Courses Offered

COMP3366 Quantum algorithms and computer architecture

COMP3366 Quantum algorithms and computer architecture

Instructor(s):Yang Yuxiang
(Class A) No. of credit(s):6
Recommended Learning Hours:
Lecture: 36.0
Tutorial: 3.0
Pre-requisite(s):MATH1853; and COMP2119
Mutually exclusive with:  

Course Learning Outcomes

1. [Concepts]
Familiar with the quantum circuit model, rules of quantum computation as well as basic elements of quantum computing architecture.
2. [Problem solving]
Able to solve basic problems in quantum computing and quantum error correction, such as evaluating the outcome and the efficiency of an algorithm or determining the distance of a quantum code.
3. [Algorithm design]
Proficient in one quantum programming language. Able to identify the right quantum algorithm for a specific task. Able to work as a team in designing a quantum algorithm and presenting the algorithm to the audience.
Mapping from Course Learning Outcomes to Programme Learning Outcomes

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.


Calendar Entry:
Quantum computing can perform hard computational tasks that are far beyond the reach of conventional computers. This course will focus on quantum computing and its realization, offering a tour through the most important concepts and the most recent progresses. The course consists of four major parts: basics of quantum computing, quantum algorithms, quantum machine learning, and quantum error correction. The course starts with an introduction to the essential ingredients of quantum circuits. We will get familiar with quantum computing by going through representative quantum algorithms and visiting more advanced topics in quantum machine learning. We will then discuss how to build a quantum computer: various ways of implementing quantum computations and coping with noises will be discussed. Finally, we will conclude the course with an overview of recent progresses and with a perspective on the future of quantum computing. Tutorials will also be offered on quantum programming, where we will design our own quantum algorithms that address practical problems.

Detailed Description:

Basics of Quantum Computing Mapped to CLOs
Quantum bits, gates, and measurements1
Universal gate set and complexity1
Quantum Programming Language3
Quantum Algorithms Mapped to CLOs
Quantum Fourier transform2, 3
Shor’s algorithm2, 3
HHL algorithm2, 3
Quantum Machine Learning Mapped to CLOs
Quantum support vector machine2, 3
Variational algorithms2, 3
Quantum neural networks2, 3
Quantum Error Correction Mapped to CLOs
Error Correction Codes1, 2, 3
Fault tolerance1, 2
Implementation of quantum computing1

Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

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