centroiding and searching

I spoke with Vakili about centroiding stars. We are trying to finally complete a project started by Bovy ages ago to compare the best-possible centroiding of stars with a three-by-three pixel hack related to what is done in the SDSS pipelines. Vakili hit this issue because if you don't have good centroids, you can't get a good point-spread function model. Well, actually I shouldn't say "can't", because you can but then you need to make the centroids a part of the model that you learn along with the point-spread function. That may still happen, but along the way we are going to write up an analysis of the hack and also the Right Thing To Do.

Foreman-Mackey, Fadely, Hattori, and I discussed Hattori's search for exoplanets in the Kepler data. The idea is to build up a simple system based on simple components and then swap in more sophisticated components as we need them. We discussed a bit the question of "search scalar"—that is, what we compute as our objective function in the search. There is a likelihood function involved, but, as we often say in #CampHogg: Probabilistic inference is good at giving you probabilities; it doesn't tell you what to do. Search is a decision problem.