Process blank field data with a
jack-knife-based method REDUCE_SCAN_FAINT_POINT_SOURCES_JACKKNIFE
Each observation is processed twice using the specified parameters, the second time with an artificial point source added to the timeseries, to create a signal map and an effective PSF image.
These images are coadded (like with like) to produce a total signal map and a total effective PSF image. The amplitude of the source in the effective PSF image is compared with the input value to assess the effect the map-making process has on a point source. This ratio is used to scale the FCF later when calibrating the data.
The observations are divided into two groups which are coadded separately. These coadds are subtracted from one another to create the jack-knife map.
The angular power spectrum of the jack-knife map (which should consist purely of noise) is calculated and used to remove residual low-spatial frequency noise from the signal map and the effective PSF. This is the so-called whitening step (because it produces a map which has a noise power spectrum that is white).
The data are calibrated in mJy/beam using a corrected FCF.
The whitened signal map is processed with a matched filter using the whitened PSF image as the PSF.
The jack-knife map is also whitened and processed with the matched filter. This map should consist purely of noise.
Signal-to-noise ratio maps are created for the filtered versions of the signal map and the jack-knife map.
The outcome (the match-filtered whitened signal map) should be the optimal map with white noise properties. This is the map to be used for science goals.
This recipe generates a large number of output files. There will be two for each observation (the signal map and the effective PSF map), a total signal coadd, an effective PSF coadded from all the individual effective PSF maps, a jackknife map, a whitened signal map, a calibrated whitened signal map, a matched-filtered calibrated whitened signal map and a signal-to-noise ratio map created from it.
This recipe should only be given data for a single source, and a single field.
An even number of observations will be used to create the jack-knife map.
Alternative configuration parameters for the iterative map-maker may be specified using the recipe parameters outlined below.
This recipe may be called via the shorter name FAINT_POINT_SOURCES_JACKKNIFE.
For large amounts of data this recipe will spend a long time not updating the ORAC-DR window. Check to see that makemap is still processing by running top or ps. (Running with -log sf is recommended.)