Undergraduate Programme and Module Handbook 2020-2021 (archived)
Module COMP4117: ALTERNATIVE COMPUTING
Department: Computer Science
COMP4117: ALTERNATIVE COMPUTING
| Type | Open | Level | 4 | Credits | 10 | Availability | Not available in 2020/21 | Module Cap | None. | Location | Durham |
|---|
Prerequisites
- COMP2181 Theory of Computation AND (COMP2261 Artificial Intelligence OR COMP2231 Software Methodologies)
Corequisites
Excluded Combination of Modules
Aims
- To introduce students to Natural Computing as a paradigm of Computer Science concerned with both simulating natural processes as well as emulating them for algorithmic advantage.
- To introduce students to Quantum Information Processing and Quantum Computing with emphasis on where these may be advantageous over the classical approach.
Content
- Philosophy of Natural Computing
- Ant Colony Optimization
- DNA Computing
- Models of DNA Computation
- DNA Self-Assembly
- Membrane Computing
- Qubits and Quantum Key Distribution
- Computing with Multiple Qubits
- Quantum Gates and Circuits
- Quantum Algorithms
- Shor's Algorithm for Factorisation
Learning Outcomes
Subject-specific Knowledge:
- On completion of the module, students will be able to demonstrate:
- an understanding of various ways in which computation can be accomplished through the mimicking of processes in nature
- an understanding of various ways in which computation can be accomplished through the use of natural processes outside of a conventional chip
- an understanding of the fundamental notions from Quantum Information Processing.
- an understanding of the workings of Quantum Computing.
Subject-specific Skills:
- On completion of the module, students will be able to demonstrate:
- an ability to formulate and solve computational problems using methods inspired by nature.
- an ability to formulate and solve computational problems using natural materials other than the conventional chip.
- 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 Alternative Computing.
- Summative assessment assesses the application of methods and techniques.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| lectures | 22 | 1 per week | 1 hour | 22 | |
| preparation and reading | 78 | ||||
| total | 100 |
Summative Assessment
| Component: Coursework | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Summative Assignment | 100% | No | |
Formative Assessment:
Example formative exercises are given during the course.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University