Algorithms for calwebb_coron3, which is stage 3 of the JWST Science Calibration Pipeline for coronagraphic data, are used to process data from calibrated slope images to combined, reference-PSF-subtracted coadded images. 

The calwebb_coron3 module is stage 3 of the JWST Science 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.

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Steps for all coronagraphic data

Note that all steps in this module are common to both NIR and MIR data.

Assemble reference PSFs

Software documentation outside JDox: Stack Refs 

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.

Outlier detection

Software documentation outside JDox: Outlier Detection 

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

Software documentation outside JDox: Align Refs 

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

Software documentation outside JDox: KLIP Processing 

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).

Image combination

Software documentation outside JDox: Resample 

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 2-D images and rectified 2-D images.

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References

Soummer, R., Pueyo, R., Larkin, J., 2012, ApJ, 755, 28
Detection and Characterization of Exoplanets and Disks Using Projections on Karhunen-Loève Eigenimages

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