When I finished my undergrad degree, I regretted taking CS 467. I spent about 80% of my coursework time on that class. Now that I see the same notation and set theory used in a statistics textbook I am reading, I would say the course was totally worth it. It would have helped if I had taken the assignments lightly, since the assignment questions were always a puzzle to students. The time would have been better spent working through examples in the textbook. Looking back at my elective courses, I am glad I didn’t take a CS elective that was mostly programming, such as CS 349. Classes like CS 360 enhance math skills which are helpful in graduate studies.
At the exam today Professor Mosca wore a suite again. He does that too often teaching the class. Maybe he wants us to take graduate courses in the field. He talks about the classes every time a relevant lecture topic comes up.
Compared to other classes I took this term, I learned the most from this one. I read the first few chapters of the textbook before the class, but got bogged down by the notation. Taking the class and working on the assignments helped me to learn it. The slides had extra material to go along with the textbook.
Those walks in the QNC building were memorable. The wooden stairs hanging in the air with light filtering through glass walls and white boards beside sofas capture the spirit of the building.
The solutions to homework assignments were always simple, but they’re challenging when going through the material for the first time. I spent many days this term working on them, long enough that I would have read How to Solve It at the start of the term. I plan to read that book as I start work next month, since the problems solving skills always help.
CS 467 is Introduction to Quantum Information Processing, which I have with Michele Mosca. He has received many awards and written the textbook with other authors for the course. However, he is a very approachable professor. He gives detailed answers to questions during lecture and stays after class to answer questions. He makes the subject more approachable pointing out areas that he had trouble with when he started in the field, making sure we are better prepared to read papers in the area. With people like him doing research and teaching students, quantum computing will be ubiquitous in 15 years and Waterloo will be heading the effort.
Besides wanting to take the course for a long time, the course also cleared up assumptions I had:
- What makes quantum theory able to accommodate Schrödinger’s cat is the probabilistic representation of qubits, which isn’t magical at all in mathematical terms.
- Information can only travel as fast as light, as in the case of quantum teleportation where classical bits are sent to transfer qubits
- Unmeasured quantum states can change simultaneously, as in entanglement
- The secret ingredient to quantum computation: only measure what you need to know. As in the case of error correction codes, only measure the error