MAT3052

Techniques for scientific computing

Coordinator: Dr Paul Cally

4 points - Two 1-hour lectures per week - Second semester - Clayton - Prerequisites: MAT2030, MAT2040, MAT2072 - Prohibitions: ASP3132, GPS3272, MAA3132

Objectives On completion of this subject, students will have a basic understanding of a variety of techniques commonly used in large scale scientific computations; be able to design programs which are fast and accurate while using a minimum of computer storage.

Synopsis Topics to be covered include numerical error estimation for ordinary differential equations, adaptive grid and time stepping, multigrid and finite-element methods, efficient data storage including linked lists and tree codes, stiff differential equations, multistep integration schemes, Monte Carlo methods, genetic algorithms and Fast Fourier transforms. Skeleton computer programs will be provided.

Assessment Examination (2 hours): 85% - Assignments and/or tests: 15%

Recommended texts

Press W H, Flannery B P, Teukolsky S A and Vetterling W T Numerical recipes Fortran edn, CUP, 1992

Back to the 1999 Science Handbook