This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.
Undergraduate Handbook 2025-2026 (archived)
Module COMP4117: Quantum Computing
Department: Computer Science
COMP4117: Quantum Computing
| Type | Level | Credits | Availability | Module Cap | Location |
|---|---|---|---|---|---|
| Open | 4 | 10 | Available in 2025/2026 | None. | Durham |
Pre-requisites
- COMP2261 Artificial Intelligence AND COMP2211 Networks and Systems
Corequisites
Excluded Combinations
- MATH3391: QUANTUM COMPUTING III
Aims
- To introduce students to Quantum Information Processing and Quantum Computing with emphasis on where these may be advantageous over the classical approach.
Content
- Qubits and Quantum Key Distribution
- Computing with Multiple Qubits
- EPR paradox and Quantum State Transformations
- Quantum Gates and Circuits
- Quantum Algorithms
- Quantum Networking
Learning Outcomes
Subject-specific Knowledge
- On completion of the module, students will be able to demonstrate:
- an understanding of the fundamental notions from Quantum Information Processing
- an understanding of the workings of Quantum algorithms
- an understanding of the principles of Quantum networking
Subject-specific Skills
- On completion of the module, students will be able to demonstrate:
- an ability to apply basic methods from Quantum Physics for the study and analysis of systems of Quantum Information Processing and Quantum Computing.
Key Skills
- On completion of the module, students will be able to demonstrate:
- an ability to formalise computation problems in a variety of contexts
- an ability to reason mathematically about information in a variety of ways.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures enable the students to learn new material relevant to Quantum Computing.
- Summative assessment assesses the application of methods and techniques.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 22 | 2 per week | 1 hour | 22 | |
| Preparation and Reading | 78 | ||||
| Total | 100 | ||||
Summative Assessment
| Component | Component Weighting | Element | Length/Duration | Element Weighting | Resit Opportunity |
|---|---|---|---|---|---|
| Examination | 100% | Online Examination | 2 hours within 3 hour timed window | 100% |
Formative Assessment
Example formative exercises are given during the course.
Students who do not attend monitored activities shown under Teaching Methods
and Learning Hours, or who fail to complete the summative or formative
assessment(s) specified above, may be subject to the Academic Progress
procedures defined in the University's General Regulation V, and may be
required to leave the University.