I've been thinking about joint transit and RV modeling. In a full joint model, one would include the following parameters
{P, tc, e, w, K, Rp/Rstar, a/Rstar, b}
some variables are informed by both datasets: {P, tc, e, w}
some are just informed by RVs: {K}
some are just informed by the transits {Rp/Rstar, a/Rstar}
However, in general P and tc are typically much better constrained from photometry that we fix-it and forget-it in RV modeling. I think we can do something similar with e and w.
One typically gets a joint constraint on e and w from transit modeling if mean stellar density is known. This could be implemented into radvel 1.4.1 using the existing functionality, but this requires a KDE evaluation.
I sketched out a solution that I think should be much more efficient and could be implemented in a straight forward manner using radvel.prior.UserDefinedPrior. See attached PDF. A project for @mason-macdougall perhaps?
I've been thinking about joint transit and RV modeling. In a full joint model, one would include the following parameters
{P, tc, e, w, K, Rp/Rstar, a/Rstar, b}
However, in general P and tc are typically much better constrained from photometry that we fix-it and forget-it in RV modeling. I think we can do something similar with e and w.
One typically gets a joint constraint on e and w from transit modeling if mean stellar density is known. This could be implemented into radvel 1.4.1 using the existing functionality, but this requires a KDE evaluation.
I sketched out a solution that I think should be much more efficient and could be implemented in a straight forward manner using
radvel.prior.UserDefinedPrior
. See attached PDF. A project for @mason-macdougall perhaps?e-w-constraints-into-radvel.pdf