CMSC/PHYS 457: Introduction to quantum computing (Spring 2019)

Syllabus (PDF)

Overview

An introduction to the concept of a quantum computer, including algorithms that outperform classical computation and methods for performing quantum computation reliably in the presence of noise. As this is a multidisciplinary subject, the course will cover basic concepts in theoretical computer science and physics in addition to introducing core quantum computing topics.

Course topics

The following is list of topics is tentative and subject to change: quantum phenomena, basics of quantum information, quantum entanglement and quantum protocols, quantum circuits and universality, relationship between quantum and classical complexity classes, simple quantum algorithms, quantum Fourier transform, Shor factoring algorithm, Grover search algorithm and its optimality, quantum error correction and fault tolerance, and selected additional topics as time permits.

Prerequisites

(MATH240 or PHYS274) and (CMSC351 or PHYS373)

Coordinates

Time: Tuesday/Thursday, 12:30–1:45 pm
Location: CSI 1122

Instructor

Andrew Childs (amchilds@umd.edu)
Office hours: Tuesday and Wednesday, 2–3 pm, ATL 3100F; also available by appointment

Teaching assistants

EmailOffice hours (in AVW 4101/4103)
Nishant Rodrigues ngrodrig@cs.umd.edu Monday, 10–11 am
Jue Xu juexu@cs.umd.edu Wednesday, 1–2 pm

Piazza

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 quickly get help from classmates, TAs, and the instructor. Instead of emailing questions to the teaching staff, please post questions on Piazza. Please do not use any other online forum for course discussion without prior permission of the instructor.

Texts

Primary: Paul Kaye, Raymond Laflamme, and Michele Mosca, An Introduction to Quantum Computing, Oxford University Press (2007).

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

Evaluation

Your final grade will be determined as follows:

Assignments 30% (lowest assignment grade will be dropped)
Midterm exam 10%
Project 30%
Final exam 30%

Assignments

There will be 5 homework assignments during the course. Assignments will be made available below and should be submitted to Gradescope. Please register for Gradescope using the course code (to be provided in class) and check that you are able to upload solutions by making a test submission well in advance of the first assignment deadline. You should submit your completed assignments in PDF format, either as a typeset document (preferred) or a clear scan of handwritten solutions.

A1 problems A1 solutions
A2 problems A2 solutions
A3 problems A3 solutions
A4 problems A4 solutions
A5 problems A5 solutions

Your solutions must be submitted before the start of class on the due date. Gradescope will not accept submissions after the deadline, and since solutions will be posted on the course website promptly, late assignments will not be accepted. The lowest assignment grade will be dropped.

Your solutions 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 returned via Gradescope, and grades will be available through that system. If you think a problem has been graded incorrectly, you may submit a regrade request on Gradescope within one week. Regrade requests must include a detailed justification. The course staff will carefully review your solution and could raise or lower your score.

You are encouraged to discuss homework problems with your peers, with the TA, and with the course instructor. However, your solutions should be based on your own understanding and should be written independently. For each assignment, you must either include a list of students in the class with whom you discussed the problems, or else state that you did not discuss the assignment with your classmates.

Project

A significant component of the course will be a project on a topic of your choice. The goals of this project are to explore a topic in in depth, to give you experience reading the research literature, to identify possible future research directions, and to practice your scientific communication skills through both an in-class presentation and a written report.

You will have considerable freedom in deciding how to structure your project. You may work either on your own or in a group of two or three students. Suggested project types include

Your project will include the following deliverables:

Your project proposal and reports must be typeset in LaTeX and submitted in PDF format via Gradescope. Further details regarding expectations for the project will be discussed in class and on Piazza.

Exams

The course will include a midterm exam and a comprehensive final exam. Both exams will be given in our regular lecture room (CSI 1122). The midterm exam will be held on Thursday, March 14, at the regular class time (12:30–1:45 pm). The final exam will be held on Tuesday, May 21, from 1:30–3:30 pm (as scheduled by the registrar).

Course policies and academic accommodations

You should be familiar with the University of Maryland course policies.

As mentioned above, extensions to assignment due dates will not be granted for any reason, so that all students can have timely access to solutions. In circumstances that justify an excused absence, appropriate accommodations will be made, in accordance with the course-related policies described at the above link.

Any student eligible for and requesting reasonable academic accommodations due to a disability is asked to provide, to the instructor during office hours, a letter of accommodation from the Accessibility and Disability Service (ADS) office within the first two weeks of the semester.

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 and its faculty take this feedback seriously, and appreciate your input. Toward the end of the semester, please go to www.courseevalum.umd.edu to complete your evaluation.

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