It seems that success for us will be linked to our ability to correctly remove scattered light from the BS. This hinges on our understanding of the scattering model – in essence, the PSF.
Currently we use a PSF that is empirical. The core is made up of values from a table generated from observations of bright stars and Jupiter. To that we link an extension, also empirical, that is based on what the far wings of the lunar halo looks like. This PSF is then ‘exponentiated’ during fitting to actual images in the EFM method.
We noted during several posts below that the values for the exponent varied little and only now and then seemed linked to the extinction. This could be an indication that most of the time (during good nights) we are limited by something fixed – such as the optics – rather than atmospheric conditions. On the other hand it could mean that the PSF is not very accurate in its basic from and that the fitting method gives up at some stage, leaving us with an exponent that is somewhat random, and therefore not linked to the atmospheric conditions.
We should also recall what happens during application of the EFM method: We have tested various forms of sky masks for this method – some that allowed fitting emphasis on both the DS and BS sky, and others that emphasized only one side. Common for the ones that focused on either just the DS sky or the BS sky was that the halo shape on the other side was not very good.
Might these things be indicating that a better PSF should be generated or a better way found to apply the fits?
I’d like to suggest the following: Perhaps the PSF has a form like
PSF ~1/R^alfa(R)
instead of the present
PSF ~1/R^const_alfa ?
I would like to try to use a piece-wise constant alfa so that the PSF is separated into radial zones, each of which has its own alfa, found by fitting.
More to be added …
