Fengji Hou (my new student, will be Hou from now on in this diary), his co-advisor Jonathan Goodman (NYU Courant), and I discussed Fengji's start on exoplanet radial velocity fitting using advanced sampling tools. We spent a long time talking about code, but once we were done, Goodman and I spent some time talking about medium-term projects that would be non-trivial and interesting. We discussed the idea that if you are a Bayesian (not always advisable), you don't really want to detect planets per se, you want to pass forward probabilistic information about their existence and properties, and then perform your analysis on those probabilistic outputs. In this world, you might be able to discover and say things about classes of planets that are not detected clearly in any individual stellar radial velocity time series. Approaches like this could greatly increase the number of known expolanets for some kinds of statistical studies.

1 comment:

  1. This reminds me of a talk that I recently heard Scott Ransom give about detecting the gravitational waves produced by SMBH mergers as 10^-14 level variations in pulsar timing solutions. You aren't detecting any individual binaries, just the general background in frequency space of all such objects. I don't think that his analysis is fully Bayesian, though.