Scientific Computing
| Code | School | Level | Credits | Semesters |
| PHYS4007 | Physics and Astronomy | 4 | 10 | Autumn UK |
- Code
- PHYS4007
- School
- Physics and Astronomy
- Level
- 4
- Credits
- 10
- Semesters
- Autumn UK
Summary
The first third of the module will cover verification issues: examining how one demonstrates that codes work by comparing them to known solutions. Students will write bespoke routines (integrators, FFTs etc) and then comparing the solutions with inbuilt MatLab commands. This will include the generation of mock data with noise to see whether a known solution can be recovered.
Once verification had been established, the middle part of the module will deal with validation. Specifically, how to check convergence to a solution by altering timestepping and resolution in the model and/or by lowering the number of parameters / points used in a fit. This will be illustrated with an integration problem for which the integrator can be changed as well as the tolerance.
The module will finish with a small project designed to test the students understanding of these issues. Topics to be considered would include:
- chaos;
- random walks;
- N-body;
- Monte-Carlo estimation;
- multi-variable minimization.
For specific coding exercises the module will assume that MatLab is being used, although the general principles, of course, apply to any programming environment.
Target Students
Students in the 3rd year of Physics programmes. Students in the 3rd or 4th year of Mathematical Physics, Chemistry and Molecular Physics, or Natural Sciences programmes.
Classes
This module is based on a series of computer practical sessions supplemented by lectures
Assessment
- 10% Coursework 1: Solving ODEs
- 10% Coursework 2: Signal Processing Task
- 80% Project: Mini-Project Report (~3000 words)
Assessed by end of autumn semester
Educational Aims
This module aims to provide students with the skills necessary to use computational methods in the solution of non-trivial problems in physics and astronomy. Students will also sharpen their programming skills.Learning Outcomes
Knowledge and Understanding
On successful completion of the module, students will have enhanced their:
• A2 knowledge and understanding of the scientific method
• A4 knowledge of computational methods for the analysis of physical problems
• A5 knowledge of scientific computing
Intellectual Skills
On successful completion of the module, students will have demonstrated their ability to:
• B1 apply computational methods to the quantitative analysis of physical situations
• B2 apply high levels of numeracy and analysis
• B3 apply techniques of problem solving
• B4 apply high levels of computer literacy.
Professional/Practical Skills
On successful completion of the module, students will have demonstrated their ability to:
• C1 formulate problems in physics using appropriate mathematical language
• C4 model physical problems using appropriate computational methods
Transferable/Key Skills
On successful completion of the module, students will have demonstrated their ability to:
• D3 meet deadlines and manage their time effectively
• D4 make effective use of general IT tools for acquiring, processing, and presenting information
• D5 communicate effectively in writing, in particular to report critically on the results of an investigation.