Datastar is the 2500 CPU supercomputer I do most of my work on. Until today I had never seen it in person. Behind me are just a few of the racks that make up the computer. The room was loud and alternatively very hot and very cold. There are a few more pictures from the SDSC supercomputer room in my Cell Pics gallery.
Below is a little animation that I made yesterday that shows what I have been doing lately. The green dots correspond to the positions of dark matter particles, while the little yellow squares are the locations of dark matter haloes that I’m interested in. The white lines are the edges of the simulation volume, and you can see the axes triad in the bottom-left corner. To give you an idea of the scale of what’s depicted here, each edge of the cube is 50 Mpc, or 163 million light years. Our entire galaxy is only about 20 kpc or 65,000 light years across.
In the first part of the movie, the cube is rotated about its center. Next, while looking along the z-axis, the volume of the cube plotted is reduced until only 1/10th of the cube is shown. Then, this 1/10th thickness is scanned through the entire cube, and then the volume plotted is replenished back to full.
The things to notice are how the dark matter form areas of high density, which are connected by filaments. Between these are areas of relatively few particles, which are called voids. This is how our universe really looks, with huge collections of galaxies clustered together, separated by huge expanses of nearly empty space. I should point out that there are many more galaxy haloes in this box besides the yellow boxes.
What I was looking for was one of those yellow boxes which is fairly isolated from areas of high density dark matter. I picked one, and now I am doing this same simulation again, but with higher resolution boxes centered on the area of interest. The simulations I’m doing right now are fairly cheap (in computer time currency). I want to be sure that when I run big, time-intensive simulations in the future that I’ve picked a good area to focus my attention on.
I did this visualization with Visit, a stereo, 4D visualization tool out of the Livermore National Lab. The ‘stereo’ means that it can create two images of the same data that are slightly offset, which create a 3D effect if viewed correctly. The fourth dimension is for time, as it can handle time-ordered data sets. I then used Visit’s Python scripting features to output 800 individual PNGs, which I then stitched together (exactly like my time lapse movies) to make this movie.
Above is a part of what I’ve been working on lately. It’s a small part of the galaxy family tree that I’ve derived from a large simulation. In the simulation there are several ingredients that are thrown in the ‘box.’ Relevant to this are the dark matter particles, which coalesce into consituents of galaxies. The dark matter particles have unique id numbers. Using a some code I didn’t write, I process the simulation data and make a list of galaxies along with the particles in each galaxy. Then, using some code I did write, I track particles and galaxies over a number of time steps, which builds a relational mapping. Then, I use Graphviz to make a nice tree, as you see above.
Inside each box are either three or four data values. The top grid shows what percentage of the particles in that group came from no group, the middle grid shows both the number of dark matter particles that are in the group and the position of the group, while the bottom grid shows the percentage of the particles that go to no group. The simulation takes place inside of a 3D box with length 1 on a side and periodic boundaries (which means the distance between 0.9 and 0.1 is 0.2, not 0.8). The colors of the box correspond to its ranking in size, red is the largest, green the smallest. The numbers next to the arrows are what percentage of the parent group goes to the child group.
The goal of this is to get an idea of how the galaxies form over the course of the simulation. Of course the simulation tries to mirror reality, so this family tree may be worth something.
For the better part of half a year now I’ve been working slowly on a project with Mike Norman, my advisor. I’m basically implementing a test of the efficiency & accuracy of the cosmological simulation code his group uses. I do this by sticking a ring of gas into the simulator and watching the gas spread out. I compare the computer simulation to how it should go if all things were perfect (which the simulation is not). The two plots below are a culmination of my accelerating efforts.
Above is a 3D plot of the gas density. The two horizontal coordinates are the x-y position, while the vertical gives the density at that point. I’m doing my simulation in two dimensions right now, eventually I’ll go to three.
The white line above (hidden by the red line) is a sideways slice of the density, starting at the center going out. The red line is a best curve fit of the white line. The curve fit is very good because the white line was generated by the same function I’m using for the best fit, but the picture shows my fitting technique works, and that’s what matters.
I hope to make further, faster progress! I’ll post things here as I go along.
Date: 11/03/09
It seems your using an unsafe, out-of-date browser. Click here to upgrade to Firefox for free.
Canonical URL by SEO No Duplicate WordPress Plugin
Stephen Skory is Digg proof thanks to caching by WP Super Cache