ECE 396 / COS 396 / QSE 320
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Clarification (2026-09-02). To clear up confusion about the collaboration policy: feel free to solve the problems in the problem sets with whoever you want. However, you should write up the solutions separately, and you should not share these writeups with others.
Lectures: Mondays and Wednesdays, 10:40 am – 12:00 pm, in Friend Center 006
Instructor office hours: Mondays 12:00 – 1:00 pm, in COS 308
TA office hours: Tuesdays and Thursdays 5:00 – 6:30 pm, in COS 301
Instructor: Ewin Tang
Graduate teaching assistants: Lakshika Rathi, Hongkun Chen, Salahedeen Issa
This course will give a mathematically rigorous introduction to the theory of quantum information and quantum computation. Topics of focus include the matrix form of quantum mechanics, entanglement, algorithms, error correction and fault tolerance, and physical platforms for quantum computers.
The course objective is to enable you to:
Requires sophomore linear algebra at the level of MAT 202, 204, 217 or the equivalent. A previous quantum mechanics course will not be required. Beyond linear algebra, a basic understanding of probability, complex numbers, and algorithms is recommended. Please contact the instructor if you wish to take the course but do not currently meet these requirements.
We will be communicating in a few ways:
For urgent or sensitive matters, or matters involving individual grades, please email the course staff. If you wish to talk in person, please go to an office hours session or email one of the course staff members to schedule a private meeting.
Grades will be based on the following components:
| Component | Weight |
|---|---|
| “Meet the professor” | 1% |
| Problem sets & in-class quizzes | 33% (split 16/17) |
| Midterm | 33% |
| Final exam | 33% |
The grading scale below outlines a starting point for your end-of-semester conversion from numeric grade to letter grade. While we may choose to curve final grades, we will never curve grades down; we guarantee that your grade will always be no worse than the grade assigned by the grading scale below. Treat the scale as a contract that reaching a particular bracket guarantees earning at least its corresponding grade:
| Score | 93%+ | 90%+ | 88%+ | 83%+ | 80%+ | 78%+ | 73%+ | 70%+ | 60%+ | <60% |
|---|---|---|---|---|---|---|---|---|---|---|
| Grade | A | A- | B+ | B | B- | C+ | C | C- | D | F |
Please see this university policy for the symbolic meaning of each letter grade, noting that all letter grades other than F are passing grades. Note that this scale does not include an A+; while it is possible to earn an A+, there is no numeric grade which can guarantee it.
I want to get to know you all better! In the first few weeks of the course, I will be hosting 15-minute meetings with groups of 3–4 students at a time. You will receive full credit just for attending; you won’t be graded on the conversation.
Problem sets will make up 16% of your total grade. Tentatively, there will be 6 problem sets, roughly once every two weeks, which will be announced and released according to the course schedule. All problem sets will be mathematical, with some questions asking for proofs; there will be no programming in this course. Typed solutions are encouraged, but high-resolution photos or scans of neatly hand-written solutions are acceptable.
Problem sets are graded on completion only; we may also give each problem set a diagnostic score to give you a sense of how you are doing in the course. The diagnostic score will not affect your grade; it is purely for your information. Late submissions will not be accepted.
Collaboration with other students is allowed and encouraged; the use of AI is not allowed (see the AI policy). Please adhere to the following rules.
After each problem set deadline, there will be a 10-minute in-class quiz, tentatively scheduled for the start of the following class. The quiz is open-book and open-notes, but electronic devices are not allowed; we expect you to bring your problem set solutions. This quiz is designed to test your understanding of the solutions and prepare you for the exams.
We will drop the lowest two grades among all quiz and problem set grades.
The midterm will occur in class, currently scheduled for October 14th. It will be open book and open notes; electronic devices are not allowed.
The final is scheduled to take place on December 16, 4:00 – 7:00 pm. It will be open book and open notes; electronic devices are not allowed.
Should you foresee a need for accommodations for either exam, we encourage you to contact ODS the course staff as soon as possible to discuss your needs further.
Do not use large language models or any other generative AI tools to help with any aspect of the problem sets, including searching for references, computations, or writing: they can be solved with only the course materials, and no external help. Moreover, since they are graded by completion only, using them will not help your grade.
Beyond that, I discourage the use of AI for this course, but you are free to use it in whatever you believe most effectively helps with your learning. In particular, you are allowed to use AI to create notes for quizzes and exams.
Absolute integrity is expected of all Princeton students in every academic undertaking and respect is expected for all communications in this course. You are responsible for understanding the university policies found here and our specific course policies outlined below.
All assignments you turn in must be 100% your own work. You may not copy entire solutions from any internet sources including generative AI models. You may not share solutions with classmates. Students agree that by taking this course, all submitted work may be subject to similarity analysis using plagiarism detection software.
Conduct during exams and quizzes is covered by the University Honor Code. If we suspect a student of inappropriate conduct during either the midterm or final exam, then we will refer the case to the Honor Committee (for in-person exams) or Committee on Discipline (for remotely administered exams). If the appropriate Committee finds the student guilty of inappropriate conduct, then the standard course penalty is automatic failure of the course, but the course’s instructor may adjust this penalty to as little as 0 credit for the portion of the exam or quiz on which the violation took place. The presiding Committee may impose additional penalties.
For students with disabilities, all accommodations requests must go through The Office of Disability Services for approval. Please request your accommodations early in the semester to give us adequate time to arrange your approved academic accommodations.
Princeton University offers a variety of resources to support your mental health and well-being. If you or someone you know needs support or is looking to access specific services, consider reaching out to these university and student-led resources: