This week was mostly installing packages.
- The simulations I’ll be working on in the nearest future use AREPO, a hydrodynamic simulation code.
- A good introduction, and the primary tool in later work, is the Gadget code.
- The output is a series of snapshots, which need to be compiled into a video for meaningful interpretation. This requires GadgetViewer, a visualization software.
- Running this, in turn, asks for GTK+ 2.0, a tool for creating graphical user interphases.
- Given the multiple languages used across these packages, I also had to install gettext, an open-source utility that structures other programs such that every function therein knows where to look for certain necessary files (mostly libraries and commands).
Yup, that’s a lot of packages.
And of course files are located in weird places, some are remotely accessed.. So making sure everything installs correctly is a much larger task than I would have thought. Not really complaining though – I can see myself getting better reading and editing source code by the hour.
Meanwhile, I’d also obviously like to understand the physics behind these simulations and how they compare with alternatives. This is quite alien to the fluid mechanics noob that I am.
- AREPO uses the numerical Godunov scheme to model fluid behaviour on a moving mesh, in contrast to the analytical approach taking in both Eulerian and Smoothed Particle Hydrodynamics (SPH). The two of these in turn differ in how they look at the system.
- The Eulerian approach considers conservation of certain properties, namely momentum and energy, and continuity of mass within a region of space. The Godunov scheme in fact builds on Eulerian conservation laws. Pre-AREPO, however, simulations would consider these dynamics on a Cartesian plane, resulting in a loss of Galilean invariance (the requirement that laws of motion be the same in all inertial frames). How exactly? That, and how AREPO’s moving mesh handles the issue, are questions for a future post when I know better.
- SPH, as the name indicates, follows the dynamics of each constituent particle (or fluid elements, rather), in turn dependent on the properties of others surrounding it. This smoothing, however, mutes the effect of instabilities within the smoothing length. Turbulence can have significant effects on thermal and magnetic pressure (depending on whether the fluid studied is a gas or a magnetic field), as noted in Lage’s recent paper modeling a merger in the Bullet cluster, where he had to introduce a physically unknown fudge factor to maintain gas clouds in equilibrium.
I’ll be digging some brains at the CfA tomorrow, attending lab meeting and mapping out a project sequence with my immediate supervisor. All good things.
