NIRSpec BOTS Known Issues

Known issues specific to NIRSpec BOTS (bright object time series) spectroscopic 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. Users should also refer to the Known Issues with JWST Data page for characteristics and caveats that are common to all instruments in time-series (TSO) mode. 

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 NIRSpec BOTS Calibration Status for an overview of the current photometric and wavelength calibration accuracy of NIRSpec BOTS data products.



Artifacts

Information on NIRSpec instrument artifacts are found on the main NIRSpec Known Issues article.



Pipeline notes

Early in the mission, our understanding of the observatory performance is evolving quite rapidly and changes to calibration procedures are expected. Spectrophotometry obtained using NIRSpec/BOTS during commissioning revealed that the instrument performance is close to photon and read-noise limited, in part due to the excellent stability of the observatory (Espinoza et al., 2022).

However, at this moment, there are some caveats in the pipeline processing that observers should be aware of that are summarized below.

Stage 1 processing

1/f noise

See also: JWST Time-Series Observations Noise Sources

The NIRSpec near-infrared HgCdTe detectors show spatially correlated noise, known as 1/f noise, that is introduced by the detector readout system (Schlawin et al., 2020; Moseley et al., 2010). One of the features of this noise is an apparent horizontal striping in the detectors as explained in the NIRSpec Known Issues article and in JWST Time-Series Observations Noise Sources. 1/f noise has a considerable impact on the light curve scatter for time-series observations if it is not accounted for. It can be partially corrected.

One possible way of performing the 1/f correction is by carefully selecting background pixels and subtracting those from each pixel in each column. This methodology is not perfect because it does not account for the intra-column component of 1/f noise nor does it correct for all the inter-column covariance between pixels. One way to take this covariance into account is to include it in the spectral extraction algorithm itself, as suggested by Schlawin et al. (2020, Sections 4.3.3. and 4.3.4). Optimal methods for extracting and/or correcting 2-D spectra considering 1/f noise are under investigation.

The user may consider experimenting with a recently published algorithm for NIRSpec called NSClean by B. Rauscher (2023).

Saturation

See also: JWST Time-Series Observations TSO Saturation

In Birkmann et al. (2022), the authors plot the brightness limits for the available filter and disperser combinations (Figure 1) in J-band Vega magnitudes, calculated using the default subarrays, that is, SUB512 for PRISM/CLEAR and SUB2048 for all gratings. Host stars of known transiting exoplanets, as of September 2021, are over-plotted in gray, with a few labeled by name. If a host star lies beneath the curve for a given configuration, that target can be observed without any saturation in the spectrum. It is clear that most of these targets can be observed with JWST NIRSpec even with the PRISM configuration and only a handful are out of reach for the high-resolution gratings. It is still possible to observe host stars that fall above the curves, but with partial saturation in some wavelength ranges. An uncertainty of 20% should be considered when using brightness limits indicated in Figure 1.

Figure 1. Brightness limits for available filter and disperser combinations

Click on the figure for a larger view.

An uncertainty of 20% should be considered when using brightness limits indicated in this figure. © Birkman et al., 2022

For proposal preparation, observers are highly encouraged to use the official JWST Exposure Time Calculator (with updated in-flight sensitivities starting with ETC 2.0) to assess the number of groups before the saturation/brightness limits for their targets. Preliminary results from observatory commissioning indicate that system throughput is higher than pre-mission expectations, by amounts that vary with wavelength. This might affect the saturation levels used for the NIRSpec wide aperture target acquisition (WATA). For this reason, observers are encouraged to read the article on NIRSpec WATA, especially the note on saturation. 

Quantum yield

        See also: JWST Time-Series Observations Noise Sources

The HgCdTe detectors employed in NIRSpec are known to occasionally generate more than a single electron-hole pair for incident photons having energies sufficiently above the band gap of the device. Jakobsen (2022) created simple statistical models for the additional noise added to the extracted detector electron signal due to the quantum yield effect. Using pre-flight quantum yield estimates, they demonstrated that photon-noise error bars at 1.5 μm are likely underestimated by 10%–30%; the same effect implies an underestimation of those error bars of 30%–50% at 0.6 μm. The actual magnitude and wavelength dependence of this enhancement is currently under investigation.

Observed TSO systematic effects

The NIRSpec focal plane uses 2 individual detectors, also called sensor chip arrays (SCAs). The SCAs (designated as NRS1 and NRS2) are IR hybrid arrays with HgCdTe used for light detection and a silicon integrated circuit for the readout. More information can be found in the NIRSpec Detectors article. 

From a commissioning study performed on HAT-P-14 b (Espinoza et al. 2022) using NIRSpec/BOTS G395H/F290LP, the NRS1 transit light curve clearly shows a more pronounced exposure-long slope than that for the NRS2 (about ~140 ppm per hour for NRS1, compared to 40 ppm per hour for NRS2). At the white light curve level, these systematic slopes vary with time over the course of a given time-series observation, with steeper slopes pre-transit compared to the post-transit slopes. For NRS1, there appears to be a correlation between the systematic slope and the host star magnitude, as well as the systematic slope and the number of groups per integration for the visit-long slope, pre-transit, and post-transit slopes. For NRS2, the visit-long slopes are roughly zero. For the spectroscopic light curves, the NRS1 and NRS2 detectors reveal different wavelength-dependent (chromatic) systematic slopes. For NRS1, slopes are strongest between ~3–3.4 μm (with a peak at ~3.2μm). NRS2 does not show any apparent chromaticity in the systematic slopes. It is possible that this effect is due to some underlying detector level effect, and this issue is currently under investigation.

Detector timestamp differences 

Differences in the timestamps, ranging from 0 to 12 seconds, for the NRS1 and NRS2 detectors have been noted for time-series observations for programs observed prior to March 2025. An initial study concluded that syncing both detectors could resolve the offset issue for observations with time stamp differences. An instrument commanding update was released in March 2025 to sync NRS1 and NRS2 at the beginning of each observation. Also, note that for some TSOs, the time stamp difference increases over the course of the observation. An investigation is currently underway on all TSOs to identify observations having a time stamp difference increase and determine their origin.

Light curve scatter

From the commissioning study performed on HAT-P-14 b (Espinoza et al. 2022) using NIRSpec BOTS G395H/F290LP (35 um), at the native resolution of the instrument, the JWST pipeline precisely predicts the noise levels observed on the out-of-transit light curves in the NRS1 detector. However, there appears to be a slight but significant extra scatter of about 5% in the actual data when compared with the pipeline products for NRS2. The source of this discrepancy is currently under investigation. 

  


Summary of common issues and workarounds

The sections above provide details on each of the known issues affecting NIRSpec BOTS data; the table below summarize 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.


SymptomsCauseWorkaroundFix buildMitigation Plan
NS-BOTS03: There is vertical striping across the NIRSpec BOTS rate images (2-D spectra), which appears as negative and/or surplus flux in extracted 1-D spectra (typically with an irregular wavelength-dependent undulation).Correlated noise from low level detector thermal instabilities (1/f noise) is seen as vertical banding in 2-D count rate images, particularly in exposures of the NRS2 detector.

Run NSClean script developed by B. Rauscher on count rate images, using an appropriate mask. Several additional community tools that mitigate 1/f noise are also available.

NSClean was implemented in the pipeline and is available as a non-default option (jwst 1.13.0 and later versions).  Additional 1/f cleaning options in the pipeline have been included in jwst 1.16.0 (and later versions), which can now be run on group data in calwebb_detector1 using the clean_flicker_noise step.

A dedicated example for how to the nsclean step in the pipeline can be found in this JDAT notebook. The JWST pipeline notebook for BOTS also provides examples of how to use the  clean_flicker_noise and nsclean steps when reprocessing data.  More information on these steps can be found here: 1/f noise.

N/A

Updated issue

Investigations are underway to explore whether 1/f cleaning can be turned on by default in the pipeline.

NS-BOTS04: The extracted 1-D spectrum ("x1d" product) has spurious absorption features, typically one pixel wide.

Pixels marked as "DO_NOT_USE" in the reference data are not included in 1-D extracted spectrum.

Use the Science Calibration Pipeline software (jwst 1.11.0 onwards) to estimate the value for each "DO_NOT_USE" pixel from neighboring 2-D profiles before extracting the 1-D spectrum by running the pixel_replace step. Testing has shown improvements in many cases, but this is currently disabled by default.  

N/A

Updated issue

The team is investigating using the pixel_replace step by default for BOTS data.

NS-BOTS05: Artificial ~10% deep absorption feature between about 0.97 and 1.02 µm in NIRSpec G140M/F070LP spectra when observed through the S1600A1 aperture.

The lamp flat field images, which are used to create the "sflat" reference files, for the S1600A1 slit are contaminated by the zero-order image, which causes a large positive feature in the "sflat" correction image in the lower part of the aperture.

Use only the spectra extracted from the upper dither positions in the affected wavelength range.

 N/A

Created issue

Investigate feasibility of editing the "sflat" reference file to remove the contamination, and/or flagging affected pixels as DO_NOT_USE.

SymptomsCauseWorkaroundFix BuildMitigation Plan
NS-BOTS01: The shape of spectra taken with the SUB512, SUB512S, or SUB32 subarrays exhibits unexpected features and wavelength-dependent flux discrepancies of 10% or more. This causes time-series observations (TSO) light curve scatter to increase by orders of magnitude larger than expected.

Some subarrays have no reference pixels, which means bias drifts are not corrected.

Rerun calwebb_detector 1 starting from the "_uncal" files. Before the linearity step, identify non-illuminated pixels in the detector and estimate their median value; this will provide an estimate of the detector pedestal level on each group. Remove this value from each group, and then run the remaining calwebb_detector1 steps. 

 9.3

Updated Operations Pipeline

The reference pixel correction was modified to use non-illuminated pixels in the columns at the left and right edges of these subarrays. This was implemented in the Operations Pipeline on August 24, 2023.


NS-BOTS02: Large number of outlier pixels are identified in the jump step, which leads to lower SNR of the "rateints" products (slope images) per integration.The jump step default threshold, in combination with the current reference file uncertainties, results in too many pixels being flagged as cosmic rays.

Rerun the jump step with the a rejection_threshold value > 10 (default is 4.0).

Resolved issue

Pipeline version jwst 1.18.0 (and later versions) fixed a bug in the jump step that was causing long BOTS exposures use an incorrect jump detection method.  This change amongst several improvements over the preceding pipeline versions has reduced the number of unnecessary jump detections.

NS-BOTS06: Fluxes are too low at the red and blue wavelength extremes of extracted 1-D spectra for M- and H-grating observations

The default extract_1d extraction uses a rectangular extraction box that does not follow the curved trace of M- and H-grating data in "calints" files.  This causes the 1-D extraction to miss some of the flux at the red and blue wavelength extremes for M-grating data and can miss the red and blue ends of the H-grating traces entirely.

Reprocess BOTS data with jwst 1.18.0 (or later versions), which extracts data using a curved trace boxcar extraction.  The trace is built using the WCS model and expected source position in the slit.

Additionally a custom curved trace can be used for 1-D extraction by providing extract_1d.override_extract1d a modified "extract_1d" parameter reference file that provides a list of polynomial coefficients that define the trace via the src_coeff keyword (see the extract_1d step description for more details).

Alternatively see the calwebb_spec2 workaround notebook for BOTS data from JWebbinar 29 for an example of a custom extraction of BOTS data.

Resolved issue

As of  jwst 1.18.0 (or later versions), a curved trace boxcar extraction is used by default for BOTS data, where the instrument WCS model and expected source positions are used to calculate a curved source trace.  These updates will be included in the operational pipeline build to be released in May 2025. Reprocessing of affected data typically takes 2–4 weeks after the update.

 


References

Birkmann, S. M., et al., 2022, A&A, 661A, 83B
The Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope. IV. Capabilities and predicted performance for exoplanet characterization

Espinoza, N., et al. 2022, PASP, 135, 018002
Spectroscopic Time-series Performance of JWST/NIRSpec from Commissioning Observations 
ADS

Jakobsen, P., 2022, ESA Instrument Report, ESA-JWST-SCI-NRS-TN-2022-003 
(PDF)

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., 2023, submitted
NSClean: An Algorithm for Removing Correlated Noise from JWST NIRSpec Images

Schlawin, E., et al. 2020, AJ 160, 231S
JWST Noise Floor. I. Random Error Sources in JWST NIRCam Time Series
ADS




Notable updates
  •  
    Updated issues NS-BOTS03 and NS-BOTS04 language to be consistent with other NIRSpec issues. 

    • Added text about systematic slopes investigations currently underway.
    • Added section on detector timestamp differences.
    • Moved issues NS-BOTS02 and NS-BOTS06 to the list of retired issues.

  •  
    Resolved issue NS-BOTS06, and updated its workaround and mitigation plan.

  •  
    • Moved retired issue NS-BOTS01 to a separate expandable table.
    • Updated issue NS-BOTS06 mitigation plan.

  •  
    Updated mitigation plan for issue NS-BOTS03.

  •  
    Created issue NS-BOTS06: Fluxes are too low at the red and blue wavelength extremes of extracted 1-D spectra for M- and H-grating observations.

  •  
    Updated issues NS-BOTS02, NS-BOTS03, NS-BOTS04.
Originally published