Computational Astrophysics (Studierendentage SS 2018)
The goal of this crash course in computational astrophysics is to learn about several numerical methods to compute and/or model physical systems and solve a variety of problems. We apply these methods to problems from the field of astrophysics, because that is a particular fruitful area with many exciting examples. But many of the methods of this course will also be applicable to other areas of physics and science in general.
A tentative list of topics:
- Modeling orbits of planets in a multi-planetary system using Runge-Kutta integration. Applied to: Exoplanetary systems such as TRAPPIST-1.
- Fitting a model to observed data using Markov Chain Monte Carlo modeling. Applied to: Exoplanetary observational data.
- Computing a spectrum of an accretion disk. Application: Either a black hole or a protoplanetary disk (your choice).
- 1-D spherical gas dynamics model (numerical hydrodynamics) of a collapsing molecular cloud. Applied to: The formation of a star.
- Basic knowledge of Python programming, including handling numpy arrays and plotting with matplotlib
- Bring your own laptop with Python 2.7 or Python 3 installed, including the following libraries installed:
- Chapter 1: N-body model for exoplanetary systems
- Chapter 2: Automatic fitting of exoplanetary RV data
- 51 Pegasi radial velocity data
- Chapter 3: Numerical hydrodynamics of astrophysical gas clouds
Anmeldung erfolgt auf dem Übungsgruppensystem:
StudierendenTage SS 2018 in der Gruppe E.
Monday April 9 to Friday April 13 (5 days) from 9:15 to 12:00
Location: INF 227, SR 2.402
Verantwortlich: Cornelis Petrus Dullemond, letzte Änderung am 12.04.2018 01:34 CEST