Introduction to quantum information processing (CMSC 657, Fall 2022)

Course description

An introduction to the field of quantum information processing. Students will be prepared to pursue further study in quantum computing, quantum information theory, and related areas.


Basic model of quantum computation (reversible computing, qubits, unitary transformations, measurements, quantum protocols, quantum circuits); quantum algorithms (simple query algorithms, the quantum Fourier transform, Shor's factoring algorithm, Grover's search algorithm and its optimality); quantum complexity theory; mixed quantum states and quantum operations; quantum information theory (entropy, compression, entanglement transformations, quantum channel capacities); quantum error correction and fault tolerance; quantum nonlocality; quantum cryptography (key distribution and bit commitment); selected additional topics as time permits.

See the detailed schedule (which may evolve as the semester progresses) for more on the course content, including recommended readings.


Familiarity with complex numbers and basic concepts in linear algebra (e.g., eigenvalues, eigenvectors, Hermitian and unitary matrices) is required. Students should have strong mathematical skills but are not expected to have taken previous courses in quantum mechanics or the theory of computation. If you have any questions about your preparation for the course, please contact the instructor.

Class format

Lectures will be held in person and will be recorded for later viewing (on a best-effort basis), with videos posted on the Panopto section of Canvas. We will reevaluate this format as the semester progresses and may make adjustments in response to evolving conditions and university guidelines.



Andrew Childs (
In-person office hour: Tuesday, 1–2 pm, ATL 3359 (enter QuICS suite through 3100, turn left to enter wing 3, then turn right)
Zoom office hour: Thursday, 3–4 pm (Zoom link provided on Canvas)

Teaching assistants

EmailOffice hours
Doruk Gur Wednesday, 11 am–noon, IRB 5111 and on Zoom (link on Canvas)
Nishant Rodrigues Monday, 2–3 pm, ATL 3100D
Friday, 10–11 am on Zoom (link on Canvas)


We will use Piazza for class announcements and discussion. You should sign yourself up for the course Piazza page as soon as possible. This is the best way to stay up to date on what is happening in the course and to quickly get help from classmates, TAs, and the instructor. Instead of emailing questions to the teaching staff, please post questions on Piazza. You are encouraged to post questions publicly whenever possible so the whole class can benefit from the discussion, though you can also post private questions for any personal issues. Please do not use any other online forum for course-wide discussion without prior permission of the instructor.


Michael A. Nielsen and Isaac L. Chuang, Quantum Computation and Quantum Information, Cambridge University Press (2000).


Your final grade will be determined as follows:

Assignments 40%
Project 25%
Final exam 35%

Your lowest assignment grade will be dropped. If you are unable to complete an assignment by its deadline due to an excused absence (as per the UMD graduate course policies), the remaining assignments will be reweighted.


There will be five homework assignments during the course. Assignments will be made available on Canvas and should be submitted using Gradescope. Please check that you are able to upload solutions by making a test submission well in advance of the first assignment deadline. Please submit completed assignments as PDF files, either as a typeset document or a clear scan of handwritten solutions, by the deadline stated on the assignment. Gradescope will not accept submissions after the deadline, and late assignments will not be accepted under any circumstances so that solutions can be made avilable promptly (on Canvas). You can replace a submission as many times as you like before the deadline (only the final submission will be graded).

Your answers to the assignment problems should be written neatly and concisely, and you should always aim to present the simplest possible solution. Your assignment grades will be based on both correctness and clarity. Graded assignments will be available on Gradescope. If you think a problem has been graded incorrectly, you may submit a regrade request on Gradescope. Regrade requests must be submitted within three business days after an assignment is returned and should include a detailed justification.

You are encouraged to discuss homework problems with your peers, with the TAs, and with the course instructor. However, your solutions should be based on your own understanding and should be written independently. You should not read solutions for the same or similar problems to the ones you are assigned until after your assignment has been submitted.


As a course project, you will write an expository paper on a topic of your choice from the quantum information literature. You should submit a project proposal by Wednesday, October 12; a project progress report by Wednesday, November 9; and your completed paper by Wednesday, December 7. Submissions should be made on Gradescope. Further details, including a partial list of possible project topics, will be made available on the project page.

Final exam

The course will include a comprehensive, take-home final exam. The exam will be made available on Canvas by 7 am on Wednesday, December 14, and will be due on Gradescope by 11:59 pm the same day. You may choose to take the exam during any two-hour period during that time.

Course policies and academic accommodations

We will follow the standard University of Maryland graduate course policies. You should be familiar with them.

Any student eligible for and requesting reasonable academic accommodations due to a disability is asked to provide an electronic letter of accommodation from the Accessibility and Disability Service office within the first two weeks of the semester. Please meet with the instructor to discuss any issues related to the implementation of your accommodations.

If you plan to observe any holidays during the semester that are not listed on the university calendar, please provide a list of these dates by the end of the first two weeks of the semester.

Course evaluations

Student feedback is an important part of evaluating instruction. The Department of Computer Science takes this feedback seriously and appreciates your input. Toward the end of the semester, please go to to complete your evaluation.

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