Special Topics in Quantum Information Science (EE5105, 113-2, Spring 2025)

Prerequisites

Students enrolling in this course are expected to have a solid understanding of linear algebra, equivalent to the content covered in EE1002 (Engineering Mathematics - Linear Algebra). Additionally, familiarity with basic concepts of quantum information science, as taught in CommE5061 (Quantum Information and Computation), is recommended for better comprehension of the material.

Course Staffs

There is no TA for this offering.

Topics

This is an advanced course intended for students interested in research in quantum information science. We plan to cover various research topics in quantum computing, with emphasis on quantum algorithms, including:

• Mathematical preliminaries
• Clifford+T synthesis
• Quantum algorithms for algebraic problems
• Learning properties of quantum states
• Quantum query complexity and lower bounds
• Quantum walk algorithms
• Hamiltonian simulation algorithms
• Quantum singular value transform

References

There is no required textbook. Good references for background materials include

• Quantum Computation and Quantum Information by Nielsen and Chuang
• The Theory of Quantum Information by Watrous
• Classical and Quantum Computation by Kitaev, Shen, and Vyalyi
• An Introduction to Quantum Computing by Kaye, Laflamme, and Mosca

These lecture notes will often be consulted:

• Lecture Notes on Quantum Algorithms by Andrew Childs
• Lecture Notes on Quantum Algorithms for Scientific Computation by Lin Lin
• Quantum Computation and Quantum Information by Ryan O’Donnell
• Quantum Computing: Lecture Notes by Ronald de Wolf

References for each topic covered in this course will be listed along with the schedule below.

Evaluation

• Assignments (55%)
• Scribes (5%)
• Exam (20%)
• Project (20%)

Assignments

The course includes five written homework assignments, each contributing 10% to the final grade. Additionally, an “Assignment 0” (worth 5% of the total grade) will be distributed during the first class to help students assess whether this course is suitable for them. All assignments must be typeset using LaTeX. An online editor, such as Overleaf, may be useful if you prefer not to set up a LaTeX toolchain yourself. The assignments will be made available and should be submitted using NTU COOL.

Late Submission Policy:

• Submissions within one week: 20% penalty.
• Submissions within two weeks: 40% penalty.
• Submissions after two weeks will not be accepted.
• No late submission is accepted for Assignement 0.

Policy on Using AI Tools: If you use an AI tool, you must disclose the name of the tool and how you use it in your submission. Any use of AI tools must align with the policy that all submissions must be based on your own understanding.

Scribes

Each student is required to submit a scribe individually for at least one class meeting.

Exam

An exam will be given in the week of final exams.

Project

Students are required to form groups of up to two members for the final project. Project presentations will take place during the last few weeks of the semester. Each group must submit a written project report (typeset in LaTeX) after the last class meeting.

The project consists of the following three parts:

• A project proposal (due April 8), worth 20% of your project grade
• A presentation in class, to be scheduled in the last two weeks of class (40%)
• A final paper (40%, due in the week of June 3)

Each group should email the instructor to schedule a meeting before the proposal deadline.

A list of possible topics can be found here.

Schedule (Tentative)

† An: Assignment #n, PP: project proposal, FP: final paper