Known issues specific to MIRI LRS 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.

Please also refer to MIRI LRS Calibration Status for an overview of the current astrometric and flux calibration of MIRI LRS data products.

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Telescope operations

Problems with blind pointing to the LRS slit have been solved

In cases where self-TA will not work and a suitable offset TA target cannot be found, the STScI MIRI team now can recommend blind pointing. See the target acquisition page for more guidance.

Artifacts

Scattered light in the LRS

See also: MIRI Low Resolution Spectroscopy

If a bright target is present in the imager field, its light may scatter into the region where the LRS slit is dispersed. Scattered light artifacts are seen in the detector substrate around bright sources (see the cruciform artifact), so these features can persist despite the presence of a focal plane mask. As the pipeline extracts a cutout region from the array in the later stages of the stage 2 pipeline (the photom and resample_spec steps), it's recommended that users inspect level 2a data (the "rate.fits" file) to check for the presence of such contaminating sources. If science target is reasonably compact, users are encouraged to experiment with PSF-based spectral extraction to remove background.

Useable wavelength range, spectral fold over and leak in LRS slitless

The blue limit is nominally 5 µm, as explained below. It is at a slightly longer wavelength for slitless. The red limit is nominally 14µm. However, the signal-to-noise ratio in science data and some reference files can be low, which can reduce the red limit to 13 µm or even 12 µm.

As both slit and slitless modes use the same dispersing element, the dispersion profile is similar for both, modulo changes due to optical distortion. The nominal spectral range of 5–12 µm is dispersed over ~370 pixels. The dispersion profile however folds over below 4.5 µm (where the prism throughput is very low), superimposing 2 parts of the spectrum onto each other. A dedicated filter is mounted over the slit to block radiation shortward of 4.5 µm to avoid this contamination in the slit. This effect is not mitigated for LRS in slitless mode, causing some spectral contamination at the shortest wavelengths. 

For a source with a different spectral shape than our standard stars (e.g., a red object), the spectral fold over can result in calibration artifacts, which can push the blue limit for useable spectral data to longer wavelengths. In these cases, the blue limit can be shifted to as far as 5.2 µm.

Electromagnetic interference (EMI) pattern noise

All MIRI data show coherent pattern noise from electromagnetic interference. While the 10 Hz heater noise affecting all MIRI data is subtle, 390 Hz noise is prominent in most MIRI subarray data whose readouts are out of phase with this signal. In jwst pipeline version 1.13.0 a new step was added to the calwebb_detector1 pipeline to correct for this correlated noise by calculating the phase of each detector pixel and searching for and removing periodic amplitude variations at the known EMI frequencies. In the future, the MIRI subarray locations may be moved to be better in phase with any EMI.

As of build 11.3, the pipeline has been optimized to correct this for all slitless data (see Figure 2).

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Pipeline notes

Background subtraction (slitless mode)

The JWST calibration pipeline does not currently perform any background subtraction on the spectral images taken with the slitless LRS mode. Work is being done to implement an optimized algorithm for this in the Fall 2025 pipeline update (build 12.1). Based on experience with commissioning and early science data, the following strategies are recommended:

• A very simple background subtraction can be performed as part of the spectral extraction in the extract_1d step of the calwebb_spec2 pipeline. By creating a custom reference file for the extract_1d step, an off-target background region can be defined alongside the source region, from which a background is computed. This is demonstrated in the materials of the TSO JWebbinar (see video, notebook). 
  
  
• A better result is obtained by manually computing a background spectrum from off-target regions of the subarray in the "rateints.file", for each individual integration. The best regions of the subarrays from which the background is computed are those at the edges of the subarray (excluding the first 4 columns, which contain the reference pixels). By median-combining different off-target regions to compute an effective background, a 2-D background image can be constructed, and subtracted from the science data. If this operation is performed on the "rateints" product, the same file can then be processed further through the calwebb_spec2 pipeline. 

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Summary of common issues and workarounds

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

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