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Computational plasma physics 2020

This lecture provides an introduction to scientific computing with examples from plasma physics. A particular emphasis will be placed on the discretization of partial differential equations. Numerical methods for the Poisson equation, conservation laws as well as kinetic equations will be introduced. In the exercise classes, an introduction to the Python computer language and basic software development techniques will be offered. This will be used to code the discretisation methods introduced in the lecture. After successful completion of the module, students understand different methods for the discretization of partial differential equations and their implementation by means of the Python programming language.

Topics are:

Until further notice, lectures will be held online in this BigBlueButton classroom. You will need Firefox or Chrome browser for this to work. Programming exercises will be done as homework and discussed each Monday right after the lecture.

Prerequisites are basic analysis and linear algebra. The lecture is accessible to students with a bachelor in mathematics, in physics or a related field.


Literature (with links to TUM library)


Lecture notes

Exercise sheets


As a bonus mechanism in order to improve your grade at the final examination, an assessment of the programming exercises in Python will be offered at the end of the course. In order to be able to participate in the programming assessment, active participation during the exercises is required since the assessment will be based on the code written in the exercise classes. Your result in the programming assessment will be one third of your final grade but only if it improves the grade.

-- StefanPossanner - 06 Apr 2020