At the end of the day, Malz came by the CDS space and we talked through first steps on a project to look at sky subtraction in spectroscopy. We had a great idea: If the sky residuals are caused by small line-shape changes, we can model the sky in each fiber with a linear combination of other sky fibers, including those same fibers shifted left and right by one pixel. This is like the auto-regression we do for variable stars—and they do on Wall St to model price changes in securities—but applied in the wavelength direction. It ought to permit the sky fitting to fit out convolution (or light deconvolution) as well as the brightness.
Group meeting included some very nice plots from Fadely showing that he can model the color-size distribution of sources in the SDSS data, potentially very strongly improving star–galaxy separation. We also talked about ABC (tm), or Bayesian inference when you can't write down a likelihood function, and also stellar centroiding.
At lunch, Goodman told the Data Science community about affine-invariant MCMC samplers. He did a good job advertising emcee and some new projects he is working on.