If you look closely at the spectrum in #9 you can see places where the model fit is so good that it implies the underlying template would be adequate for a deconvolution approach: infer the convolution kernel that gives rise to the line profile perturbations. I am inclined to try this out. If we do this on a few trustworthy regions and get about the same kernel then we can have some assurance that the signal is genuine. My scientific expectation is that the kernel should vary smoothly with wavelength, so comparing adjacent orders may be fine, but H- and K-band could very well have different characteristic vsini values depending how their equators and poles are illuminated.
If you look closely at the spectrum in #9 you can see places where the model fit is so good that it implies the underlying template would be adequate for a deconvolution approach: infer the convolution kernel that gives rise to the line profile perturbations. I am inclined to try this out. If we do this on a few trustworthy regions and get about the same kernel then we can have some assurance that the signal is genuine. My scientific expectation is that the kernel should vary smoothly with wavelength, so comparing adjacent orders may be fine, but H- and K-band could very well have different characteristic vsini values depending how their equators and poles are illuminated.