MIRI LRS Known Issues
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.
On this page
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.
Telescope operations
Problems with blind pointing to the LRS slit due to the FGS-MIRI misalignment
The astrometric alignment between the FGS (FGS1 and FGS2) and MIRI focal planes has been found to have a small systematic offset in the V3 axis, of around 0.15"–0.2" (approx. 1–2 pixels). This can result in offsets of ~0.1"–0.2" in RA, Dec in the observation (due to the angle between the V2-V3 and sky coordinate systems). When using target acquisition, this issue should not have any impact on the data quality if the coordinates of the TA target are accurate and the source is placed well within the TA region of interest. In this case, the TA procedure will locate the source and place it into the slit, correcting the small systematic. However, in observations that do not use TA this issue will result in the source being placed off-center in the slit, or even outside the slit altogether. Until this issue is resolved, STScI strongly recommends against using blind pointing with the LRS slit mode. If TA is not an option for an observation, users should work with their contact scientist to work out an optimal solution.
For LRS Observations in slitless mode, a misplacement of the target by 1–2 pixels does not have as severe an impact on the data quality as when using the slit, but will result in calibration inaccuracies. These can be corrected using the JWST calibration pipeline, but users are still advised to use TA as default strategy for their science.
Dedicated background observations with LRS in slit or slitless mode can continue to use a no-TA strategy without issue.
Artifacts
Scattered light in the LRS
See also: MIRI Low Resolution Spectroscopy
Words in bold are GUI menus/
panels or data software packages;
bold italics are buttons in GUI
tools or package parameters.
Figure 1. Light scattered from the imager field of view into the LRS spectral location
Click on the figure for a larger view.
Image of a bright source in the imager FOV during an LRS observation. Light from the bright source is dispersed and scatters into the LRS slit spectrum. Image section (a) shows the entire imager FOV, with the slit marked in green, the TA ROI in yellow, and the zoomed region in dashed white. (b) shows the zoomed region from the full FOV. (c) shows the level s2d pipeline product, which shows both LRS along-slit nods subtracted (resulting in the negative and positive spectral images). As mentioned above, the pipeline does not automatically remove this scattered light contamination.
LRS slitless spectral foldover and leak
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.
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.
While effective for most MIRI LRS slitless data, the new pipeline correction for 390 Hz noise is not yet optimal for data with less than 10 integrations. Corrections improve for data with more than 10 integrations (see Figure 2).
Figure 2. Pipeline correction for 390 Hz noise in the LRS slitless subarray
Click on the figure for a larger view.
Rate image for a source observed with the MIRI LRS slitless subarray. On the left is the image showing a pronounced 390 Hz coherent pattern noise, on the right is the corrected output produced by the emicorr step in calwebb_detector1.
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. 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.
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.
| Symptoms | Cause | Workaround | Fix build | Mitigation Plan |
|---|---|---|---|---|
MIRI-LRS03: Spectra of bright sources can experience data dropouts at wavelengths where they are brightest (in the "x1d" files). The problem can also be seen in 2-D spectral images, with the peak column flagged as "DO_NOT_USE" in several adjacent rows where the spectrum is brightest. | The jump detection step in calwebb_detector1 can flag pixels with strong signals as "DO_NOT_USE" in the spectral images even though the data are viable. These pixels are "NaN" in the spectral images and their signal is missing from the affected wavelengths in the extracted spectra. | Users can run calwebb_detector1 themselves and adjust the rejection_threshold parameter in the jump step to eliminate (or reduce) improper flagging. A generic workaround is challenging to produce as the occurrence and severity of the issue depends on several factors, e.g., target brightness and number of groups per integration. | N/A | Updated issue The jump step algorithm and default parameters are continually being examined and optimized; improvements are expected in future builds (spring 2024 and beyond). The issue likely cannot be entirely eliminated as it differs greatly between observations (and indeed many are not affected). |
| MIRI-LRS04: Spectra extracted from the LRS slit ("x1d" files) can show major disparities between the nods or with expected values. | The pathloss correction is generating incorrect results due to a poor understanding of the location of the source in the slit. | The "pathloss" reference file has already been modified to apply a correction as though the source were in the center of the slit, no matter where it actually is (or where it is believed to be). Effective with build 10.0, even if the pipeline thinks a source is out of the slit, it will still be corrected as though it were in the center of the slit. | N/A | Updated issue The Science Calibration Pipeline has been modified as described in the workaround column. Longer term, the Operations Pipeline will be modified to determine the source position based on the TA verification image. That solution is not yet implemented. |
| MIRI-LRS05: The "ERR" extension in "rate" data products (and other error estimates downstream) is incorrect. | Error values are estimated incorrectly by the pipeline. | Bootstrap uncertainty from science spectra. | N/A | Created issue The root cause of incorrect error estimates in the pipeline is being investigated. |
| MIRI-LRS06: Target acquisition images taken with FASTGRPAVG readout patterns are incorrectly calibrated. | The calibration pipeline does not compute the exposure time for these readout modes when fitting a slope to the uncalibrated data. | The verification images are calibrated correctly; if additional photometry is required, the MIRI team recommends the use these images. | N/A | Created issue The issue will be fixed in the calibration pipeline code in early 2024. |
| MIRI-LRS07: FGS-MIRI alignment issue | A calibration issue resulting in a systematic offset of ~0.15-0.20" in the V3 axis between FGS and the MIRI Imager focal plane. | Using TA will mitigate this issue very effectively (including TA with an offset target). If TA is not possible, the offset may be added to compensate for the issue; please work with your contact scientist to identify the best solution for your observations. | N/A | Created issue. Analysis is in progress. The imager distortion reference file will be updated and redelivered in a future pipeline build. |
| MIRI-LRS08: Scattered light in the LRS slit image | Dispersed airy rings from bright targets in the imager field can spread into LRS slit region. | No fix, but be sure to inspect level 2A data for this type of contamination. | N/A | Created issue. Analysis in progress. |
| MIRI-LRS09: Background gradients and residuals in LRS spectral images. | Multiple: stray light from bright sources in imaging field, persistence from the slit image, real gradients and complex backgrounds, and possibly more. | None at this time. | N/A | Created issue. Investigation in progress. When PSF-based spectral extraction is released, fitting a polynomial background wavelength by wavelength may help. |
| MR-LRS02: Extracted 1-D spectra ("x1d" files) often show salt-and-pepper noise (i.e., spikes and divots one pixel across). | Pixels flagged as "DO_NOT_USE" appear as "NaN" in the spectral images, and the signal in those pixels is missing from the summed signal at that wavelength in the extracted spectra. | Users can apply the new pixel_replace step in the developmental pipeline, which replaces the pixels flagged "DO_NOT_USE" with pixels in the same column by normalizing nearby spatial profiles in the 2-D spectral images. The best solution is to download the developmental program and just run it. The default for pixel_replace is to use 3 rows above and below the problematic row. This value can be changed by setting the n_adjacent_rows argument. | Updated Operations Pipeline The new pixel_replace step was implemented in the Operations Pipeline, installed on August 24, 2023. STScI reprocessed affected data products, which typically takes 2–4 weeks after the update. | |
| MR-LRS01: Spectra extracted from LRS slit and slitless data ("x1d" files) can have little or no signal, or even negative signal, even though the 2-D spectral images look fine. | The pipeline is extracting the spectrum from the wrong location in the 2-D spectral images because the positions it is using to determine the location of the source are inaccurate. | Users can set the location and the width of the extraction apertures themselves when running calwebb_spec2 or calwebb_spec3 manually. A notebook demonstrating the spectral extraction capabilities of the JWST calibration pipeline for MIRI LRS is available in this repository. | Updated Operations Pipeline The pipeline was updated in May 2023 to default to apertures centered on the nominal position of the level 3 spectrum in the aperture. This change is fully in operations, data have been reprocessed. |