Today was the (unfortunately Sunday) start to the first full meeting of the Milky Way Mapper team, where MWM is a sub-part of the proposed project SDSS-V, of which I will be a part. It was very exciting! The challenge is to map a large fraction of the Milky Way in red-giant stars (particularly cool, luminous giants), but also get a full census of binary stars in different states of evolution, and follow up exoplanets and other scientific goals. Rix was in town, and pointed out that the survey needs a description that can be stated in two sentences. Right now it is a mix of projects, and doesn't have a description shorter than two dense slides! But it's really exciting and will support an enormous range of science.
There were many highlights of the meeting for me, most of them about technical issues like selection function, adaptive survey design, and making sensitive statistical tests of exoplanet systems. There was also a lot of good talk about how to do non-trivial inferences about binary-star populations with very few radial-velocity measurements per star. That is where Price-Whelan and I shine! Another subject that I was excited about is how one can design a survey that is simultaneously simple to operate but also adaptive as it goes: Can we algorithmically modify what we observe and when based on past results, increase efficiency (on, say, binary stars or exoplanets), but nonetheless produce a survey that is possible to model and understand for population statistics? Another subject was validation of stellar parameter estimates: How to know that we are getting good answers? As my loyal reader can anticipate, I was arguing that such tests ought to be made in the space of the data. Can they be?