Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
Semester 2 - Online
|Fees||Look up fees|
This subject will explore the fundamentals of quantum programming and quantum algorithm design. The subject will introduce students to a range of different quantum programming platforms and languages, and will include hands-on modules. The students will be prepared to write quantum programs, implement a range of simple quantum algorithms, such as Grover’s and Shor’s algorithms, and to execute quantum programs on a quantum computer through a cloud access.
This subject will be made up of three parts:
- Fundamentals of quantum computing and quantum programming, including running quantum programs on actual cloud-based quantum computers.
- Programming fundamental quantum algorithms, such as the Deutsch–Jozsa, Grover, Shor and HHL algorithms.
- Quantum programming for cutting edge research topics, such as quantum error correction, variational quantum circuits and quantum machine learning.
Intended learning outcomes
On the completion of this subject, students should be able to:
- 1. Develop and understand the fundamental aspects of quantum computing.
- 2. Design and implement simple quantum algorithms on multiple quantum hardware architectures.
- 3. Construct programs for fundamental quantum algorithms on a cloud-based quantum language/architecture.
- 4. Identify the basic building blocks for the fundamental quantum algorithms and understand how/when they can be used in new algorithms.
- 5. Analyse and describe modern quantum algorithms, including quantum error correction, VQE, QAOA and quantum machine learning.
- Ability to undertake problem identification, formulation and solution.
- Ability to utilise a systems approach to solving complex problems and to design for operational performance.
- Ability to manage information and documentation.
- Capacity for creativity and innovations.
- Ability to communicate effectively, with the CIS team and with the community at large.
Last updated: 21 June 2021