Correct estimation of MUSE PSFs and deconvolution
The model MUSE PSFs were incorrectly calculated until now! I was mistakenly assuming that the `FSF01FWA' was the FWHM. However, the FWHM must be calculated from `b*lambda+a' where `b' is the value to `FSF01FWB' keyword and `a' is the value of `FSF01FWA'. The effective `lambda' (or wavelength) to use for each broad-band filter is the throughput-weighted average wavelength of the filter. So, the pipeline now uses the HST filter throughputs to find `lambda' and then uses the values of these keywords to generate the proper FWHM for the Moffat function. The throughputs will be downloaded if not already available. The FWHMs decreased from around 14 pixels to around 10 pixels. After implementing this correction, a test run of the deconvolution gave a better result. The reason was that the image crop to feed into the deconvolution algorithm was larger and so lower frequencies could be sampled. After seeing this trend, I increased the truncation radius of the model MUSE PSFs and also the deconvolution image size and saw that the deconvolution output kernel is becoming better and better. I finally stopped at 6 times the FWHM since it was apparently not making much more change. So, now the proper kernel to convolve with the HST images is created and we can directly compare the results with the MUSE images without worrying about a larger PSF. After convolution, the HST images are now also sampled to the same pixel size as MUSE.
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