Title of Project:
Eigenvalue Problems for (large) Matrices
Code: MM2122A
Supervisor: Professor Marco Marletta
Project description:
This project is about solving the matrix eigenvalue problem Au = λu. The
ultimate aim is to deal with the case when A is a large sparse matrix, but the
student will rst study methods which are used for full matrices. For sparse
matrices, it will involve studying numerical methods which exploit the sparsity
patter, together with possible additional properties such as being Hermitian.
Many of the algorithms to be studied are described in `Matrix Computations’
by Golub and Van Loan, and are implemented in software packages such as
LAPACK and ARPACK. The ability to programme in a suitable language such
as MATLAB or Python will be important. Special methods for PDEs will also
be studied if time permits.
Prerequisite 2nd year modules:
None
Recommended 3rd year module for concurrent study:
None
Number of students who can be supervised on this project:
1