There is far more to report here from today's than I easily can, so I will just blurt some highlights once again:
Lindegren (Lund University) gave a beautiful talk about fundamental issues in astrometry, especially with spinning satellites. Gaia—unlike Hipparcos will work in the limit in which the spin is more strongly constrained by the density of informative stellar transits than it could be by any reasonable dynamical model of the spinning satellite subject to torques. That is, there is only a very weak dynamical model and the data do the talking. This means that any measurement by the satellite that can be accommodated by an attitude change is not constraining on the global astrometric solution! For this reason, with each of the fast rotations (scans) of the satellite, the only constraining measurements made on the global astrometric solution are comparisons between stellar separations and the basic angle of the satellite, along the direction of the scan. It really is a one-dimensional machine, at least on large scales. The two-dimensional images off the focal plane will be useful transverse only on small scales. He followed these beautiful fundamental arguments with discussions of self-calibration of the satellite, which is really what all the talks have been about these two days, in some sense.
Bombrun (ARI, Heidelberg) and Holl (Lund) gave back-to-back talks about the optimization of the linearized system of equations and the error propagation. Optimization (after the Collaboration found conjugate-gradient method) is trivial, but exact error propagation—even for the linearized system—is impossible. That's because the sparse matrix of the linear system becomes very non-sparse when you square and invert it. Holl has some very nice analytic approximations to the inverted matrix, made by expanding around invertible parts, and by making simplifying assumptions. This is key for the first generation of error propagation. In my talk I will emphasize that if the Collaboration can expose something that looks like the likelihood function, error propagation is trivial and it becomes the burden of the user, not the Collaboration. However, there is no chance of this in the short run.
Eyer (Geneva) gave an electrifying talk about variable stars, making clear what should have been obvious: Gaia will be the finest catalog of variable stars ever made, and contain in almost every class of variability hundreds of times more stars than are currently known. This opens up the possibility for all kinds of novel discovery, and enormous improvements in our understanding of the variables we now know. His group is computing observability of various kinds of variables and the numbers are simply immense. He noted that Gaia might discover WD–WD eclipsing-binary gravitational wave sources.
At the end of the day Mahabal (Caltech) spoke of automated transient classification. They are doing beautiful things in the VO/semantic framework. Of course I am a critic of this framework, because I want meta-data to be probabilistic and computer-generated, not human-designed and combinatoric (as in
this is a Type IIP Supernova; much more useful to be given relative likelihoods of all non-zero possibilities). But there is no doubt that within this framework they are doing beautiful stuff.