NRFG, day 2

It turns out we are still Not Ready for Gaia. Binney (Oxford) opened the day with a strong argument that we should be thinking in terms of action–angle variables, and also a spirited explanation of his torus methods that do their best to approximate any potential with an explicitly integrable potential built from a quasi-optimal foliation of tori. His argument was good. That said, I am very against doing science by transforming the data to action–angle variables and then asking questions there. The transformation (often called sloppily a "projection") is highly non-linear and wrecks intuition about uncertainty. Besides, it depends on having a good potential model, which (I thought) was the whole point! Now Binney is not making this mistake: He wants us to do inference in the space of the observations, but there are certainly projects that transform to action–angle variables and say "look at the structure!" but don't note that the structure might be totally gone if either errors get finite or else the potential model is wrong (and both problems are unavoidable, always).

After Binney, Bovy spoke about his work with Rix modeling mono-abundance populations and getting the mass density in the Milky Way disk as a function of radius (near the Solar Circle). It is a monster project, with beautiful results. It brought to fruition quite a few things, some of which I was involved in, years past.


  1. Hi David. It sounds like you're referring to my work in the first paragraph there re transforming into actions and angles. I completely agree that it's better to take your model to the data rather than vice versa, but it can be a useful first exercise to go the other way if you don't know what to expect from the data, i.e. if you don't really have a good model. It's just so much easier to visualize to start to get a handle on the information.

    I'd add that in the paper (http://adsabs.harvard.edu/abs/2008MNRAS.390..429M) we did show that this works pretty well even if you calculate in the wrong potential. And Gomez et al (who worked on this idea using only the frequencies, and long after I got bored with it http://adsabs.harvard.edu/abs/2010MNRAS.408..935G) showed that closely related ideas could be used where there are gaia-esque uncertainties.

  2. don't disagree on anything; I think we all agree that data analysis (in the end) has to generate the data; how it does that depends on the uncertainties. Also, agree that actions are very valuable for building intuitions!