spots, variational inference, bad sci-fi

After the #GaiaDR2 week and all the knock-on consequences, I'm starting to feel a little strung out this week! But I pulled it together for Stars meeting at Flatiron. Brett Morris (UW) was in town, and he talked about the degeneracies between transit depths and star spot statistics and other observables. He is generalizing the star surface model to properly capture those uncertainties. That's important for downstream inferences.

David Blei (Columbia) graced us with his presence. He categorized inference problems into a nested classification, with Gibbs-like problems in the center and fully implicit (you can do simulations but nothing else) problems on the outside. We have problems across this spectrum. He talked about how variational methods capitalize on optimization advances to deliver posterior approximations; this has limitations, but it is far faster than MCMC in most high-dimensional situations. He talked about many other things as well, and we looked at points of contact for collaborations. We are interested in scaling up things we did in the million-source TGAS to the billion-source Gaia DR2.

Late in the day, Rabbi Dan Ain (Because Jewish) and I did an event with Brian Sheppard (Seton Hall) at Caveat NYC, using the (bad) 80s film Short Circuit as our jumping-off point. It was ill-attended, but seriously fun.

#GaiaDR2 zero-day workshop, day 1

Today was Gaia DR2. My day started at 05:00 for the press release, and ended at 18:00 with the champagne toast we lifted to the entire Gaia DPAC, who have actually changed the world. Amazing things happened during the day, way too much to report on in this forum. So I will just tell you what I was paying close attention to today.

Ana Bonaca (Harvard) and Adrian Price-Whelan (Princeton) looked to see if they could see the long, cold stellar stream GD-1. They found it, and it is in the data at immense signal-to-noise. It is still subtle though, reminding us that finding brand-new streams in the data will still be a challenging project. Their map of the stream confirms the gaps we thought we saw many years ago, and there might even be hints of kinematic distortions at the edges of those gaps. If any of that turns out to be real, we might be able to directly measure substructure in the stream.

Megan Bedell (Flatiron) did the match between Gaia and Kepler and made basic visualizations. These already revealed something interesting: Although there are very few planets around blue subdwarfs (and no, I have no idea what they are, but blue stars below the main sequence), the fraction of blue subdwarfs that host planets looks like it is way too high. What could this mean? Perhaps even more interesting: The planet orbital periods are too short for the planets to have survived the stellar evolution up the red-giant branch and back down again, so there is an astrophysical mystery there too.

In the Gaia DR2 press conference, the team attributed complexity in the white-dwarf color-magnitude diagram (and check it out, it is beautiful!) to different compositions (or maybe surface compositions) of the white dwarfs in the different stripes or modes in the diagram. Kareem El-Badry (Berkeley) did some digging in the white-dwarf world and finds that this is not a good explanation for the differences, or at least not a complete explanation. He thinks there must be some complexity to the mass distribution of white dwarfs, unless the cooling models have serious issues. And he also thinks that the diagram is not showing lots of white-dwarf–white-dwarf binaries, but also not showing zero of them!

There were some reporters at the event. I thought this story by Lee Billings (Scientific American) captured a lot of the spirit of the day!

chemical correlates of planet system architecture

At Stars group meeting, Jo Bovy (Toronto) demonstrated to us that the red-giant branch in Gaia DR1 TGAS is populated about how you would expect from a simple star-formation history and stellar evolution tracks. This was surprising to me: The red clump is extremely prominent. This project involved building an approximate selection function for TGAS, which he has done, and released open-source!

John Brewer (Yale) showed relationships he has found between planet-system architectures and stellar chemical abundances. He cleverly designed complete samples of different kinds of planetary systems to make comparisons on a reasonable basis. He doesn't have a causal explanation or causal inference of what he is finding. But there are some very strong covariances of chemical-abundance ratios with system architectures. This makes me more excited than ever to come up with some kind of general description or parameterization of a bound few-body system that is good for inference.

I spent the afternoon at CIS 303, a middle school in the Bronx, as part of their Career and College Day. This is an opportunity for middle schoolers to discuss with people with a huge range of careers and backgrounds what they do and how they got there. So much fun. I also ran into Michael Blanton (NYU) at the event!