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 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.
As of JWST pipeline v2.0.0 (and later versions) there are multiple 1/f cleaning options in the pipeline provided by the optional clean_flicker_noise step available in both calwebb_detector1 and calwebb_spec2. The BOTS pipeline notebook shows how this step can be run as part of pipeline processing. Further information on 1/f noise can be found on the main NIRSpec Known Issues and 1/f Noise pages.
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
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 (3–5 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.
| Symptoms | Cause | Workaround | Fix build | Mitigation 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. | The JWST pipeline includes an optional step in calwebb_detector1, called clean_flicker_noise, with multiple methods for cleaning 1/f noise in ramps or rate images as of jwst 1.16.0 (and later versions). This step is also available in the calwebb_spec2 pipeline as of jwst 2.0.0 (and later versions), replacing the previously available nsclean step, which had been available since jwst 1.13.0 and implemented a version of the NSClean script developed by B. Rauscher (B. Rauscher 2023). As of jwst 2.0.0 (and later versions) a specialized option, background_method = median_image, has been added to clean_flicker_noise in order to better model and preserve source flux in TSO data while cleaning 1/f. The JWST pipeline notebook for BOTS provides examples of how to use the clean_flicker_noise when reprocessing data. Several additional community tools that mitigate 1/f noise are also available. More information on the clean_flicker_noise step 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. |
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