Computational plasma physics
Module MA4304
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of SS 2014
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
| available module versions | |
|---|---|
| WS 2018/9 | SS 2014 |
Basic Information
MA4304 is a semester module in English language at Master’s level which is offered in summer semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
| Total workload | Contact hours | Credits (ECTS) |
|---|---|---|
| 150 h | 45 h | 5 CP |
Content, Learning Outcome and Preconditions
Content
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.
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.
Learning Outcome
After successful completion of the module, students understand different methods for discretization of partial differential equations. They have a good knowledge of possibilities and limits of computer modelling and they can apply basic software development methods for efficient and reliable code development.
Preconditions
MA1101 Linear Algebra and Discrete Structures 1, MA1102 Linear Algebra and Discrete Structures 2, MA0901 Linear Algebra for Informatics, MA1001 Analysis 1, MA1002 Analysis 2, MA1304 Introduction to Numerical Linear Algebra
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
| Type | SWS | Title | Lecturer(s) | Dates | Links |
|---|---|---|---|---|---|
| VO | 2 | Computational Plasma Physics [MA4304] | Sonnendrücker, E. |
Mon, 10:15–11:45, MI 03.06.011 |
|
| UE | 1 | Computational Plasma Physics (Exercise Session) [MA4304] | Bell, D. Sonnendrücker, E. |
Mon, 12:00–12:45, MI 03.04.011 |
Learning and Teaching Methods
The module is offered as lectures with accompanying practice sessions. In the lectures, the contents will be presented in a talk with demonstrative examples, as well as through discussion with the students. The lectures should animate the students to carry out their own analysis of the themes presented and to independently study the relevant literature. Corresponding to each lecture, practice sessions will be offered, in which programming exercises, exercise sheets and solutions will be available. In this way, students can deepen their understanding of the methods and concepts taught in the lectures and independently check their progress.
Media
Blackboard, jupyter notebooks
Literature
R. J. Leveque: Finite Volume Methods for Hyperbolic Problems, Cambridge Texts in Applied Mathematics, 2002.
C.K. Birdsall and A.B. Langdon: Plasma Physics via Computer Simulation, Taylor & Francis, 2005
C.K. Birdsall and A.B. Langdon: Plasma Physics via Computer Simulation, Taylor & Francis, 2005
Module Exam
Description of exams and course work
Students take an oral exam of about 20 minutes. They show their ability to understand the basic methods for the numerical solution of partial differential equations treated in the course, like finite difference, finite volume, spectral and finite element methods. The context is given by the equations of plasma physics such as Vlasov-Maxwell and the corresponding fluid-dynamical models. Students should be able to describe the generic mathematical properties of the model equations, derive discretization methods and analyze their rate of convergence.
Exam Repetition
The exam may be repeated at the end of the semester.