The algorithms for CALWEBB_CORON3, which is Stage 3 of the JWST calibration pipeline for coronagraphic data, are described. These algorithms process the data from calibrated slope images to combined, reference PSF subtracted coadded images.
The CALWEBB_CORON3 module is Stage 3 of the JWST calibration pipeline for NIRCam and MIRI Coronagraphic data. The inputs to this stage are the calibrated slope images (CALWEBB_IMAGE2 output) and the output is a reference PSF subtracted image stack. The steps are listed in Figure 1 with the flow from the top to the bottom.
Unless otherwise stated, the algorithms described are the baseline version.
Steps for all coronagraphic data
Note that all steps in this module are common to both NIR and MIR data.
Assemble reference PSFs
See also: Stack Refs (more detailed software module documentation)
The available list of reference PSFs is generated. These reference PSFs can include reference stars specifically observed for the target as well as observations of the target taken at different orientations.
See also: Outlier Detection (more detailed software module documentation)
Outlier detection is done using the image stack. The majority of the outliers will be due to cosmic rays undetected during the 1st pass at outlier detection done in CALWEBB_DETECTOR1. An iterative sigma clipping algorithm is used in pixel coordinates on the image stack. The presence of an outlier results in a pixel flag being set.
Align reference PSFs
See also: Align Refs (more detailed software module documentation)
The reference PSFs are aligned with the target observation using the Fourier LSQ algorithm to measure the shifts and the Fourier Shift algorithm to apply the shifts to each reference PSF integration.
Reference PSF subtraction
See also: KLIP Processing (more detailed software module documentation)
The reference PSF that is subtracted from each target integration is created using the list of reference PSFs and the KLIP algorithm (Soummer et al. 2012).
See also: Resample (more detailed software module documentation)
The target images (including those at different rotations) are combined into a single combined image. This is done using the AstroDrizzle code with the output pixel size set to the input pixel size.
Exposure level products
The exposure level products are re-created at this stage to provide the highest quality products that include the results of the ensemble processing (updated WCS, matching backgrounds, and 2nd pass outlier detection). These products are for the archive and include the unrectified 2D images and rectified 2D images.
Soummer, R., Pueyo, R., Larkin, J., 2012, ApJ, 755, 28
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