Known issues specific to NIRSpec data processing in the JWST Science Calibration Pipeline are described in this article. This is not intended as a how-to guide or as full documentation of individual pipeline steps, but rather to give a scientist-level overview of issues that users should be aware of for their science. 

Specific artifacts are described in the Artifacts section below. Guidance on using the pipeline data products is provided in the Pipeline Notes section along with a summary of some common issues and workarounds in the summary section.

Information provided in this article affects all NIRSpec observing modes. For mode-specific issues, see the NIRSpec BOTS, fixed slit, IFU, and MOS issues articles. For a detailed discussion of many aspects of the NIRSpec detectors and their impact on science calibration, see NIRSpec Detectors. 

Please also refer to NIRSpec Calibration Status.

Artifacts

Spurious features in extracted 1-D spectra

Pixels flagged as "DO_NOT_USE" in the data quality (DQ) array are excluded from spectral extraction, with the possibility of causing divots in the final 1-D spectrum. If the flagged pixel is close to the center of the point spread function (PSF) at a given wavelength, the absence of the signal in the flagged pixel will lead to a divot at that wavelength in the extracted spectrum.

A pixel_replace step has been created for the pipeline, based on an adjacent profile approximation, which generates an average spatial profile from columns immediately adjacent to the one with the bad pixel, normalizes that profile to the good data in the affected column and uses the value of the corresponding pixel in the normalized profile to replace the signal in the bad pixel. Currently this step uses a default-off configuration for all NIRSpec modes. Use of this step can introduce artifacts when pixels are over-corrected by the spatial profile normalization. Bad corrections may have worse impacts on calwebb_spec3 reductions than no corrections.  

The NIRSpec team continues to explore options for handling missing pixel data. In the meantime, pipeline users can test the use of the pixel_replace step on their data sets by setting skip = False in the parameters for the pixel_replace step in the stage 2 pipeline.

Snowballs

The detectors used in NIRSpec experience cosmic ray events known as snowballs and showers. Pipeline algorithms to address these artifacts are under development; in the interim, the best mitigation strategy is to dither. 

Pipeline Notes

See known issues pages for NIRSpec BOTS, fixed slit, IFU, and MOS modes.

 Alternating column noise

A pattern of alternating brighter/darker pixel rows over part or all of a detector image is an effect sometimes referred to as alternating column noise (ACN; note that pixel rows in the science data actually represent columns in the detector frame of reference, as the data are rotated to put the dispersion direction horizontally). This is due to the two amplifiers (one for odd and one for even columns) in an output sometimes having slightly different offsets because of drift or a cosmic ray event. Pipeline code testing is underway to mitigate this odd-even column discrepancy.

Uncorrected correlated noise - 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). This noise results in horizontal striping, as illustrated in Figure 2. With NIRSpec's IRS² readout mode, reference pixels are interspersed with the sampling of normal pixels to mitigate the 1/f noise. However, this noise will still be present in data taken with NIRSpec's traditional detector readout mode; this includes all observations made with NIRSpec's subarrays, where IRS² is unavailable. In these cases, it may be necessary to use background pixels in the horizontal bands to estimate and subtract the 1/f noise. The accompanying mode-specific pages further discuss 1/f noise.

To address this issue, the JWST Science Calibration Pipeline has integrated an external package developed by Bernard Rauscher, known as NSClean (Rauscher 2024), within the Spec2Pipeline under NSCleanStep. This algorithm uses dark areas of the detector to fit a background model to the data in Fourier space. It requires an input mask to identify all dark areas of the detector. The more thorough and complete this mask is, the better the background fit. The pipeline creates an on-the-fly mask using default parameters to remove 1/f noise, and the user should refer to the optional parameters for this pipeline step if the default settings are not sufficient for the data. If needed, see the NSClean documentation for suggestions on manually creating a custom mask.

Pixel rows exhibit anomalous count rates in "rate" images for IRS2 data.

Some reference pixels are "bad" (e.g., excessive noise or "telegraph" behavior) and are flagged as such. However, those flags are not considered in the refpix step of the calwebb_detector1 pipeline, resulting in anomalous corrections for the associated science pixels, leading to image behavior in Figure 3. A flag check has been implemented in the pipeline, along with an improved algorithm to filter out noisy reference pixels.

No flux or negative flux in FS or MOS extracted 1-D spectrum 

The extract_1d step uses an automated centering routine to place the extraction aperture, based on the source coordinates. The extraction aperture can be offset along the spatial axis, for example, due to an error in target coordinates or the world coordinate system. The assumed source position should work well for most NIRSpec sources, but in case the extraction aperture is still poorly placed, it can be manually tweaked by specifying start and stop positions to the extraction step. (Extraction parameters can be set in a reference file in JSON format, described in the pipeline documentation.) Instead of using the sky position, one can use the relative slit position of the target, as planned in APT, to place the aperture. Following a successful target acquisition, this position is typically known with high accuracy (~5–10 mas). The automatic centering can be overridden by setting the optional step argument use_source_posn = False, and modifying the reference file parameters ystart and ystop (found in the pipeline output log file) to define the desired boundary of the extraction aperture (in integer pixels or the use of polynomial  for fractional pixels). More on this can be found on the NIRSpec MOS Known Issues page. 

Summary of common issues and workarounds

The sections above provide detail on each of the known issues affecting NIRSpec data; the table below summarizes some of the most likely issues users may encounter along with any workarounds, if available. Note that greyed-out issues have been retired, and are fixed as of the indicated pipeline build. 

References

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

Rauscher, B. J. 2024 PASP 136:015001
NSClean: An Algorithm for removing Correlated Noise from JWST NIRSpec Images