combinatoric options for a paper

I had my weekly call with Bonaca (Harvard), about information theory and cold stellar streams. We discussed which streams we should be considering in our paper. We have combinatoric choices, because there are N streams and K Milky-Way parameters; we could constrain any combination of parameters with any combination of streams! And it is even worse than that, because we are talking about basis-function expansions for the Milky-Way potential, which means that K is tending to infinity! We tentatively decided to do something fairly comprehensive and live with the fact that we won't be able to fully interpret it with finite page charges.

circumbinary planets, next-gen EPRV

The Gaia DR2 workshop and Stars Group meeting were both very well attended! At the former, Price-Whelan (Princeton) showed us PyGaia, a tool from Anthony Brown's group in Leiden to simulate the measurement properties of the Gaia Mission. It is really a noise model. And incredibly useful, and easy to use.

In the Stars meeting, so many things! Andrew Mann (Columbia) spoke about the reality or controversies around Planet 9, which got us arguing also about claims of extra-solar asteroids. Kopytova (ASU) described her project to sensitively find chemical abundance anomalies among stars with companions, and asked the audience to help find ways that true effects could be scooped. Her method is very safe, so it takes a near-conspiracy, I think, but Brewer (Yale) disagreed. Veselin Kostov (Goddard) talked about searching for circumbinary planets. This is a good idea! He has found a few in Kepler but believes there are more hidden. It is interesting for TESS for a number of reasons, one of which is that you can sometimes infer the period of the exoplanet with only a short stretch of transit data (much shorter than the period), by capitalizing on a double-transit across the binary.

Didier Queloz (Cambridge) was in town for the day. Bedell (Flatiron) and I discussed with him next-generation projects for HARPS and new HARPS-like instruments. He is pushing for extended campaigns on limited sets of bright stars. I like this idea for its statistical and experimental-design simplicity! But (as he notes) it is hard to get the heterogeneous community behind such big projects. He has a project to pitch, however, if people are looking to buy in to new data sources. He, Bedell, and I discussed what we know about limits to precision in this kind of work. We aren't far apart, in that we all agree that HARPS (and its competitors) are extremely well calibrated machines, much better calibrated than the end-to-end precision obtained.

searches for anomalies

Today Kate Storey-Fisher (NYU) and I met with Mike Blanton (NYU) and Zhongxu Zhai (NYU) to discuss possible projects that Storey-Fisher and I have been talking about. We are thinking about trying to systematize (and pre-register) the search for anomalies in cosmological surveys. The idea (which is still vague) is to somehow lexicographically order all anomalies we could search for, and then search, such that we can keep exquisite track of the number of independent hypotheses we have checked.

Blanton and Zhai had some advice for us. One category of advice was around systematics: Anomalies and systematics in the data might appear similar! So we should think about anomalies that are somehow least sensitive to these systematics. One good thing is that we are working at the home of many of the tools that we need to make these assessments. Another category of advice was to think about what anomalies are motivated by questions of theory in the dark sector, in galaxy formation, or in the initial conditions. Theory-inspired (if not predicted) anomalies are more productive, in a scientific-literature sense, than randomly specified anomalies. We are close to being able to specify a project!

detailed abundances and stellar companions

Taisiya Kopytova arrived in NYC for a few days to work on stellar abundances and orbital companions. Her project is very well designed: She has a set of red-giant stars in APOGEE where we know they have companions. For each of these stars with companions, she has found a set of matched stars—matched in stellar parameters—that don't have companions (or not companions that are detectable). She then compares the detailed chemical abundances between these two samples. The approach is extremely conservative and very robust to problems in the data: For a false effect to appear, it has to be an effect that causes a companion to be detected (or not detected)! And she finds signals.

One disturbing thing is that we find signal-to-noise effects, and we get slightly different results when we use APOGEE DR13 or DR14 data. So we might need to match on signal-to-noise as well as stellar parameters.

paper scopes, voids

In Friday parallel-working session, Megan Bedell (Flatiron) and I discussed (for the nth time) the scope of the first paper and next papers in our extreme-precision radial-velocity work. We realized that paper 1 is pretty-much ready to go! We also realized that the point should not be about what people might be doing wrong, but about what things you can do that are easy and close to correct. In particular, the point that a data-driven spectral model can come close to saturating the Cramér–Rao bound on radial-velocity. This was not obvious at the outset, because some of the information in the data must go into the spectral model (and not the RV measurement). That's a good point!

Renée Hlozek (Toronto) gave the Astrophysics Seminar. In part she talked about the negative S–Z effect from voids. In another part, she talked about constraining light scalar dark matter with large-scale structure. Both problems I am interested in for near-future research. In the afternoon, she and Alex Malz (NYU) and I talked about advising and mentoring. Hlozek is a deep thinker about these things.

geometry bugs

In our weekly meeting, Ana Bonaca (Harvard) and I discovered a super-subtle bug in how the covariance matrices we are making (context: the Cramér–Rao bound on Milky-Way parameters given observations (and a model) of cold stellar streams) are being plotted. Damn geometry is hard! But she fixed the code and all our covariances look really good now. We think we understand the trade-offs between different parameters, given different data. Time to write! And use the framework for planning new observations.

I spent the rest of the day not working on my NSF proposal, which is very bad!

Gaia DR2 halo and disk projects

Today Kathryn Johnston (Columbia) came through Flatiron to discuss Gaia DR2 projects in the Milky-Way halo. She made the very nice point that we could use a Gaia simulator like PyGaia to “observe” the Bullock & Johnston all-substructure simulations to see how halo substructure appears in a realistic DR2 data set. We discussed clustering algorithms and the relationships between applying clustering directly to the observed data vs transforming the data to some better space (invariants, say) vs doing some kind of inference or data-driven model that respects the Gaia noise model and so on. We are looking for methods that will be powerful, but simple, since we are looking for fast projects to do in the immediate follow-up period to the data release.

Our conversation veered into chemical-abundance space, where we all realized that Megan Bedell (Flatiron) is sitting on an amazing chemical-tagging data set. She only has 80 stars, but because they are Solar twins, they have exceedingly good chemical measurements. Can we use these to measure scattering processes in the Milky-Way disk?

We also briefly discussed something inspired by Alyssa Goodman (Harvard), who spoke first thing in the morning at the Scientific Visualization conference that is on at Flatiron: Can we measure our position relative to the disk plane, and maybe see fluctuations in that plane? Goodman says that the Sun is 25 pc above the plane, and that is obvious (she says) from the radio observations of HI gas. But Bovy (if I recall correctly) looked at this in Gaia DR1 and finds that our offset from the midplane is less than 10 pc. Is there an offset between stars and gas? If so, why? If not, who is wrong? Great set of questions for DR2.

heteroskedastic GPLVM; search for anomalies

Christina Eilers (MPIA) and I have decided to re-implement the Gaussian Process latent-variable model, with modifications that permit the data to be heteroskedastic (and missing) and the kernel function to be different along different dimensions of the data space. We spent an hour today de-bugging analytic derivatives. We need these, because there is a non-convex optimization as part of that model. We resolved to bring the action to New York and have Foreman-Mackey (Flatiron) help us re-implement everything in george. I was left with homework to write this model down in full generality.

Kate Storey-Fisher (NYU) and I got close to specifying a well-posed problem in our nascent project to find CMB-like anomalies in large-scale structure data. We read this paper by NYU locals about prospects for future surveys, but we want to work with real data if we can. We discussed how a search for anomalies can be cast as a parameter estimation problem. We haven't settled on a methodology, though.

linear models for nuisances

The day started with Rodrigo Luger (UW) and Dan Foreman-Mackey (Flatiron) and me discussing a range of projects. They endorsed my general idea of looking for planets by searching resonances! Which is good. We tentatively decided to try to write one of the new ApJ Research Notes about our systematics models for Kepler and other projects. There are a lot of unifying good ideas there; let's spread the Good News. The idea is that it is possible to simultaneously fit a linear model and marginalize it out with a simple linear-algebra move. Work on that started almost immediately.

Lauren Anderson (Flatiron) visualized the proper motions of stars in the Galaxia model as a function of sky position and distance, to see if proper motions can be used to infer distances by methods that are more clever than reduced proper motion. It looks like they can be! We discussed further improvements to the visuals, with help from Vasily Belokurov (Cambridge).

stellar age–velocity relation

Jonathan Bird (Vandy) and I spent the morning working together on his paper on the age–velocity relationship in the Milky-Way disk. He has absolutely beautiful results, from APOGEE red-clump stars and Gaia DR1 transverse kinematics. The thing that is new is that (thanks Martig and Ness) he has actually useful age estimates for many hundreds of stars. And we will have the same for tens of thousands in the overlap with Gaia DR2. Indeed, we commented in the paper that SDSS-V will make this possible at scale. The great thing about the ages is that even with hundreds of stars, we get a comparable measure of the age–velocity relation to studies that involved orders of magnitude more stars.

We discussed the final presentation in the paper. We worked through the figures and drew a simple graphical model to illustrate the project. We then went, very carefully, through the assumptions of the project, so we can state them explicitly at the outset of our methods section, and then use them to structure the discussion at the end. It's a fun intellectual exercise to go through these assumptions carefully; somehow you only understand a project substantially after it is finished!

self-calibration of stellar abundances

I spent the day at Vanderbilt, where I gave a talk and had many valuable conversations. Some were about data science: Andreas Berlind (Vanderbilt) is chairing a committee to propose a model for data science at Vanderbilt. We discussed the details that have been important at NYU.

One impressive project I learned about today was Hypatia, a compendium of all detailed stellar abundance measurements (and relevant housekeeping data) in the literature. Over dinner, Natalie Hinkel (Vanderbilt) and I discussed the possibility that this catalog could be used for some kind of self-calibration of all abundance measurements. That's an interesting idea, and connects to things I have discussed over the years with Andy Casey (Monash).

self-calibrating pulsar arrays, and much more

I had a great conversation with Chiara Mingarelli (Flatiron) and Ellie Schwab (AMNH) today about pulsar-timing arrays and gravitational-wave sources. We are developing some ideas about self-calibration of the arrays, such that we might be able to simultanously search for coherent sources (that is: not just stochastic backgrounds) and also precisely determine the distances to the individual pulsars to many digits of accuracy!. It is futuristic stuff, and there are lots of ways it might fail badly, but if I am right that the self-calibration of the arrays is possible, it would make the arrays a few to tens of times more sensitive to sources! We started with Mingarelli assigning us some reading homework.

In the Stars group meeting, we had a productive discussion led by Megan Bedell (Flatiron), Andrew Mann (Columbia), and John Brewer (Yale) about things learned at the recent #KnowThyStar conference. There are some new uses of machine learning and data-driven models that I might need to spend some time criticizing! And it appears that there are some serious discrepancies between asteroseismic scaling relations for stellar radii and interferometric measurements. Not bigger than those expected by the stellar experts, apparently, but much bigger than assumed by some of the exoplanet community.

Prior to that, in our weekly Gaia DR2 prep working session, we discussed the use of proper motion as a distance indicator in a post-reduced-proper-motion world. That is: The assumptions underlying reduced proper motion are not great, and will be strongly violated in the DR2 data set. So let's replace it with a much better thing!

Adrian Price-Whelan (Princeton) showed some incredible properties of (flowing from beautiful design of) the astropy coordinates package. Damn!

writing projects

Coming off my personal success of (finally) getting a paper on the arXiv yesterday (check the footnote on the cover page), I worked through two projects that are close to being writeable or finishable. The first is a paper with Stephen Feeney (Flatiron) on the Lutz-Kelker correction, when to use it (never) and what it is (a correction from ML to MAP). The second is a document I wrote many months ago about finding similar or identical objects in noisy data. After I read through both, I got daunted by the work that needs to happen! So I borked. I love my job! But writing is definitely hard.

discovery! submission!

It was an important day for physics: The LIGO/VIRGO collaboration and a huge group of astronomical observational facilities and teams announced the discovery of a neutron-star–neutron-star binary inspiral. It has all the properties it needs to have to be the source of r-process elements, as the theorists have been telling us it would. Incredible. And a huge win for everyone involved. Lots of questions remain (for me, anyway) about the 2-s delay between GW and EM, and about the confidence with which we can say we are seeing the r process!

It was also an unusual day for me: After working a long session on the weekend, Dan Foreman-Mackey (Flatiron) and I finished our pedagogical document about MCMC sampling. I ended the day by posting it to arXiv and submitting it (although this seems insane) to a special issue of the ApJ. I don't write many first-author publications, so this was a very, very good day.

calibration of ZTF; interpolation

I am loving the Friday-morning parallel working sessions in my office. I am not sure that anyone else is getting anything out of them! Today Anna Ho (Caltech) and I discussed things in my work on calibration and data-driven models (two extremely closely related subjects) that might be of use to the ZTF and SEDM projects going on at Caltech.

Late in the morning, an argument broke out about using deep learning to interpolate model grids. Many projects are doing this, and it is interesting (and odd) to me that you would choose a hard-to-control deep network when you could use an easy-to-control function space (like a Gaussian Process, stationary or non-stationary). But the deep-learning toothpaste is hard to put back into the tube! That said, it does have its uses. One of my medium-term goals is to write something about what those uses are.