In Stars Meeting today, visitors Greg Green (KIPAC) and Richard Teague (Michigan) both talked about mapping dust. Teague is working at protoplanetary-disk scale (using velocity maps to find planets), while Green is working at Milky Way scale (making 3-d extinction maps). Teague is working with Foreman-Mackey (Flatiron) to get better velocity maps out of ALMA data and they are getting good success with one of my favorite tricks: Fit the peak with a quadratic. We have shown, in astrometric contexts, that this saturates information-theoretic bounds. They have gorgeous maps!
Green is trying to apply more useful spatial priors to the dust maps he has made of the Milky Way, which are (currently) independently sampled in pixels. He is resampling the pixels, using neighbor information to regularize or as a prior. His method is slow, but a lot faster than using a fully general Gaussian Process prior. And it appears to be a good approximation thereto. Certainly the maps look better!
I presented my project to figure out orbits from chemistry. There was good discussion. Spergel (Flatiron) opined that I would do no better than Jeans modeling if I did the Jeans modeling conditioned on chemistry. I am sure that's wrong! But I have to demonstrate it with a good information-theoretic argument.
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