JWST MIRI MRS Pipeline Caveats

Features and potential caveats specific to MIRI MRS data processing in the JWST Science Calibration Pipeline are described in this article.

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Caveats specific to MIRI MRS data processing in the JWST Science Calibration Pipeline are described below. This article 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 any known issues that users should be aware of for their science.

An example Jupyter notebook that users can use to reprocess data with the pipeline is available on GitHub



MIRI MRS pipeline

Astrometric calibration

The astrometric alignment of the 12 MRS bands is generally good to better than 0.1 arcsec.  However, there are some uncorrected higher-order scale effects and linear offsets peculiar to individual slices that are not presently accounted for in the spatial distortion reference files used to assign world coordinates to the dispersed MRS spectral data.  This is expected to have little effect on the majority of science programs, other than representing a slight broadening to the reconstructed point spread function.  However, the suboptimal alignment can limit the performance and repeatability of the MRS for extremely high-SNR studies or those that rely critically on measuring the size and shape of the point spread function.  These calibrations will be improved in Cycle 1.

Wavelength calibration

Wavelength calibration of the MIRI MRS data is generally accurate to within about 1 spectral resolution element (~ 100 km/s).  Improved calibration accuracy will be provided throughout Cycle 1 as more calibration data are obtained.

Flux calibration

Flux calibration of the MIRI MRS data is presently based on observation of a single standard star during commissioning.  As such, the present calibration (particularly longward of about 20 microns) will need to be improved throughout Cycle 1 as more calibration data are obtained.

Source type

This step determines whether the pipeline should consider the observation to be a point source or an extended source, which affects whether 1d spectral extraction is later done from the entire FOV or using aperture photometry around a given point.

  • If EXTENDED=YES is selected in the APT target description, it will choose Extended. 
  • If EXTENDED=NO in APT, it will choose Point. 
  • If EXTENDED=UNKNOWN, it will try to use the dither pattern to figure out what the likely source type is.  A point source optimized dither pattern will result in Point, otherwise it will be Extended.  
  • This step can be manually overridden to specify either case.
  • Time Series observations will require a separate optimal reduction process. For TSO observations the pipeline processing ends before the cube building and spectral extraction steps.  (See: JWST Time Series Observations Pipeline Caveats

Background subtraction

See also:  software documentation (external links): Background Subtraction, Master Background Subtraction

The MIRI MRS sees a significant component of background light at long wavelengths, both from reflected zodiacal light and from JWST thermal emission (particularly in Channel 4).  As such, it is important to subtract this background signal in order to measure the astrophysical signal of interest.  There are presently three locations at which this can happen in the pipeline:

  1. Background Subtraction (Spec2): This performs pixel-by-pixel background subtraction in which one exposure can be directly subtracted from another, removing a background signal but introducing noise from both the science and background exposures into the final image. This approach is not used by the pipeline unless manually overridden to do so, and analysis of commissioning data shows that it is not necessary in general.
  2. Master Background Subtraction (Spec3): This subtracts the background signal from 2- D data using a 1-D master background.  Using all x1d products (produced for individual exposures in spec2, although they could be created in other ways too) provided in the spec3 association file, it obtains the 1-D background spectrum from the  BACKGROUND extension and projects this spectrum to the entire 2-D detector array. This broadcast array is then subtracted from the individual 2-D science frames with little to no degradation of the SNR (since it uses a 1d spectral model produced from the sigma-clipped combination of many detector pixels rather than the values of those pixels themselves).
    1. This step does not run by default unless there is a dedicated background observation properly linked to the science observations.  Science data cubes for programs that did not include dedicated backgrounds will not be background-subtracted unless users create and provided a 1d background spectrum to the Master Background routine.
    2. If data are designated as linked background observations, then extract_1d will use the entire field-of-view as the extraction region. The Master Background step recognizes the type of background exposure and uses the appropriate x1d data product to produce the master background. 
  3. Extract1D
    1. (Spec2): If processing any target indicated as a point source, the extract_1d step will compute a background spectrum using a sigma-clipped algorithm in an annulus surrounding the location of the source.  By default, this background spectrum will be subtracted from the 1-D science spectrum extracted from the circular aperture centered on the source (accounting for the effective area of that aperture).
    2. (Spec3): As in Spec2, the process of spectral extraction from a 3-D data cube for point sources by default applies a background subtraction from an annular region surrounding a point source.  Even in cases for which Master Background subtraction was already done, the point source aperture correction factor is tied to the expectation that the annular background subtraction has also been performed.

Note that there is a bug in the data quality arrays during spectral extraction that causes the background model produced by the Master Background step to jump discontinuously between individual MRS bands. This has been fixed in the main pipeline, however data processed with version 1.5.3 or earlier of the JWST pipeline does not yet have this correction.

Spectral extraction

For extended sources spectral extraction sums the flux within the entire MRS field of view.  Since the field of view is different for each MRS spectral band (and increases substantially for longer-wavelength channels) the summation region will thus be different as well.  Depending on the source geometry within the FOV, the extracted 1d spectrum may thus be discontinuous between bands as it corresponds to a different astrophysical area.

For Point sources spectral extraction sums the flux within a conical aperture at the target header coordinates.  This conical aperture grows with wavelength to enclose roughly the same total fraction of the PSF, which increases in size by a factor of 5 over the MRS spectral range.  Likewise, the annular background subtraction region also grows with wavelength.  There is currently a known bug in this extraction in that the header coordinates of the source do not account for proper motion and give only the RA/DEC in the epoch provided to APT in the original proposal.  It does not account for any proper motion of the source with respect to this epoch.  Likewise, the global WCS of JWST data products can often be incorrect by a few tenths of an arcsec, compounding issues with the extraction location in the cubes.  Sources may therefore need to be re-extracted using adjusted coordinates.

Cube building

See also:  software documentation (external link): Cube Building

The cube_build step combines the individual 2D IFU slice images and creates a 3D spectral cube. The IFU cubes are by default constructed with north pointing up and east to the left. Cube building can be done using either 3d drizzle an exponential modified Shepard's method of weighting (emsm), however 3d drizzle is recommended. The current pipeline default is set to use the 3d drizzle algorithm.

  • Set WEIGHTING=DRIZZLE to use 3d drizzle
  • Set WEIGHTING=emsm to use the exponential modified Shepard's method

The FOV, slice width, number of slices, and plate scales are different for each channel. The cube_build step will use reference files to determine the proper output sampling scale as a function of wavelength. If data from a single channel or band is combined the resulting IFU Cube will have a linearly-spaced wavelength dimension. If the user combines data covering several channels into a single data cube, the output scale corresponds to the channel with the smallest scale and the resulting IFU cube will have a non-linear wavelength dimension designed to reasonably sample the spectral line spread function (LSF) as a function of wavelength.

Cube building can be used to combine all integrations per band, channel, or combine all channels together. Association files are used to identify the desired input files for the cube building. JWebbinar 5 (MIRI and NIRSpec IFU ) gives detailed examples of how to process MIRI MRS data with the different cube building options.:

  1. 12 per-band cubes: Create a composite data cube from all dithered data for each of the 12 MRS bands individually (this was the default pre-flight).
  2. Channel Configuration: The pipeline can also produce per-channel data cubes where all bands are combined into a single channel  (e.g., 1A, 1B, and 1C are combined into a single Channel 1 cube).  This is the default at the present time.
  3. All-wavelength Cube: The pipeline can be configured to combine all data into a single cube spanning the wavelength range of the data taken. If combining data from all four channels, this single cube will have a wavelength range of 5-28 microns.  This can be useful to get an overall view of a given scene, but is extremely computationally demanding to produce, and will contain artifacts at long wavelengths resulting from sampling the output data cubes on scales far below the native detector/slicer sampling.

    spec3.cube_build.output_type = 'multi'

Cube building caveats

  • Moving targets are currently not combined correctly as the motion between frames is not taken into account in cube_build. This will be addressed early in Cycle 1.
  • All-wavelength cubes are created with an output scale corresponding to the sampling at the shortest wavelength. This will result in artifacts in the cube at long wavelengths where the sampling of the data is significantly smaller than the native sampling.
  • The JWST IFUs are significantly undersampled by the slicing optics, leading to a recommendation that users dither in order to help recover spatial information lost by the native sampling.  However, this cannot be entirely fixed using a small number of dither points, and reconstructing a data cube from undersampling observations thus results in an apparent spectral 'ringing' in the spectrum due to resampling noise as the spectral trace crosses detector pixel boundaries. This is inherent to the drizzle and cube building process and there is currently no correction in the pipeline for this.  Further documentation of this effect is forthcoming, but the 'ringing' can be mitigated by using spectral extraction apertures comparable to the PSF FWHM instead of using the spectra of individual spaxels. 



Managing detector features

MIRI MRS has instrument specific features that can be corrected for with the pipeline. These corrections are actively under development. See MIRI Features and Caveats for detailed descriptions of detector features.

Detector1 

There is the potential for artifacts to be introduced in flight from column/row pull up/down effects produced by extremely bright sources on the detector.  Currently, detector artifacts can be best corrected by using dedicated background exposures. This effect is still under study and additional calibration is under development as results from Cycle 1 calibration are assessed.

Scattered light correction

See also:  software documentation (external link): Stray Light

Scattered light is a manifestation of the MIRI cruciform diffraction at the pixel gap and reflection at the anti-reflection coating. As such the 'straylight'  is an integral part of the MRS PSF.   Because neighboring slices on the detector do not correlate to neighboring pixels on the sky, the diffraction spikes will appear in the spectral cubes as faint sources away from the observed point source. The signal from the scattered light linked to the pixel-gap-diffraction is clearly defined in the spatial direction (detector horizontal direction) and automatically corrected in the pipeline.  While this correction does a reasonable job of removing the horizontal 'band' type features and reducing the amplitude of the small 'spike' features, some spikes will still remain in the data.  Users should be cautious about the existence of such spikes when performing PSF subtraction and/or looking for faint companions within the field of view.

Figure 1. Pipeline correction for spatial scattered light

 3-D cubes of a point source are shown before and after the pipeline correction. The scattered light manifests as horizontal bars across the spatial cube. 

The scattered light in the spectral direction is still under investigation and and no correction is currently available.  Likewise, the performance of the spatial correction degrades in the vicinity of extremely bright emission lines, and can lead to artifacts in adjacent regions on the detector.

Fringe correction

See also:  software documentation (external link): Residual Fringe

There are two correction steps in the pipeline, FringeStep and ResidualFringeStep.

  • FringeStep divides the detector image by a static fringe flat.  The fringe flats were derived by fitting a physical model of detector fringes to observations of spatially extended sources.  Fringe flats largely remove detector fringes from MRS data, although residuals remain.  For point sources and spatially semi-extended sources, the fringe pattern depends on the distance from the PSF peak (to sub-pixel accuracy).  Point sources will always show residual fringes after fringe-flat correction (which are generally smallest at PSF peak).  At present the static fringe flat correction is performing better for some wavelengths than others, and will be improved throughout Cycle 1.
  •  ResidualFringeStep fits sinusoids to detector-level data and removes them.  Care is taken not to accidentally remove physical features.  In particular, the fringe frequency is constrained to values known to match the physics of the MRS, governed by the known optical thickness of the detectors and the dichroic.  The number of fringe components to be removed is governed by Bayesian evidence: the algorithm will continue to remove fringe components for as long as there's evidence for it.  This residual fringe correction can be applied to either 2d calibrated detector data or 1d extracted spectra.  There is currently a bug in the code however such that it does not run properly on data from the MIRIFULONG detector (Ch3 + 4).

Improved fringe flats and more sophisticated fringe-removal techniques are under development throughout Cycle 1.

Figure 2. Fringe correction

Channel 2 spectrum of a point source without fringe correction is shown in black. The FringeStep in the pipeline applies the fringe flat and results in the corrected orange spectrum. The ResidualFringeStep (RFC) can be run to apply an additional correction shown in blue.

 





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