Simple Monte Carlo; a noise model

After the successes of yesterday on our custom radial-velocity sampler, currently called The Joker (but not pronounced how you might think), I put some time into writing the method section. One complex point of the sampling, which is fundamentally not Markov but instead just Simple Monte Carlo, is that if the SMC doesn't lead to many surviving samples, we either do more SMC or else switch over to a standard MCMC, initialized by the output of the SMC. That took some design thought; it capitalizes on an important point of problem structure, which is that—given a finite time window of observations—there is a finite resolution to likelihood peaks in the period direction. It remains to be seen if what we have designed will work.

Early in the day, I spoke with Andy Casey (Cambridge) about a possible noise model for the label outputs from The Cannon acting on the RAVE data. As my loyal reader knows, we consider the formal uncertainties coming from The Cannon to be under-estimates. It sounds like Casey has good evidence for a noise floor, which can be added in quadrature and make repeat visits to spectra more-or-less consistent. It's do-or-die because he needs to submit this paper today or tomorrow!

1 comment:

  1. There are lots of MCMC codes for fitting radial velocity data. Mine is the best ;-) What's unique about this one?