Specific characteristics of the JWST Science Calibration Pipeline for processing NIRISS data through the calwebb_detector1  stage of the JWST calibration pipeline are discussed.

See also: JWST Near Infrared Imager and Slitless Spectrograph

Detector1 pipeline steps

Detector-level corrections and calibrations are applied during the calwebb_detector1 stage of the pipeline. By default, all steps in the calwebb_detector1 stage of the pipeline are run for NIRISS except for the ipc and gain_scale steps.

1/f noise

JWST's near-infrared HgCdTe detectors have a correlated noise, known as 1/f noise, that is introduced by the detector readout system (Moseley et al. 2010). It results in stripes in the vertical, or fast-read axis, in each group of an integration and can be a limiting factor in subsequent analysis. Community tools are available to subtract this noise. Investigation is underway to implement a 1/f noise correction into the pipeline to improve the quality of NIRISS data.

Persistence

While the persistence step is set to run by default, this step does not automatically correct the science data for persistence. The persistence step creates a "_trapsfilled.fits" file which is a model that records the number of traps filled at each pixel at the end of an exposure. This file would be used as an input to the persistence step, via the input_trapsfilled argument, to correct a science exposure for persistence. Since persistence is not well calibrated for NIRISS, this correction is not performed and the "_trapsfilled.fits" file is not used.

To run the pipeline in Python to turn off the step to create the "_trapsfilled.fits" file:

from jwst.pipeline import Detector1Pipeline 
rate_file = Detector1Pipeline.call(uncal_file, steps={'persistence': {'skip':True}})

Charge Migration

The charge_migration step is particularly important for NIRISS images to mitigate apparent flux loss in resampled images due to the spilling of charge from a central pixel into its neighboring pixels (see Goudfrooij et al. 2023 for details). Charge migration occurs when the accumulated charge in a central pixel exceeds a certain signal limit, which is ~25,000 ADU. This step is turned on by default for NIRISS imaging, Wide Field Slitless Spectroscopy (WFSS), and Aperture Masking Interferometry (AMI) modes, but not for the Single Object Slitless Spectroscopy (SOSS) mode. Different signal limits for each filter are provided by the pars-chargemigrationstep parameter files which are available via the Calibration Reference Data System (CRDS).

As currently implemented, this step does not attempt to track the charge migration and put the charge back to where it should have been.  Instead, the step truncates the ramp for pixels where the signal goes above the signal limit threshold, and also applies this ramp shortening to the immediately adjacent pixels which are receiving the charge from the high signal pixel.  This improves the count rate calculation, and hence the flux accuracy, for the pixels affected by charge migration.

Users can specify a different signal limit by running this step with the signal_threshold flag and entering another signal limit in units of ADU:

from jwst.pipeline import Detector1Pipeline 
rate_file = Detector1Pipeline.call(uncal_file, steps={'charge_migration': {'signal_threshold':25000}})

Correcting snowball halo residuals

See also: Snowballs and Shower Artifacts

Large cosmic ray impacts cause features known as snowballs on near-infrared detectors which can affect up to hundreds of pixels. The effects of the snowballs are mostly flagged in the jump step and removed, although this is not always true for NIS readout.  However, there are commonly uncorrected low-level signal residuals surrounding snowballs that can be removed by running the jump step with the expand_large_events parameter set to True.

By default, this option is turned on for the NIRISS imaging, WFSS, and AMI modes but not the SOSS mode. The chosen default parameters for NIRISS can be found in the pars-jumpstep reference file. Users may wish to alter parameters to optimize removal of snowball residuals. Available parameters are discussed in the Detection and Flagging of Showers and Snowballs in JWST Technical Report (Regan 2023).

References

Goudfrooij, P., et al. 2023 arXiv:2311.16301
An Algorithm to Mitigate Charge Migration Effects in Data from the Near Infrared Imager and Slitless Spectrograph on the James Webb Space Telescope

Moseley, S. H., et al. 2010 SPIE Proceedings Vol.  7742
Reducing the read noise of H2RG detector arrays: eliminating correlated noise with efficient use of reference signals

Regan, M. 2023, JWST-STScI-008545
Detection and Flagging of Showers and Snowballs in JWST