#AstroHackWeek, day three

Early in the morning, before #AstroHackWeek 2016 day three, I had a long phone call with Andy Casey (Cambridge) about The Cannon, RAVE, and Gaia DR1. He is trying to produce a catalog of detailed abundances from RAVE matched to Gaia T-GAS before the DR1 deadline, which is in two weeks! There are many hard parts to this project. One is to make a model of the red giants and a model of the main sequence, and somehow understand that these two models are physically consistent. Another is to get a training set of detailed abundances for main-sequence stars. We also talked about DR1 zero-day projects. I am still stumped as to what, exactly, I am going to do!

I also got a great email this morning from Megan Bedell (Chicago), demonstrating that the convection explanation is reasonable for the radial-velocity scatter she sees in her HARPS data. As my loyal reader may recall, we spent the last few months demonstrating that there is no evidence (and damn, did we search) that the HARPS pipeline is leaving radial-velocity information on the table. If it isn't, then the radial-velocity scatter must come from intrinsic stellar noise (or something much worse). What Bedell has shown is that the quantitative amplitude and granularity of stellar surface convection is sufficient to lead to meter-per-second jitter. Duh! Now we have to figure out how to deal with that. I have ideas, related to The Cannon.

The afternoon and evening of #AstroHackWeek was at GitHub headquarters in San Francisco, which is a (dangerously) fun place to hack. Jonathan Whitmore (Silicon Valley Data Science) gave a great presentation about all the crazy things you can do with a Jupyter notebook, which blew me away, and Phil Marshall (SLAC) gave a presentation to the company about how GitHub is integrated into astrophysics research these days (oh, and what features we would like).

From my (limited) perspective, the most important thing about day three was that Adrian Price-Whelan (Princeton) and I had the final realization that the importance sampling we wanted to do for the radial-velocity problem will not work. Sad, but true: We can't get a complex enough linear model that maps cleanly enough onto the Kepler problem. So we decided to switch gears today to Phil Marshall's favorite: Simple Monte Carlo. What we will do is sample the prior extremely densely, and then rejection sample to the posterior using the likelihood function. This is usually impossible! We will make it possible in this case by capitalizing on the linearity of two of our parameters: These two parameters we can analytically marginalize out at every sample in the four-dimensional space of non-linear parameters. That's our job for tomorrow.

Fail fast. That's what we are trying to do.


  1. David - I also thought about this RV linearization problem a while back (for MARVELS) after a discussion with Jason Wright at TIARA in 2008 (which led to his paper with Andrew Howard on partly linearizing the Kepler problem, 2009ApJS..182..205W). I also had in mind the second-order expansion (and found that the unconstrained amplitudes, which can take on unphysical values, was a problem), but I think this may work well in the case where it is needed most: high-multiplicity multi-planet systems since these systems have small eccentricity due to the necessity of dynamical stability. I tried this out on 55 Cancri (which Wright & Howard studied in the partially linearized case), and I found that I was able to identify a 'global' minimum (i.e. that matched the known exoplanets) in a multi-planet fit quickly & robustly, in which I ran successive periodograms with N=1,2,3,... planets, allowing the period of each planet to vary in the optimization (the only non-linear parameters!), while searching over a sufficiently fine grid of periods for the Nth planet (and starting the 1,...,N-1 planets at the optimum period(s) from the previous periodogram searches). I never wrote this up, but I can send you some notes if you're interested. -Eric

  2. I'm glad that you liked my Jupyter notebook talk! It was great working w/ you and everyone last week.