ASP3162 · Computational astrophysics and the extreme universe

Overview

In this unit you will learn the basic principles of astrophysical fluid dynamics and how it can be used to model the most extreme events in the universe. The unit covers the basic equations of compressible hydrodynamics, including the behaviour of linear waves, the transition to shocks and the behaviour of fluids at high Mach number. You will apply this to understand the physical processes that power accreting sources including white dwarfs, neutron stars and black holes, and the physics behind the explosion of stars as supernovae. You will gain practical experience in computational fluid dynamics including basic programming skills and an understanding of how large scale astrophysical simulations are performed.

Areas of study: Astrophysics Physics

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Demonstrate a basic understanding of astrophysical fluid dynamics, involving the physics of fluids at high Mach number, including sound waves and shocks.
2. Demonstrate practical skills in scientific computing, computational modelling, data analysis and visualisation.
3. Perform computer simulations of astrophysical flows using advanced astrophysical simulation codes, and demonstrate an understanding of the physics and mathematics behind modern large-scale astrophysical simulations.
4. Obtain understanding of high-energy astrophysics phenomena such as supernovae and gamma-ray bursts, compact objects, and matter under extreme astrophysical conditions such in the interiors of stars. This includes nuclear reactions and numerical modelling of simple nuclear reaction networks.

Workload

The workload to achieve the learning outcomes for this unit is 144 hours spread across the semester (roughly 12 hours per week) - approximately an even mixture of attendance at scheduled activities and self-scheduled study time. Learning activities comprise a mixture of instructor directed, peer directed and self-directed learning, which includes face-to-face and online engagement.

Student experience, not official rules. Nothing here changes what the Handbook says.