Marshall and I spent a phone call talking about how we can model strong gravitational lenses in the PanSTARRS data, given that the data (in the short term, anyway) will be in the form of catalogs. As both my loyal readers know, I am strongly against catalogs. What Marshall and I had independently realized—me for catalog source matching and Marshall for lens modeling—is that the best way to deal with a catalog is to treat it as a lossy compression of the data. That is, use the catalog to synthesize an approximation to the imaging from which it was generated, use the error analysis to infer a reasonable noise model, and then fit better or new models to those synthesized images. I love this idea, and it is very deep; indeed it may solve the combinatoric complexity that makes catalog matching impossible, as well as the lensing problems that Marshall and I are working on.
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