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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2011/2012
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DRPS : Course Catalogue : School of Physics and Astronomy : Postgraduate (School of Physics and Astronomy)

Postgraduate Course: Applied Numerical Algorithms (PGPH11008)

Course Outline
SchoolSchool of Physics and Astronomy CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaPostgraduate (School of Physics and Astronomy) Other subject areaNone
Course website http://www.epcc.ed.ac.uk/msc/ Taught in Gaelic?No
Course descriptionThis course covers the fundamental issues surrounding the use of numerical methods to solve scientific and mathematical problems. It starts by describing the basics of the IEEE floating-point standard for real numbers, and associated issues of accuracy and exceptions. Basic techniques for representing mathematical equations in a numerical form are also described. A number of types of problem are then examined, along with the standard algorithms used to solve them. The most trusted libraries that implement these algorithms are introduced, and the motivation behind utilizing such standard algorithms and/or libraries is discussed. The course covers some of the most popular numerical libraries (eg. LAPACK and FFTW) and techniques (eg. direct and iterative linear equation solvers).

The most important example covered in the course is a convection-diffusion problem which is used to study the way that pollution released from a chimney disperses over land when there is a prevailing wind. The techniques used in deriving and solving the partial differential equations for this particular problem are applicable to a wide range of application areas in science and engineering. For example, similar techniques are commonly used in structural mechanics, fluid dynamics, astrophysics, weather modelling, and fundamental particle physics.

The course is taught using a variety of methods including formal lectures, practical exercises, programming examples and informal tutorial discussions. Lectures are supported by tutored practical sessions in order to reinforce the key concepts.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements Only postgraduates or final year MPhys students with suitable computational background, subject to space restrictions and agreement with relevant Programme Coordinator.
Additional Costs None
Course Delivery Information
Delivery period: 2011/12 Semester 1, Not available to visiting students (SS1) WebCT enabled:  No Quota:  1
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
No Classes have been defined for this Course
First Class First class information not currently available
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S1 (December)2:00
Summary of Intended Learning Outcomes
On completion of this course students should be able to:

- Explain how real-valued quantities are represented on a computer as floating-point variables.
- Discuss the various sources of error relevant for computational simulation.
- Convert simple partial differential equations into numerical form.
- Select and implement the most appropriate method for solving a given system of linear equations.
- Use standard numerical libraries in their own codes.
- Diagnose when a numerical algorithm may be failing due to limited machine precision or floating-point exceptions.
Assessment Information
100% examination consisting of a two hour exam
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsANA
Contacts
Course organiserDr Judy Hardy
Tel: (0131 6)50 6716
Email: j.hardy@ed.ac.uk
Course secretary Yuhua Lei
Tel: (0131 6) 517067
Email: yuhua.lei@ed.ac.uk
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