280418 VU Introduction to Numerical Methods (2023W)
Continuous assessment of course work
Labels
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).
- Registration is open from Mo 04.09.2023 00:00 to Tu 26.09.2023 23:59
- Registration is open from Th 28.09.2023 00:00 to We 04.10.2023 23:59
- Deregistration possible until Tu 31.10.2023 23:59
Details
max. 60 participants
Language: German
Lecturers
- Alice Zocchi
- Iris Breda
- Ryan Leaman
- Lukas Winkler
- Mathias Lechthaler (Student Tutor)
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
- 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: Mo 30.10.2023 12:08