General Information

An introduction to quantum computing for students who have not necessarily had prior exposure to quantum mechanics. This course is intended for physicists, electrical engineers, and computer scientists. Topics include: foundational algorithmic building blocks and quantum algorithms; variational quantum algorithms (for physics simulation and for combinatorial optimization); quantum machine learning; basic physics of quantum computing hardware implementation. There will be substantial programming exercises implementing quantum algorithms to run on simulators and quantum computers in the cloud.

Outcome 1: Students will be able to understand and have the knowledge to implement core quantum algorithms.

Outcome 2: Students will be able to apply some of the quantum algorithms studied to new application problems.

Outcome 3: Students will be able to explain key challenges in constructing quantum computers and in running quantum algorithms on current quantum computers.

Prerequisites

Prerequisite: MATH 2940 or equivalent, and CS 1110 or equivalent exposure to Python. Co-meets with AEP 5310.

Topics Covered

Workload

The workload is highly dependent on your comfort with Python (the lectures focus on the physical, mathematical, and algorithmic background with no programming, whereas the homework assignments are mostly coding). They are released about one week before the due date but assigned approximately once every two weeks; each takes approximately 3-5 hours. [Spring 2024]

General Advice

Testimonials

This course has a lot to cover and I think will be most enjoyed if you are looking to get a cursory introduction to quantum algorithms. That makes up the second half of the course and the lectures were a little dry–they mostly just go through each step of implementing the algorithms. They don’t really “build” up–it’s mostly the professor explaining why an already-existing implementation works. Some of the theory is glossed over (e.g. why you implement something a certain way, proofs behind some necessary mathematical theorems). The first half of the class is more focused on background; if you have taken a quantum mechanics class, a fair bit of it will probably be review (e.g. bra-ket notation, early QM experiments) but is taught through a slightly different lens, which was interesting. However, a lot of theory is skipped over (physical implementation of quantum computers and gates) and the professor was not always helpful in answering the more theoretical questions. Rating: 3/5. [Spring 2024]

Past Offerings

Semester Professor Median Grade Syllabus
Spring 2024 Peter McMahon N/A AEP3100_SP24.pdf