Great conversations today with Brewer about sampling and inference, Knut Jahnke and Stefanie Wachter (MPIA) and Doug Finkbeiner (CfA) about Euclid calibration, and Jennifer Hill (NYU) about data science. But that's not all:
In the morning, Coryn Bailer-Jones (MPIA) gave a status update on the Gaia mission, which was launched in December. It is performing to spec in almost all respects. Bailer-Jones gave us straight talk on three issues they now face: The scattered light (from sources not in the field of view) is much higher than expected, reducing the magnitude limits for all accuracies and capabilities. There is something (probably water) affecting the total photometric throughput. It looks like this can be mitigated with occasional thermal cycling of the optics. The "fundamental angle" between the two telescopes seems to be varying with time with a larger amplitude than expected. This can be modeled, so long as it is understood properly. I think I speak for the entire astronomical community when I say that we can't wait for early data releases and wish the Gaia Collaboration the best of luck in addressing these challenges.
In the afternoon, Dun Wang, Foreman-Mackey, Schölkopf, and I worked through Wang's results on Kepler data-driven calibration. I am pretty excited about this project: Wang has shown that when we "train" the model on data not near (in time) to an injected transit, the data recalibrated with the model produces unbiased (on average) inferences about the transit. We assigned Wang next steps.