all the plots, radial-velocity survey design

In response to requests from my team, I made a 256-page, 2560-panel plot of every single one of the 256 k-means clusters we found in abundance space, a few of which we published in our paper yesterday. I don't see much else in there that is easy to interpret, but it looks to me like the higher metallicity groups we see are actually multiple groups mashed together. So I resolved to run at higher values of K on the weekend.

In the afternoon, I had a call with Dan Foreman-Mackey about exoplanet populations. (Thinking of the future) he observed that the goal of finding reliable targets for some kind of Terrestrial Planet Finder mission and the goal of understanding how typical planetary systems form and evolve might be very much at odds, especially when it comes to radial-velocity surveys. Indeed, there haven't been many populations analyses of radial-velocity surveys to date, in part because most of them are not designed with long-term statistical goals in mind. We discussed a bit about what we might do to encourage a future in which both goals can be met, handily. I pointed out something that Charlie Lawrence (JPL) said to me at #AAS227 a couple weeks ago: If some kind of TPF is going to cost billions of dollars, it is worth spending a few hundred million on the ground in preparation. So resources might be abundant.

1 comment:

  1. Howdy, Hogg. You know about X-means, right: https://www.cs.cmu.edu/~dpelleg/download/xmeans.pdf . I'm sure you can think of generalisations (K-means likelihood used in X-means models the distribution as a N(0,sigma^2*I) multivariate Gaussian in each cluster). We use something similar (but generalised the distribution to a KDE estimate based on the cluster members) when turning posterior samples into skymaps in LIGO: https://github.com/farr/skyarea .