Universität Wien

260018 VO Scientific Computing (2010S)

3.00 ECTS (2.00 SWS), SPL 26 - Physik

Details

Language: German

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 04.03. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 11.03. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 18.03. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 25.03. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 15.04. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 22.04. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 29.04. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 06.05. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 20.05. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 27.05. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 10.06. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 17.06. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien
  • Thursday 24.06. 11:00 - 12:30 Ludwig-Boltzmann-Hörsaal, Boltzmanngasse 5, EG, 1090 Wien

Information

Aims, contents and method of the course

This course deals with basic methods of scientific computing, leaning towards applications in theoretical physics.

Scientific Computing is an interdisciplinary field of study, situated bewteen numerical analysis, computer science and natural science. Nowadays, numerical simulations are used to conduct expensive or practically impossible experiments in
complex mathematical models of a given physical system. The insights obtained by the simulations may, in turn, suggest new directions for theory.

In the course of the lecture, the following topics will be discussed using simple numerical algorithms. In the excercises
these algorithms will be applied to examples, implemented and visualized:
Visualization
Interpolation
Numerical Differentiation
Numerical Integration
Solution of Nonlinear Equations
Fitting
Ordinary Differential Equations
Partial Differential Equations
Linear Systems of Equations
Eigenvalueproblems
Monte-Carlo Simulation

Assessment and permitted materials

Written examination

Minimum requirements and assessment criteria

The students acquire methods for the numerical analysis and the solution of problems in physics. Understanding of the course.

Examination topics

Corresponding to the type of the course.

Reading list

Wird in der Lehrveranstaltung bekanntgegeben.

Association in the course directory

PD250

Last modified: Mo 07.09.2020 15:40