noise, and error correction
Understand quantum information theory and its comparison to Shannon's entropy and traditional information theory
Understand in detail the central results of quantum computing
Develop a working understanding of the fundamental tools and design methods of quantum computing
Develop expertise in writing programming code for quantum computers

10. Teaching the Projects Component of the Course
Student projects utilize hands-on labs with simplified quantum program development, live code executions, and projects performed on IBM’s Quantum Experience Platform with access to real Quantum Computers
We use multiple Quantum Computing (QC) Science Kits to teach students quantum computing technology
The objective is to help students gain practical experience via lab exercises and to develop projects to solve relevant and practical problems using quantum computing algorithm and programs

11. Teaching the Projects Component of the Course
The projects involved three types of problems that were coded using Quantum Computing Assembler Language (QASM) and Python
Well-defined quantum computing experiments, such as placing qubits in super positions and implementing quantum entanglement
Optimizations, such as the traveling salesman problem
Practical problems, such as financial portfolio optimization

12. Teaching High School Students
We have taught short courses at several high schools
For example, a 5-day course was taught to the 12th grade at a Brooklyn high school
Day 1 – quantum bit (qubit), |ket> notation for vectors, explanation of gates, matrix notation for kets and gates
Day 2 – superposition and entanglement
Day 3 – Grover’s algorithm
Day 4 – return to superposition and entanglement, present Bloch sphere representation of a qubit
Day 5 – students split into teams, each team reworked set of instructor slides into their own

13. Teaching High School Students
IBM Composer for Creating Quantum Programs

14. Teaching High School Students
Day 5 – student survey ranked topics of interest

15. Conclusions Quantum computing is a rich area with opportunity
for teaching courses
for obtaining funding from the federal government
for employment for our students
for strengthening our nation’s economic future