- Professor Pete Vukusic (Professor - Exeter University)
|Delivery Type||Delivery length / details|
|Lecture||11 x 1 Hour Lectures|
|Practical||11 x 2 Hour Practicals|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Continuous assessment of coursework.||50%|
|Semester Assessment||A numerical project report.||50%|
|Supplementary Assessment||As determined by the Departmental Exam Board||100%|
On successful completion of this module students should be able to:
Demonstrate a familiarity with various techniques and algorithms for scientific computing and analysis.
Devise and implement numerical programs to perform the relevant algorithms.
Numerical solutions to mathematical and physics problems is a cornerstone of both physics and applied mathematics research. This module is a continuation of the practical-based module PH36010. The numerical techniques are more advanced and will require more detailed understanding of the numerical methods.
This module builds on the Numerical Methods module PH36010. Methods of solving (large) systems of simultaneous linear equations are introduced. This is then used to numerically solve partial differential equations. Monte Carlo methods are introduced as a general method. More specifically, Metropolis Monte Carlo methods for solving problems in statistical mechanics are covered. The students will implement these algorithms and apply them to simple physical problems.
Iterative methods for solving sparse systems of linear equations.
Numerical methods for partial differential equations.
Monte Carlo methods.
Metropolis Monte Carlo methods for simulation of statistical mechanical systems.
|Skills Type||Skills details|
|Application of Number||Throughout the module.|
|Information Technology||This module involves programming and computational visualisation.|
|Personal Development and Career planning||Programming skills.|
|Problem solving||Throughout the module.|
|Subject Specific Skills||Programming, numerical methods.|
This module is at CQFW Level 7