NIRCam Short Wavelength Grism Time Series Observing Strategies
This page describes strategies for taking advantage of the improved bright source limits for the new (in Cycle 4) short wavelength (SW) grism capability in the NIRCam grism time-series observing mode, while balancing that with the higher throughput in the long wavelength channel and the increased data volume produced in this new mode (which uses all 5 detectors in module A rather than 3).
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See also: NIRCam Grism Time Series, NIRCam Short Wavelength Grism Time Series, NIRCam Multistripe Subarrays, NIRCam Grism Time-Series APT Template
The use of the Dispersed Hartmann Sensor (DHS) grisms in NIRCam's short wavelength channel is offered on a shared-risk basis due to limited time to obtain on-sky calibration observations prior to Cycle 4, and the use of new subarray readout operations. The capability is enabled by setting SW Channel Mode = GRISM in the NIRCam Grism Time Series template, starting in Cycle 4 (APT 2024.5). Furthermore, additional readout patterns tailored to DHS observations will become available only after Cycle 4 proposals are due, so accepted programs will need to be re-evaluated prior to being declared ready for flight. The new patterns will provide additional flexibility for balancing integration time and data volume.
Background regarding this new capability
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The NIRCam grism time-series observing mode now includes the capability to collect slitless spectra in the short wavelength (SW) and long wavelength (LW) channels simultaneously, enhancing the mode to obtain time-series spectra spanning 0.7–5.0 μm, depending on the blocking filters selected in the two channels. The SW Dispersed Hartmann Sensor (DHS) grisms produce multiple spectra from the target spread evenly in the cross-dispersion direction. This new capability is described in detail in the article NIRCam Short Wavelength Grism Time Series.
To provide short frame times (and improved bright limits), new subarrays have been implemented that consist of multiple substripes (groups of rows) that exclude the many rows of blank pixels between the DHS spectra in the SW channel. SW subarrays that sample 1, 2 or 4 of the DHS spectra per SW detector (corresponding to 2, 4 or 8 DHS spectra, respectively) are available.
Available subarrays
The subarrays available when DHS grism spectra are being collected in the SW channel have names that indicate the number of detector rows in the subarray, the number of substripes the subarray is divided into, and the number of SW DHS spectra that are collected. In APT they are SUB40S1_2-SPECTRA, SUB80S2_4-SPECTRA, SUB160S4_8-SPECTRA, and SUB256S4_8-SPECTRA (see Table 1 below and NIRCam Short Wavelength Grism Time Series). In this article, these names will usually be shortened to SUB40S1, SUB80S2, SUB160S4 and SUB256S4, respectively, without loss of uniquenes. Currently the ETC uses a different naming convention, but the correspondence to the APT names is fairly intuitive: SUB40STRIPE1_DHS, SUB80STRIPE2_DHS, SUB160STRIPE4_DHS, and SUB256STRIPE4_DHS. Additional detail about multistripe subarrays is provided in NIRCam Multistripe Subarrays.
Challenges
The DHS grism sub-apertures only transmit 25% of the light collected by the JWST primary mirror, while the LW grism sees the entire collecting area, and the DHS produces multiple SW spectra while the LW grism produces a single spectrum. As a result, the count rates in the two channels are significantly imbalanced: SNR in the SW channel (even when all of the DHS spectra are co-added) is intrinsically lower than in the LW; conversely the saturation bright limit in the LW channel is significantly fainter than in the SW channel.
The first goal to designing successful observations in this new mode is to balance the SW SNR with the LW saturation limit. The second is to achieve that goal while also staying within the available downlink capacity of JWST. When the SW DHS grisms are used, data are collected on all 5 detectors in module A; when the DHS grisms aren't employed, data are collected on 3 detectors.
Multistripe subarray readout
As mentioned above and described in detail in the NIRCam Short Wavelength Grism Time Series and NIRCam Multistripe Subarrays articles, in the LW channel a single substripe of pixels is read out each time one of the SW substripes is read out; if 2 or 4 substripes are defined, the LW substripe is read out 2× or 4× more frequently than any substripe in the SW channel. Figure 1 illustrates the timing of reads in the SW and LW channels. Repeat_Stripe is the parameter controlling whether the subarray is read out as spatially separate substripes (as in the SW channel) or as a single substripe to be read repeatedly (as in the LW channel), and is not user selectable.
Click on the figure for a larger view.
Schematic showing the timing of substripe resets and reads for SW and LW multistripe subarrays used in the NIRCam Grism Time Series template when SW Channel Mode = GRISM. The exposure pattern is BRIGHT1 (nFrames=1, nSkip=1), and there are 3 groups per integration. Solid blue triangles represent the frames that are saved and downlinked; blue rectangles with red borders are the skipped frames. In the short wavelength (SW) channel 4 spatially separated substripes are read out, while in the long wavelength (LW) channel a single substripe is read out 4× more often. The frame time, group time, and integration time in the two channels is identical, but the reads in the LW channel are oversampled by a factor of 4 relative to those in the SW channel because there are 4 substripes per subarray. Vertical red lines indicate the reset time for the 1st pixel in the subarrays. Sloping red dashed lines show how the start of the reset progresses through the substripes. Note that the LW substripe gets reset multiple times (once for each SW substripe). Here, neither channel experiences saturation of the signal during the integration ramp. Labels indicate the group time (tGroup) and frame time (tFrame), which are unchanged from normal subarray definitions: both are determined from the dimensions of the entire subarray (i.e., including all substripes). The stripe time, tstripe, is the time to read out a single substripe of the multistripe subarray. The integration time, tint, is also the same for multistripe and "normal" subarrays, but the figure reveals the subtlety that the time at which particular pixels in a subarray are read or reset depends on their position within the subarray (the same is true for FULL exposures). This fact may influence interpretation of the data since the SW spectrum in substripe 1 will be sampled at a slightly different time than a spectrum in a different substripe. Note that when there are 2 or more substripes, timing in the LW substripe is the same (modulo the oversampling) as in the last SW substripe.
New DHS-specific readout patterns
To mitigate both the data volume concerns (see next section) for transit observations, and provide added flexibility to avoid saturation in the LW channel, new readout patterns will be made available prior to scheduling of Cycle 4 observations. Instructions for filling out the NIRCam Grism TImeseries APT template using the available patterns are given below.
Table 1 provides the basic properties of these patterns, along with the time to acquire 1 group for each pattern as a function of subarray size. These patterns all have nFrames = 1, so they don't produce the extra data for Frame0 inherent in patterns with nFrames ≥ 2 (e.g., BRIGHT2, SHALLOW2). Frame times for the subarrays are provided in Table 4 of NIRCam Short Wavelength Grism Time Series, and stripe times are reproduced here from that table. The "Group time" is the frame time × the sum of the saved and skipped frames for a pattern.
Table 1. New subarrays to be implemented for grism time-series observations using the DHS grisms in the SW channel
| Readout Pattern | nFrames | nSkip | SUB40STRIPE1_DHS | SUB80STRIPE2_DHS | SUB160STRIPE4_DHS | SUB256STRIPE4_DHS | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Group time [s] | Stripe Time [s] | Group time [s] | Stripe Time [s] | Group time [s] | Stripe Time [s] | Group time [s] | Stripe Time [s] | |||
| DHS3 | 1 | 2 | 0.6446 | 0.18864 | 1.2734 | 0.19912 | 2.5310 | 0.20436 | 4.0401 | 0.33012 |
| DHS4 | 1 | 3 | 0.8594 | 1.6978 | 3.3746 | 5.3868 | ||||
| DHS5 | 1 | 4 | 1.0743 | 2.1223 | 4.2183 | 6.73345 | ||||
| DHS6 | 1 | 5 | 1.2891 | 2.5467 | 5.0619 | 8.0801 | ||||
| DHS7 | 1 | 6 | 1.5040 | 2.9712 | 5.9056 | 9.4268 | ||||
Estimating saturation limits for patterns other than RAPID
Taking DHS4 as the pattern with the shortest group time likely to be used for transits requiring exposures lasting 6 hours total, the time to save 2 groups is 5 frames times (reset at t=0, read, skip, skip, skip, read). The bright limits in Figure 5 at NIRCam Bright Source Limits are based on a RAPID integration with nGroups = 2, so if the DHS4 pattern is used instead the saturation limit would be -2.5 Log(5/2) ≈ 1 magnitude fainter in the SW channel. Similarly, in the LW channel (see Figure 4 in NIRCam Bright Source Limits) would be fainter by 1 magnitude for the same reason, but brighter by -2.5 Log(1.02/0.645) = -0.5 (for a total change of 0.5 mag fainter) due to the frame times for the DHS 2048 × 40 subarray vs. the 2048 × 64 subarray used in that figure. Similar logic can be used to estimate the limits for other patterns. An algorithm is provided below for checking saturation limits in the ETC.
Data excess limitations on time-series duration
Time-series observations typically produce science data faster than any other type of observation. The volume of data that can be downlinked is finite: details are provided in the article JWST Data Volume and Data Excess. APT calculates the volume of data produced for all observations and provides warnings when they stress the available downlink capacity.
Observations that produce a data excess more than 5 GB in excess of above the downlink capacity require significant effort to schedule, and proposers must justify why they cannot use a readout pattern that produces data at a lower rate (e.g., saturation of the signal at the minimum integration time for a longer pattern). Those that have a data excess of more than 15 GB generally will not be supported, and require a particularly strong science justification. Those in excess of the 30 GB data excess limit cannot be supported, and generate an error in APT.
Table 2 provides a summary of the rate at which excess data is produced when the DHS exposure patterns and subarrays from Table 1 are used in short integrations (2–4 groups) appropriate for typical exoplanet host stars. Because APT doesn't currently include those exposure patterns, proposers will need to submit Cycle 4 proposals using one of the currently available exposure patterns (see detailed instructions below under "How to fill out APT ..."); data excess values are thus also provided for patterns RAPID, BRIGHT1 and SHALLOW2. Note that the data excess rate for the SHALLOW2 pattern (nFrames = 2, nSkip =3) is significantly higher than for DHS5 (nFrames = 1, nSkip = 4) because "Frame0" is being saved in addition to the coadd of the 2 reads in group 1.
Table 2 also summarizes the the duration of a time series exposure (Total Exposure Time in APT) that will exceed the 5 GB data excess threshold (which produces a warning in APT). Exposure patterns with total frames per group (nFrames + nSkip) equal to or greater than 7 (e.g. DHS7) have negligible or negative data excess rates (i.e. arbitrarily long exposures will not generate a data excess), and so aren't included in the table.
Table 2. Estimated time-series duration that exceeds the lower Data Excess Threshold vs. exposure pattern, nGroups and subarray
| Data Excess Rate (GB/hr) | Hours to Exceed Lower (5GB) Data Excess Threshold† | |||||||
|---|---|---|---|---|---|---|---|---|---|
| nGroups | SUB40S1 | SUB80S2 | SUB160S4 | SUB256S4 | SUB40S1 | SUB80S2 | SUB160S4 | SUB256S4 | |
| RAPID | 2 | 6.02 | 6.13 | 6.19 | 6.21 | 0.83 | 0.82 | 0.81 | 0.80 |
| RAPID | 3 | 7.16 | 7.29 | 7.35 | 7.38 | 0.70 | 0.69 | 0.68 | 0.68 |
| BRIGHT1 | 2, 3, 4 | 3.73 | 3.82 | 3.86 | 3.88 | 1.34 | 1.31 | 1.30 | 1.29 |
| DHS3 | 2 | 2.36 | 2.43 | 2.46 | 2.47 | 2.12 | 2.06 | 2.03 | 2.02 |
| DHS3 | 3 | 2.02 | 2.08 | 2.11 | 2.12 | 2.48 | 2.41 | 2.37 | 2.35 |
| DHS3 | 4 | 1.86 | 1.92 | 1.95 | 1.96 | 2.69 | 2.60 | 2.56 | 2.54 |
| SHALLOW2‡ | 2 | 2.02 | 2.08 | 2.11 | 2.12 | 2.48 | 2.41 | 2.37 | 2.35 |
| SHALLOW2‡ | 3 | 1.09 | 1.14 | 1.17 | 1.18 | 4.58 | 4.37 | 4.27 | 4.24 |
| SHALLOW2‡ | 4 | 0.68 | 0.73 | 0.75 | 0.76 | 7.34 | 6.87 | 6.65 | 6.57 |
| DHS4 | 2 | 1.44 | 1.50 | 1.53 | 1.54 | 3.46 | 3.33 | 3.27 | 3.25 |
| DHS4 | 3 | 0.99 | 1.04 | 1.06 | 1.07 | 5.07 | 4.82 | 4.71 | 4.66 |
| DHS4 | 4 | 0.79 | 0.84 | 0.86 | 0.87 | 6.33 | 5.97 | 5.79 | 5.73 |
| DHS5 | 2 | 0.79 | 0.84 | 0.86 | 0.87 | 6.33 | 5.97 | 5.79 | 5.73 |
| DHS5 | 3 | 0.30 | 0.34 | 0.36 | 0.37 | 16.69 | 14.62 | 13.76 | 13.44 |
| DHS5 | 4 | 0.10 | 0.14 | 0.16 | 0.17 | 51.20 | 36.35 | 31.67 | 30.14 |
| DHS6 | 2 | 0.30 | 0.34 | 0.36 | 0.37 | 16.69 | 14.62 | 13.76 | 13.44 |
| DHS6 | 3 | -0.19 | -0.15 | -0.14 | -0.13 | inf | inf | inf | inf |
† The time to exceed the middle threshold (15 GB) is a factor of 3 longer. Observations exceeding that higher threshold are extremely rarely approved for execution, and require a very strong scientific justification.
‡ SHALLOW2 will not be available for Cycle 4 observing, but for comparison purposes, it is in the APT version (2024.5) used for Cycle 4 proposing. SHALLOW2 is most similar to DHS5 in its saturation limit (both have nFrames + nSkip = 5), but has a data rate intermediate between DHS3 and DHS4. SHALLOW2 has a significantly higher data rate than DHS5.
Determining feasibility of an observation
To determine whether a particular time-series observation is feasible observers must balance two things. First, the total duration of the time-series exposure(s) places a lower limit on the exposure pattern that can be used without exceeding the data excess limits. Second, the saturation limit for the target places an upper limit on integration time, and therefore which exposure patterns can be used. Here, steps to follow are described below in order to determine if those competing limits can both be satisfied. If they can't, the observation isn't feasible within the current JWST capabilities.
Table 3. Times to reach the yellow (5GB) and orange (15GB) data volume thresholds and input values for the ETC saturation check as a function of the new readout patterns
| Readout Pattern | Time to reach 5 GB limit [hours] | Time to reach 15 GB limit [hours] | nGroups, ETC bright limit case†† |
|---|---|---|---|
| BRIGHT1† | 1.3 | 3.9 | 3 |
| DHS3 | 2.1 | 6.3 | 4 |
| DHS4 | 3.5 | 9 | 5 |
| DHS5 | 6.3 | 15 | 6 |
| DHS6 | 16.7 | 32 | 7 |
| DHS7 | inf | inf | 8 |
† Provided here for reference. Given the typical duration of exoplanet transits, it is highly unlikely that BRIGHT1 will be used with the DHS.
†† The ETC has to be configured with SUB40STRIPE1_DHS, RAPID, to check for saturation, see the feasibility determination algorithm below
Feasibility determination algorithm
Determine which exposure patterns can be used based on the necessary total exposure time (transit + baseline) and data excess limits above:
- Using Table 3, find the patterns for which the desired exposure time is shorter than the "Time to reach 5 GB limit" column.
- Note that the times shown in Table 3 are those in Table 2 for nGroups = 2 and the SUB40S1 subarray, so subarray size and nGroups can also be accounted for in this algorithm by referring to Table 2 and adjusting the "nGroups, ETC bright limit case" values to be (nGroups - 1) * (nFrames + nSkip) + nFrames.
- Note that the times shown in Table 3 are those in Table 2 for nGroups = 2 and the SUB40S1 subarray, so subarray size and nGroups can also be accounted for in this algorithm by referring to Table 2 and adjusting the "nGroups, ETC bright limit case" values to be (nGroups - 1) * (nFrames + nSkip) + nFrames.
- If not possible, find the patterns for which the exposure time is shorter than the "Time to reach 15 GB limit " column.
Using the ETC, determine which exposure patterns can be used without saturating on the source:
- Configure the Scene and Source for your target using those tabs.
- Create a NIRCam LW grism time-series calculation (the LW channel will always determine the bright limit for observations of stellar sources).
- Configure the Backgrounds tab, and select the filter under Instrument Setup tab.
- Under the Detector Setup tab:
- Select the SUB40STRIPE1_DHS (SW TS Grism) Subarray
- Set the Readout pattern to RAPID and number of integrations and dithers to 1
- Set Groups per integration to the value in the "nGroups, ETC bright limit case" column of Table 3
- Select the SUB40STRIPE1_DHS (SW TS Grism) Subarray
- Run the calculation.
- If your source does not saturate, the observation is feasible and you can stop.
- If it does saturate, go to Step 5.
- If your source does not saturate, the observation is feasible and you can stop.
- If your list of patterns from above includes a shorter one, move up one row in Table 3.
- Go to Step 3 and update the value of Groups per integration (only).
- Repeat steps 4 and (optionally) 5.
- If you have checked all of the usable patterns based on the needed total exposure time determined from Table 3 and the source still saturates, the observation is not feasible.
How to fill out the APT NIRCam Grism Time Series Template
Because the new DHS exposure patterns will not be available in time for Cycle 4 submissions, proposers should follow these guidelines for their APT submission.
- In the Proposal Observing Description field in APT Proposal Information, state which of the exposure patterns will be possible given the total exposure duration needed based on both the data excess constraints and the saturation limits. For example:
"For our total exposure duration of 5 hours, patterns DHS4 (nGroups=3) or longer do not exceed the 5 GB data excess threshold. Our saturation limit allows us to use integrations with DHS5 (nGroups=3) or shorter. Based on this we plan to update our program to use DHS4 pattern, nGroups=3 prior to execution."
- Place the observation(s) On Hold, using that special requirement, and include a comment that the exposure pattern, nGroups and nInt need to be updated to use your selected DHS pattern.
- Specify the exposure using the RAPID pattern and nGroups=3, and enough integrations to give the same total exposure duration you need.
- In the Proposal Observing Description field in APT, state the data excess you expect the proposal to generate once the exposure specification(s) have been updated. To estimate the data excess:
- Note the data excess given on the Visit view of your placeholder observation using RAPID.
- Multiply that excess by the ratio of the Data Excess Rate for your selected pattern and nGroups to that for RAPID, nGroups=3 in Table 2, above.
- If the table doesn't cover your case submit a NIRCam help desk ticket noting "DHS Data Excess" in the subject.
- In the APT Observing Description field give the result, e.g., "We estimate the Data Excess using the DHS# pattern as XXX GB, using the formula given in the JDox SW Grism Time Series Observing Strategies article." If you got assistance with the calculation through the help desk, note the ticket number.