Department of Mathematics

Numerical Methods for Partial Differential Equations

Please note that this page is old.
Check in the VVZ for a current information.

Ferienpräsenz: we offer consultation hours during the semester break where you can ask question about the lecture material. For the dates see  this document (in German). It also lists the dates for the Prüfungseinsicht.

Lecturer: Ralf Hiptmair

Assistants: Eivind Fonn, Laura Scarabosio, Cecilia Pagliantini, Fabian Müller

Lecture hours:

Exercise classes:

Consultation hours:

They will be established the first exercise class.

Please choose an exercise class here. (Will be online in the first week of the semester.)


There will be 12 weekly assignments handed out every Monday (first time on February 25th). They should be handed in the following week before midnight on Monday in the labeled box at HG G 53.X.

Exercises are marked either as core or non-core problems. Core problems (about 2 per sheet) are supposed to be essential for following the course.

Correction of homework problems will be done on request (to be written on the problem sheet you hand in) for at most two problems per sheet.

Testat requirements: NONE.

For submitting your MATLAB code, please use the online submission interface and choose the course n.7.

Assignments, lecture notes and other handouts


3 hour computer-based examination, with both programming and theoretical exercises. More info to come as the date draws nearer.

There will be two quick assessments during the semester:

The points awarded in the quick assessments will be taken into account for the grade of the final examination with a weight of roughly 20%.

Aims of the course

Introduce students of Applied Mathematics, Computational Science and Engineering and Computer Science to the most widely used numerical solution methods for ordinary and partial differential equations, their mathematical properties, and their computer implementation.

Students should be able to:

Programming Language: All implementations will be done in MATLAB.

Content of the course

See a more comprehensive list on the VVZ.

Matlab links

Students of ETH can download Matlab via Stud-IDES for free (product name 'Matlab free').


This list should be interpreted as supplementary reading beyond the lecture notes, and is neither important nor required for following the course.

Further literature

These are beyond the scope of this course, and are listed here for the particularly interested.


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© 2016 Mathematics Department | Imprint | Disclaimer | 19 March 2013