These are the parameters of interest, though brown dwarfs could have strong priors based on radius and distance arguments... worth looking into.
v_z and vsini set through "empirical Bayes"
Well, kinda...
flat in logOmega (for now)
IGRINS data aren't flux calibrated.
maximum deviation for Cheb calibration polynomials
This is a huge issue. On one hand, could be unlimited to basically filter out any low frequency structure. On the other hand, it could be strict (<1% peak to valley) to force a fit to the spectral shape. Finally, it could be somewhere in between. I recommend the inbetween, with high limit: peak-to-valley to 10%.
+/-5% in sigmaAmp
We assume we have estimated the mean sigma correctly to within 5%, which is probably accurate. The real problem is the bad pixels. These should just be thrown out!!
logAmp?
We need to get this right and it's a bit involved and bespoke for each order.
GP length scale?
We need to get this right and it should be close to the same for each order.
Here are my thoughts on priors:
uniform in logg, uniform in T_eff
These are the parameters of interest, though brown dwarfs could have strong priors based on radius and distance arguments... worth looking into.
v_z and vsini set through "empirical Bayes"
Well, kinda...
flat in logOmega (for now)
IGRINS data aren't flux calibrated.
maximum deviation for Cheb calibration polynomials
This is a huge issue. On one hand, could be unlimited to basically filter out any low frequency structure. On the other hand, it could be strict (<1% peak to valley) to force a fit to the spectral shape. Finally, it could be somewhere in between. I recommend the inbetween, with high limit: peak-to-valley to 10%.
+/-5% in sigmaAmp
We assume we have estimated the mean sigma correctly to within 5%, which is probably accurate. The real problem is the bad pixels. These should just be thrown out!!
logAmp?
We need to get this right and it's a bit involved and bespoke for each order.
GP length scale?
We need to get this right and it should be close to the same for each order.