CMSC/PHYS 457: Introduction to Quantum Computing

University of Maryland, Spring 2025

Instructor: Runzhou Tao

Staff:

NameEmailOffice Hours
Prof. Runzhou Taorztao@umd.eduBy appointment or After class
Rushil Dandamudirushilcd@umd.edu12pm - 2pm Monday at AVW 4160
Seyed Sajjad Nezhadisajjad@umd.edu1:30pm - 3:30pm Thursday at AVW 4160

Time: Tue & Thu 3:30pm - 4:45pm

Location: CSI 3117

Description: 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.

Previous Offering of the Course

Generics

Prerequisite: Familiarity with complex numbers and basic concepts in linear algebra (e.g., eigenvalues, eigenvectors, Hermitian and unitary matrices). 1 course with a minimum grade of C- from (MATH240, PHYS274); and 1 course with a minimum grade of C- from (CMSC351, PHYS373).

Syllabus: see below

In general, please send your questions/requests via Piazza or email. We will reply as soon as possible.

Evaluation: assignments (40%), exams (40%), and project (20%). Details in the policy page.

How to Navigate Through the Course

  • Quantum information and computation is an exciting emerging field, but it’s impossible to cover everything in an introductory course. The main goals are:
    1. Understand and comprehend the theoretical foundation of quantum information and computation.
    2. Cover a selective collection of fundamental topics in quantum computation.
    3. Learn about the research frontier of one specific topic via the course project.
  • Expect a large amount of reading materials and significant effort given the difficulty of the topics.
  • The course project is meant to train your ability to navigate literature and understand research papers. Original contributions are welcome but not mandatory. The main purpose is to facilitate future research endeavors.

Assignments

Homework assignments must be submitted electronically to ELMS. If you have trouble with electronic submissions, contact the instructor immediately.

We highly recommend using LaTeX for typesetting. We will reward the use of LaTeX with a 5% bonus on your homework points. Here’s a good reference and a LaTeX template for writing solutions.

Check the homework page.

Textbooks & Lectures

We will mainly use notes (available online or our own) for lectures. We will also refer to parts of the following textbooks:

  • Paul Kaye, Raymond Laflamme, and Michele Mosca, An Introduction to Quantum Computing, Oxford University Press (2007).
  • Scott Aaronson’s Introduction to Quantum Information Science (UT Austin 2017).
  • M. Nielsen and I. Chuang, Quantum Computation and Quantum Information, Cambridge University Press (10th Anniversary edition, 2011).
  • A. Yu. Kitaev, A. H. Shen, and M. N. Vyalyi, Classical and Quantum Computation (Graduate Studies in Mathematics), AMS, 2002.
  • John Watrous, The Theory of Quantum Information, Cambridge University Press, 2018.

Syllabus

Below is the tentative syllabus (subject to frequent updates). Reading assignments and references are included. All assignments and project-related deadlines are listed under the “Due” column.

DateWeekLectureDue
01/281Introduction; History of Quantum Computing.
Reading: KLM Ch.1, 2.1-2.6 (Slides) (Linear Algebra Cheetsheet)
 
01/30 Linear Algebra Background & Quantum Mechanics Formulation (I).
Reading: KLM 3.1-3.2
 
02/042Quantum Mechanics Formulation (II).
Reading: KLM 3.3-3.4
 
02/06 Quantum Mechanics Formulation (III).
Reading: KLM 3.5
 
02/113 Cancelled due to Campus Closure Assn 0
02/13 Quantum Mechanics Formulation (IV) & No-cloning theorem 
02/184Basic Quantum Circuits/Gates,
Reading: KLM 4.1-4.2
 
02/20 Universal Gate Sets.
Reading: KLM 4.3-4.4
Assn 1
02/255Teleportation and Super-dense Coding (Online)
Reading: KLM 5.1-5.2
 
02/27 Coding Lecture (I) (Online)Proj Proposal
03/046Deutsch-Josza Algorithm
Reading: KLM 6.1-6.4
 
03/06 Simon’s Algorithm
Reading: KLM 6.5
 
03/117Grover’s Algorithm (I)
Reading: KLM 8.1
 
03/13 In-Class Mid-Term 
03/16-228 Spring Break  
03/259Coding Lecture (II) 
03/27 Grover’s Algorithm (II)
Reading: KLM 8.2-8.3