Where science and tech meet creativity.

I know I’ve been silent for a long time, but this week I hope to make up for my wayward ways and blog my brain out.

This week is the 213th meeting of the American Astronomical Society in Long Beach, California. I’m here along with many of my friends and colleagues from across Astronomy Cast, 365 Days of Astronomy, IYA, and Galaxy Zoo. Since we’re all new media, Fraser and I were able to twist arms to get help live casting the conference to the world (which happens to include you). Joining me in person are: Fraser Cain (our second time meeting in person!), Ian O’Niell, Michael Koppelmann, Chris Lintott, Georgia Bracey, Scott Miller, and Jordan Raddick. Nancy Atkinson is also helping us from afar. Together, we’re going to get you as much content as we can. (Want to meet us? Join us at Rock Bottom Brewery 6-9pm on Wednesday Jan 7)

I’m currently in a pre-meeting symposium for recipients of the National Science Foundation’s Astronomy and Astrophysics Postdoctoral Fellows 2009 Symposium. The two-day symposium is a mix of presentations by recipients, panels discussions by folks the NSF thinks have something to share (I’ll be on a panel on non-traditional public outreach), and general resources on how to get their next job, their next grant, and to teach their next class.

(I have to admit I’m learning stuff)

And one of the things that is particularly cool is they are being taught through example that it’s okay that sometimes research that just doesn’t give you the results you want or expect.

Case in point: Rachel de Naray presented her research comparing actual observations of Low Surface Brightness Galaxies to theoretical models of galaxies with a specific type of dark matter halo called a Navarro -Frenk -White (NFW) potential. These models have a specific distribution of dark matter, make a specific set of assumptions, and you can read about it here on wiki. The question is: Does this model mimic reality.

de Naray is working to answer that question. One of the best ways to approach this problem is to find a system where dark matter dominates so that the errors introduced by trying to sort luminous matter (of which you will never be abe to detect all of it) from dark matter is only a minor player. (Think of it as trying to weigh water that has on few leaves swirling in it, versus trying to weigh water that is black from leaves floating in it). Nature offers a convenient solution: Low Surface Brightness galaxies do have some stars and gas an dust, but in general are under dominated by dark matter. The stars /  gas / dust act like leaves swirling in the water, and allow us to measure how things orbit in the systems’ gravitational fields, but they are such a small part of the total mass we know how to deal with them.

One of the nice things about galaxies is stars / gas / dust (the stuff we can see) orbits at velocities that are directly related to the size of the orbit and the amount of stuff (luminous and dark) inside the orbiting object’s orbit. This means that the orbital motions of the stuff we can see tell us about the distribution of the stuff we can’t see.

So… De Naray made observations. She made models using the NFW potetial. She compared them hoping for a match, and… They didn’t match. But she initially made the simulation easy by assuming perfect data acquisition, circular orbits, axial symmetry (the distribution of the dark matter is a sphere), and she ignored the finer details of how dust / gas collisions effect things. The fact that the match wasn’t perfect was sad, but there was lots of room to try and make things better. As a good scientist, she systematically removed each of these simplifications from her simulations, seeking help from a collaborator with great galaxy models, and … Still no match. In fact, she purposely “built” an artificial galaxy with her pre-assumed distributions of luminous stuff and a NFW potential and double checked that she could recover it’s distribution, with the software, and when you artificially created the galaxy her results were dead on – the software works – but it appears simulation just doesn’t match reality.

Now here is where I’m going to through out some editorial comments. First, I loved listening to her systematically go through and say, I made these assumptions and I made these simplifications, and then I removed each of the simplifications to check my assumptions, and well, something is wrong – this model doesn’t match well. She did good work and communicated well. It was a pleasure. That said, NFW models are one of the most commonly used dark matter distributions, and I honestly wonder how long it will be before enough people say, “Hey – doesn’t fit reality so well” before people start chasing new dark matter distributions. It is going to be interesting to watch over the coming years.