Universität Wien

280418 VU Introduction to Numerical Methods (2023W)

6.00 ECTS (4.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie-Geophysik und Astronomie
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 60 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

The course will be entirely in English

  • Tuesday 03.10. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 03.10. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 04.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 10.10. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 10.10. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 11.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 17.10. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 17.10. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 18.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 24.10. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 24.10. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 25.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 31.10. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 31.10. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 07.11. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 07.11. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 08.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 14.11. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 14.11. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 15.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 21.11. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 21.11. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 22.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 28.11. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 28.11. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 29.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 05.12. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 05.12. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 06.12. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 12.12. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 12.12. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 13.12. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 09.01. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 09.01. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 10.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 16.01. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 16.01. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 17.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 23.01. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 23.01. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 24.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 30.01. 13:15 - 14:45 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 30.01. 15:00 - 16:30 Seminarraum 1 Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 31.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17

Information

Aims, contents and method of the course

The aim of the course is to equip the students with important numerical methods relevant to astrophysics: solution of linear and non-linear problems, numerical differentiation and integration, numerical solution of ordinary differential equations, approximation of functions, interpolation and extrapolation of functions, discrete Fourier transform, sampling of distributions, optimization, data visualization, introductory machine learning techniques, maximum likelihood and MCMC fitting techniques.

This will be achieved through lectures focused on the theory and exercises focused on the practical implementation of the numerical methods. The programming language that will be used to present algorithms is python; students will receive an introductory tutorial to provide them with the necessary background to successfully carry out the computational tasks.

Assessment and permitted materials

Total grade: lectures 50% + exercises 50%

Lectures: Two mini-tests, each accounting for 25% of the final grade from the lectures.

Exercises: weekly homework based on the lectures topics. The grade will depend on the evaluation of the submitted exercises and on the evaluation of the submitted report for a mini-project, each accounting for 25% of the final grade.

Minimum requirements and assessment criteria

The submission of at least 75% of the exercise sheets and of the mini-project is required. Participation in both exams is also mandatory.

Examination topics

Based on the content of the lectures and on exercises similar to those proposed in the weekly exercise sheets. Indeed, homework, solved as part of the exercises, will aid and test students' understanding of the material covered in the lectures by applying numerical methods to real datasets.

Reading list

The lecture notes are provided as PDF files.

Selected chapters in the following literature are recommended:
- Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data (Ivezić, Željko et al.) [only physical copies]
- Press, Teukolsky, Vetterling, Flannery: Numerical Recipes
- Strang, G.: Introduction to Applied Mathematics

Association in the course directory

NUM; PM-NumMeth;

Last modified: We 20.08.2025 00:22