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Simulating the Universe with a zBox
An anonymous reader writes "Scientists at the University of Zurich predict that our galaxy is filled with a quadrillion clouds of dark matter with the mass of the Earth and size of the
solar system. The results in this weeks journal Nature, also covered in Astronomy magazine, were made using a six month calculation on hundreds of processors of a self-built supercomputer, the zBox. This novel machine is a high density cube of processors cooled by a central airflow system. I like the initial back of an envelope design. Apparently, one of these ghostly dark matter haloes passes through the solar system every few thousand years leaving a trail of high energy gamma ray photons."
A photo of the zBox: http://www.mirrordot.org/stories/aff65ec05d123a38a db103f5a1f9d36f/index.html
You can read the entire paper in PDF or PS at astro-ph, a web site which collects preprints in the physical sciences. See
http://xxx.lanl.gov/abs/astro-ph/0501589
I read the paper quickly. The authors have to come up with a model which has virtually no observable consequences (otherwise, we would have seen this source of matter by now), but which can also be tested experimentally in the not-too-distant-future (or else it wouldn't be science). They predict that some of the cosmic-ray shower telescopes may be able to detect the little cloudlets of dark matter. We'll see.
Michael Richmond "This is the heart that broke my finger."
mwrsps@rit.edu http://stupendous.rit.edu
http://krone.physik.unizh.ch/~stadel/zBox/story.ht ml
The 3D temperature monitor is really cool.
Maybe they should have use the zbox to host their site =)
i k.unizh.ch/~stadel/zBox/
http://rufus.hackish.org/~rufus/mirror/krone.phys
The problem in question is the number of distinguishable bodies. With weather you would have to go down to the single molecule in the air, to get a quite good prediction. In fact current weather models use cubes of air where the conditions are considered constant (same temperature, same pressure, same direction of air flow in the same cube) and take them as distinguishable bodies. Those models are a compromise between the sheer number of necessary elements, the number crunching limits of current calculation hardware and the difference between the used model and the reality.
With stellar bodies it's much more easy. The number of stellar bodies you need for a prediction is much smaller, the bodies themself can be considered almost constant for the whole calculation etc.pp. With the number crunching capacity of today's weather prediction centers you can simulate whole galaxies (if you consider stars constant, which they mainly are for about 10mio to 10bio years, depending on their mass). With the differences between your model and the measured reality you can spot elements you didn't simulate yet and add them to your model. The swiss team now was simulating clouds of about the mass of the earth and the size of the solar system and found that those added to the stellar simulation made a quite good fit to the measured data.
No. There's no net charge. If one developed between the sun and the solar wind, the solar wind would fall straight back in.
A good primer on dark energy can be found here
My guesses are: 1) Cost. A commercial 1U dual processor pizza box is actually very expensive for the computing power, compared to the do-it-yourself method. Of course, you're mostly paying for support, overhead, the brand name, and a sturdy, cool-looking case. 2) Cost. Commerical racks can be pretty pricey, too. 3) I/O speed. The zBox is wired up for good inter-CPU throughput, whereas you lose significant speed with the typical ethernet patchboard scheme you find in a commerical rackspace. Of these (3) is probably the most important.
If you mod me down, I shall become more powerful than you can possibly imagine.
Everyone, take a look at those pictures. No, not of the results, but of the computer itself. The page goes over how they built the thing, with pictures of assembling the nodes, the frame, and the completed box. That's a sight to see, all the internal guts forming that piece of computing power.
If you were trying to predict rain in the next six months it would be a lot easier than predicting it with any real useful accuracy.
It's the difference between saying it does rain, and when it will. On this scale they are just explaining a phenomena that can happen every so often, in a stellar sense. I'm guessing this eases the difficulty of computation from what would be necessary to predict the number of years before the next occurrence.
Of blankness, I know nothing.
If I remember correctly, chemical reactions happen at the atomic level, not subatomic.o l/chemtool.html
Here is a GPL program, there are plenty of others (commercial and FOSS):
http://ruby.chemie.uni-freiburg.de/~martin/chemto
"The problem in question is the number of distinguishable bodies. With weather you would have to go down to the single molecule in the air, to get a quite good prediction"
This is utter nonsense.
Weather models are fluid models, not particle models like the N-body simulation described here. They are quite different, and require different computational approaches. Both are numerically intensive, however.
Well, you'd have to have a capture/drawing tool like Chemtool, and then something that could approximate polarity, electrical charge distribution, and bond length/strength. (Those involve things like electron orbitals, hence the subatomic.) Next, you'd have to have something that handles movement of fluids and gases with respect to the temperature, pressure, etc (gas laws and the partial diff. eqns. whose exact solution is one of the Clay instutite Millenium problems). Then, you'd have to have something that will predict what happens, probabilistically, when two or more molecules interact. These interactions would have to modeled in terms of molecular collisions, so that things like titration, stirring, etc, would be accurate.
Finally, you'd have something which would prepare an "answer" to each problem by waiting for a reasonable amount of precipitate to settle, or measuring pH, or simulating a gas chromatograph of the contents of the beaker.
Other helpful things would be crystallization and such. I would think that if you could simulate the physical laws and properties at a sufficiently low level, most things would arise automatically, but IANAC.
--TheOrangeSquid Is it any wonder things seem so awry? We swim in a sea of confusion and don't have to think to survive
If you pervert Moore's law into a statement of speed, you end up coming out ahead for any computation that
1) is CPU-bound rather than interconnect-bound or disk-bound or memory-bound
2) will take 3 years+ with current technology / budget, and
3) produces no useful intermediate results
At 3 years, you come out even buying current tech and running it for 3 years versus waiting 18 months and buying spending the same money on tech that can do the job in 18 months.
There are few such computations. Note that the universe simulation being discussed here does not qualify, even if it were run for the requisite 3 years. Clearly interconnect latency/bandwidth was a significant concern, necessitating special high-speed components and a torus topography.
High-speed Road Trip (18.000KPH)