NIRSpec Detector Performance
The JWST NIRSpec detectors, NRS1 and NRS2, have been tested to characterize read noise, detector gain, dark current, non-linearity, saturation, quantum efficiency, persistence, and inter-pixel capacitance.
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The NIRSpec detectors (sensor chip assemblies; SCAs) have been optimized to balance a variety of performance metrics such as read noise, dark current, and saturation well depth.
The following sections present characteristics of the 2 NIRSpec detectors, called NRS1 and NRS2, in the data processing and pipeline systems. The presented SCA values are relevant at the operating temperature of 42.8 K and are mostly based on commissioning data, with some measurements still stemming from ground tests as they cannot be repeated on-orbit. Ground testing at detector level was performed at the Detector Characterization Lab at NASA Goddard Space Flight Center in 2014, and tests in a flight-like configuration at instrument level were carried out int the December 2015 to July 2017 timeframe.
The detector gain is the ratio of electrons to detector count (typically expressed as data numbers, or DN). This number, as a function of detector pixel, is used primarily in the data processing pipeline as part of the calculation of the shot noise, or Poisson noise, contribution to the total noise per pixel in an integration. Pixel-to-pixel gain maps for the 2 SCAs were constructed from data obtained during the detector characterization ground test campaign, using the classical photon transfer curve technique (Janesick, J. et al.,1987). The average gain values for both SCAs in full frame readout is near unity (Table 1). The gain map for NRS1 (Figure 1, Sirianni 2017) exhibits a very uniform distribution, with a small area of slightly lower values at the lower center caused by a known "epoxy void" effect. The map for NRS2 (Figure 1) is also uniform, though with a slight gradient at the ~5% level.
There is a different gain setting for subarray exposures which will provide an improved dynamic range for bright sources. The conversion gain is about a factor of 1.43 higher compared to full frame data for both SCAs. This was confirmed during OTIS testing.
All infrared detectors exhibit some level of dark signal. By virtue of the low operating temperatures, NIRSpec's detectors show extremely low dark current values, with the observed dark signal being dominated by multiplexer glow (Regan & Bergeron 2020). The dark signal measured in orbit is slightly higher than measured during ground testing, probably due to the cosmic ray environment at L2. Nevertheless, the median dark signal for both the NRS1 and NRS2 NIRSpec detectors are well within the performance requirement of <0.01 e–/s. Figure 2 and 3 present the dark signal images for the NIRSpec detectors as measured during commissioning in traditional and IRS2 readout mode, respectively (Birkmann, S.M. et al., 2022). A small region on detector NRS1 at the center bottom has an "epoxy void" that is apparent as a region of lower dark current (also seen in Figure 1). The dark signal is higher for subarrays due to the shorter frame times and thus more reads per unit time, which results in more multiplexer glow observed.
Detector read noise
Detector readout noise is measured by computing the correlated double sample (CDS) of many adjacent detector frames and getting the standard deviation for each pixel after performing reference pixel / IRS2 corrections. Using the CDS eliminates the impact of the kTC noise that is always present and results in a changing offset/pedestal for each integration. Using the slope of a ramp after fitting also eliminates the kTC noise. The CDS noise is sqrt(2) times the readout noise for a given pixel. Histograms of the CDS noise for the 2 NIRSpec detectors for traditional full frame mode and IRS2 readout mode as measured during commissioning are presented in Figures 4 and 5 below (Birkmann, S.M. et al., 2022). They are well in line (within ~1%) with the CDS noise measured during ground test campaigns.
Detector total noise
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Table 1. Effective total noise of the NIRSpec detectors
|Total Noise† (e-)|
|Readout mode||Detector||Teff ~950 s||Teff ~1700 s||Teff ~ 3560 s|
† As measured on-orbit during commissioning, includes effects of cosmic rays after mitigation
Table note: Median effective total noise of the NIRSpec detectors for the different readout modes.
All of JWST's near-infrared detectors exhibit non-linear response, as illustrated below. The thin straight line represents linear flux, the curves present the deviation from this linearity for detector operation at 3 different temperatures as measured on ground. Correction for this detector non-linearity performance is taken into account in the data reduction pipeline.
Charge cannot accumulate indefinitely in a single integration; there is a maximum level beyond which the signal saturates or can no longer be reliably corrected for non-linearity. Given the gain values discussed above, the saturation level for most pixels in the NIRSpec SCAs is set by the limit of the analog-to-digital converter: 216−1, or 65,535 DN. Counts at this level must be flagged and rejected by the data processing pipeline in order to derive the correct count rate (a minimum of 2 unsaturated groups per integration are necessary to recover the count rate). In practice, the saturation thresholds applied by the pipeline are actually below this level, and vary from pixel to pixel, in order to reject data in which the nonlinearity is too large to be corrected accurately. The average saturation level is 61,000–64,000 DN. The average detector well depth is the saturation minus the detector bias level: 55,100 and 60,400 electrons for the NRS1 and NRS2 detectors, respectively (Birkmann 2016).
Unlike with a CCD, there is no "bleeding". However, charge diffusion can impact neighboring pixels. This is also known as the "brighter-fatter" effect, see e.g., Plazas et al. 2018. Also, a highly saturated region could result in persistence that affects subsequent exposures at the same detector position. For example, in the case of solar system observations, dither patterns and target orientation should be planned such that a faint satellite does not fall onto a region that was illuminated by the planet in a previous exposure.
Detector quantum efficiency (QE)
The detector quantum efficiency (QE) is a measure of how efficient a detector is at recording incoming flux signal. NIRSpec detectors were extensively measured for QE at multiple wavelengths during detector system tests carried out in the Detector Characterization Lab (DCL) at NASA Goddard Space Flight Center. The illustration below shows relative QE for NIRSpec detector NRS2 at 3 operating temperatures. The gray region represents uncertainty in the measurements, and the orange line presents the performance requirements on the NIRSpec detectors. The NIRSpec NRS1 detector shows a similar QE pattern and amplitude.
JWST's near-infrared detectors can retain vestiges of earlier exposures; this effect is called persistence. The most vulnerable situation is when a very faint object is observed not long after something very bright. At the present time, the JWST scheduling system does not give an observer knowledge of what may occur in a preceding exposure, in part because that is not always predictable. Figure 5 shows how a persistence signal drops by a factor of ~200 after one hour. The initial persistence level is about 1 e–/s/pix, and, therefore, it is anticipated that the worst effects will be seen from self-persistence within a program.
Detector inter-pixel capacitance (IPC)
Inter-pixel capacitance (IPC) is a type of capacitive coupling between neighboring pixels (see Moore et al. 2006). This phenomenon is commonly confused with charge diffusion, which involves migration of charge carriers to adjacent pixel cells which also happens at high signal levels (at or beyond full well). Instead, IPC arises from the interaction of electric fields that alter the measured voltages.
In its simplest form, this effect can be parameterized as a convolution kernel described as a 3 × 3 matrix with values totaling unity. Measurements for NIRSpec detectors show values consistent with an assumption of symmetric coupling: the kernel will have values of nearly zero in the corners, some value α in the left, right, top, and bottom positions, and the remaining 1−4α in the central pixel (α is a coupling coefficient, see Moore et al. 2006). In the NIRSpec SCAs, α ranges from 0.005 to 0.0067. In other words, approximately 2.5%–3% of the total flux measured from a given pixel gets redistributed between its 4 adjacent neighbors.
Uncorrected IPC can affect the spatially measured Poisson noise, which will result in overestimates of the conversion gain and reported quantum efficiencies. The tables below shows the IPC kernels for the NRS1 and NRS2 detectors of NIRSpec from in-orbit determination during commissioning. This correction is currently not applied in the default data processing pipeline.
The vast majority of pixels in the NIRSpec detectors are considered operable. Non-operable pixels are for example those which do not respond to light or exhibit a large dark signal and thus noise. The number of bad/non-operable pixels in the NIRSpec detectors as measured during commissioning is summarized in the table below.
Table 2. Non-operable pixels in the NIRSpec detectors
|Bad pixel type||NRS1||NRS2||Comment|
|DEAD||7757||3938||Does not respond to light|
|OPEN||294||252||Very low response, signal mostly ends up in adjacent neighbors (see below)|
Pixel impacted by OPEN neighbor (additional signal)
Low response to light
Large dark signal that is non-linear (RC-like ramp)
Hot (dark signal > 1 e-/s) pixel
|Total bad pixels||16948||8275|
Total number of non-operable pixels
|Operable pixel fraction||99.59%||99.80%|
Fraction of operable pixels in the 2040 x 2040 pixel active area
Table note: The number of non-operable pixels of different kinds in the NIRSpec detectors. Note that the total number of bad pixels can be less than the sum, as some bad pixels belong to several categories. The fraction of operable pixels is for the 2040 x 2040 pixel active area of the detectors. (see Böker et al. 2022, in press)
Birkmann, S.M. et al. 2022 Proc. SPIE 12180
The in-flight noise performance of the JWST/NIRSpec detector system
Birkmann, S. 2016 ESA-JWST-SCI-NRS-TN-2016-004
NIRSpec Saturation and Non-Linearity Correction Reference Files for Build 7
Böker, T., Beck, T.L., Birkmann, S. et al. 2022, in press
In-orbit Performance of the Near-Infrared Spectrograph NIRSpec on the James Webb Space Telescope
Janesick, J. et al. 1987 Optical Engineering, 26(10), 261072
Charge-Coupled-Device Charge-Collection Efficiency And The Photon-Transfer Technique
Quantum efficiency overestimation and deterministic cross talk resulting from interpixel capacitance
Plazas, A.A., et al. 2018 PASP, Vol 130, Number 988
Laboratory Measurement of the Brighter-fatter Effect in an H2RG Infrared Detector
Rauscher, B.J. et al. 2014 PASP, Vol 126, p 739
New and Better Detectors for the JWST Near-Infrared Spectrograph
Regan, M. W. and Bergeron, L. E. 2020 Journal of Astronomical Telescopes, Instruments, and Systems, Volume 6, id. 016001
Zero dark current in H2RG detectors: it is all multiplexer glow
Sirianni, M. 2016 ESA-JWST-SCI-NRS-TN-2016-013
NIRSpec IPC Kernerl Reference Files for Build 7
Sirianni, M. 2017 ESA-JWST-SCI-NRS-TN-2016-012
NIRSpec Gain and Readnoise Reference Files for Build 7