Numerical Methods for Elliptic and Parabolic Partial Differential Equations Autumn Semester 2019

Lecturer
Prof. Dr. Christoph Schwab
Assistants
Fernando Henriquez
Maksim Rakhuba

Lectures

Tuesday - 10:15-12:00 - HG E 21
Thursday- 08:15-10:00 - HG E 1.2
First Lecture: Tuesday 17th of September, 2019

Exercise Classes

Wednesday - 09:15-10:00 - HG E 1.2
First Exercise Class: Wednesday 25th of September, 2019

Presence Hours

From 10:00 - 12:00 in front of HG G 53.2 .

Contents

The course will address the mathematical analysis of numerical solution methods for linear and nonlinear elliptic and parabolic partial differential equations. Functional analytic and algebraic (De Rham complex) tools will be provided. Primal, mixed and nonstandard (discontinuous Galerkin, Virtual, Trefftz) discretizations will be analyzed.

Particular attention will be placed on developing mathematical foundations (Regularity, Approximation theory) for a-priori convergence rate analysis. A-posteriori error analysis and mathematical proofs of adaptivity and optimality will be covered.

Implementations for model problems in MATLAB and python will illustrate the theory.

A selection of the following topics will be covered:

For more details, please check the ETH Course Catalogue

Exercises

The new exercises will be posted here on Thursday. We expect you to look at the problems over the weekend and to prepare questions for the exercise class on Thursday.

Submission of Matlab Codes:

Please hand in your solutions exercise class or in the marked box in front of HG G 53.2 before the next exercise session (if possible, please also provide a printout of your code)

Your solutions will be corrected and returned in the following exercise class or, if not collected, returned to the box in HG G 53.2.

Literature

Main literature Additional literature

Note: "online PDF" applies to users in the ETH domain (student computers / ETH WiFi / VPN)

Matlab Resources

Matlab links

ETH students can download Matlab with a free network license from the IT-Shop .

Matlab tutorials