We have used the ’empirical forward model’ method to reduce 384 images from night 2455864.

Using the DMI CRAY we stepped through 1000 values of alfa from 1 to 2 for each image and required the best possible fit on the sky part of each image.

We plot the best value of alfa found for each filter againts the time of observation:

We see that the values for alfa are narrowly grouped for most filters, except for the VE1 filter which jumps between two values. Unexpectedly we see that the blue filters have high alfas (i.e. narrow halos) while the reddest filter (VE2) has the smallest value of alfa (i.e. the broadest halo). This is opposite of what we might expect from physics, and the code plotting these data must be reviewed.

The scatter of alfa for e.g. the IRCUT filter is 0.0036 which is 0.2 %. Since we had 98 IRCUT values the standard deviation of the mean alfa is about 0.00036 which is about 3 times larger than the required accuarcy estimated on this page below, to achieve a DS accuracy of 0.1%.

Visual inspection of the fits show that improvements are possible, so more experiments with parameter settings is called for. The above were results from fits of the absolute residuals. Next we try fitting the relative residuals, i.e.

(obs – model)/obs

instead of

(obs – model).

We have now tested that – and it was not a good idea: fits got worse.