NIRSpec MSATA Reference Star Selection Recommended Strategies

The NIRSpec MSA target acquisition (MSATA) observes a set of stars (typically 5–8 objects) through the open micro-shutter assembly (MSA), in order to correct for JWST's pointing and roll uncertainty. The selection of suitable reference stars depends on a number of factors: near infrared magnitudes, astrometric accuracy and proper motion, as well as stellar density and isolation. 

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This type of TA is the only way to ensure that science targets observed in NIRSpec's multi-object spectroscopy (MOS) mode are precisely aligned in their 0.20" × 0.46" MSA shutters. This article discusses strategies for planning MSATA during program update stage of the MOS and MSATA process. While MSATA cannot be fully defined at proposal submission (prior to orientation assignment by STScI), it is important to consider whether it is feasible with presently available imaging. If MSATA cannot be carried out with existing data, NIRCam pre-imaging should be proposed alongside the NIRSpec MOS observations.

A note about terminology:

Guide star acquisition with a guide star in the Fine Guidance Sensor is different from target acquisition which this article describes. Guide star acquisition occurs at the start of each visit, delivering an expected 1-sigma radial pointing accuracy of  0.10". Following that, MSATA can be used to place the science sources in the small shutters of the MSA.

MSATA uses reference stars in the MSA field of view, which are different from the single guide star used to more coarsely point the telescope during guide star acquisition.

Requirements for a successful MSATA

Words in bold are GUI menus/
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tools or package parameters.

See also: NIRSpec MSA Target AcquisitionNIRSpec Target Acquisition Recommended StrategiesNIRSpec Detector ReadoutNIRSpec MSATA Reference Star Selection Recommended StrategiesResources for MOS and MSATA Program Updates

There are a number of requirements that must be met for MSATA to successfully align MOS targets in their respective MSA shutters. These requirements are described in detail in the NIRSpec MSA Target Acquisition article, and summarized below.

Astrometric accuracy

The ideal relative astrometric accuracy for MSATA is 5–10 mas in a catalog that covers the reference stars and science targets. This relative accuracy is expected to result in a TA accuracy of 20 mas, or 1/10th of a MSA shutter width. Relaxed accuracy is allowed, however, if the science case permits it. In general, MSATA will require space-based imaging, either with NIRCam, or from HST in approximately the last 10 years. Stars in older HST images may have proper motions that will compromise MSATA.

NIRSpec magnitudes

NIRSpec's MSATA is carried out in one of the 3 TA bands, with the option to choose from a number of readout modes and patterns. The MSATA algorithm will take 2 exposures, with a half-shutter dither in both dispersion and cross-dispersion directions, in order to mitigate the effect of the MSA bars. Each exposure uses 3 groups and one integration, leading to a fixed sensitivity for each filter/readout pattern. Table 1 shows the ranges of magnitudes in the NIRSpec TA bands that will achieve S/N > 20, while also avoiding saturation. It is worth noting that any stars detected in 2MASS will saturate in NIRSpec's MSATA.

Table 1. Brightness ranges for NIRSpec MSATA filter and readout pattern options

Readout modeS/N = 20Saturation






Table note: Limiting bright and faint magnitudes for target acquisition reference stars. Readout patterns NRSRAPIDD1 and NRSRAPIDD2 are only used with the CLEAR filter for TA exposures. All TA exposures are acquired with Ngroups = 3.  NRSRAPIDD6 replaced NRS for MSATA for improved cosmic ray mitigation. Numbers based on ETC default coordinates (RA = 00:00:00 and Dec = 00:00:00). Numbers may vary with coordinates.

Proposers should consider that no catalogs currently have, or will have, the exact magnitudes measured in the NIRSpec bands. However, provided that some magnitudes exist, it should be possible to estimate NIRSpec magnitudes of stars with sufficient accuracy. The large magnitude ranges between S/N = 20 and saturation in Table 1 implies that the accuracy of the NIRSpec magnitude estimates does not have to be particularly high. As long as the inferred magnitudes are not near the edges of the magnitude bins, there is room for uncertainty in their estimates. Strategies for estimating these magnitudes are given in the article on Predicting MSATA Reference Star Magnitudes


The MSATA algorithm works by examining 3.2" boxes around the expected positions of the reference stars. Then, a 3 × 3 pixel box (0.3" × 0.3") is passed over the image to find the brightest pixel and centroid the source. It follows that MSATA requires isolated stars: TA reference stars must be the brightest object within a box having 3.2" on a side (plus 0.1"–0.2" extra for absolute pointing uncertainty), in the chosen NIRSpec TA filter. Likewise, fainter companions within 0.3" should also be avoided, as they can skew the centroid. For the final submission of flight-ready program updates, it is highly recommended that images of the selected reference stars are examined by a human, in order to avoid close binary stars or other artifacts that might be missed by automated catalog preparation tools.  

In cases where the density of stars is too high to identify suitably isolated MSATA reference stars, MSATA is not possible. Instead, the recommended strategy is to step the MSA Configuration in the dispersion direction, taking science spectra at enough positions to ensure that the desired targets fall in the slitlets at one of the planned pointings. Users interested in this approach should consult the NIRSpec Target Acquisition Recommended Strategies article to determine the required dispersion-direction spatial coverage that will account for JWST's pointing uncertainty. More information about slitlet stepping can be found in the article on NIRSpec MOS Recommended Strategies.

Density and type of MSATA reference objects

While MSATA typically uses 5–8 reference stars, a larger number of stars in the MOS footprint are needed since many cannot be used. For the optimally chosen science pointing, reference stars may be excluded because they fall behind the mounting plate between the MSA quadrants, or they are too close to a failed closed MSA shutter. Tests in the GOODS-S region, using the MSA Planning Tool (MPT), indicate that around 25%–30% of TA reference objects in the FOV, and in a given magnitude bin (see Table 1), can be successfully used for MSATA. In other words, for a chosen readout pattern and filter in Table 1, the density of reference objects should be approximately 2 arcmin-2 or higher. This density would predict 24.5 reference objects in the 3.6 × 3.4 arcmin MSA FOV (including behind the MSA mounting plate); a 25% success rate would yield around 6 useful reference objects. Nonetheless, fluctuations around these estimates are expected, due to small number statistics and spatial variations in the distribution of stars.    

These densities of stars are not always available at high Galactic latitude. For example, in the GOODS-S extragalactic survey field, the density of stars reported in the Skelton et al. (2014) catalogs is a few times too low to reach the 5 star minimum in any of the magnitude ranges in Table 1. Hence, the usage of compact galaxies will be essential for MSATA in many cases (indeed, compact galaxies were used to estimate the success fraction calculated above). A quantitative analysis has shown that use of compact galaxies will provide a lower accuracy post-TA pointing position than using stars alone. The level of final TA accuracy using compact galaxies depends on the catalog coordinate accuracy and the number of reference targets used.  In the event that non-point sources are used for MSATA, it may be advantageous to aim for closer to 8 rather than 5 reference objects, as residuals from the best fit TA solution may be larger in these cases.

When do I need to request NIRCam pre-imaging? 

See also: NIRSpec MOS Operations - Pre-Imaging Using NIRCamPredicting MSATA Reference Star Magnitudes

There are a number of scenarios that may arise where it is not straightforward to decide whether NIRCam imaging should be proposed. Here, we offer some guidance on specific cases.

I do not have any HST or NIRCam imaging of my field

Pre-imaging is highly recommended. Even if the TA reference stars have high precision astrometry, e.g., from GAIA, the relative astrometry between the science targets and the TA reference stars is critical. An offset between the relative astrometry of the MSATA reference stars and the science targets would cause the science targets to fall outside their intended MSA shutters. Likewise, at ground-based resolution, the centroid positions of the science targets may not be accurate enough to ensure that they are well-located in the MSA shutters.

I have HST imaging, but it is more than 10 years old

Because the magnitude ranges for MSATA in Table 1 are relatively faint, MSATA is sensitive to nearby cool stars. As a result, high proper motion is a concern. In GAIA, proper motions of 1–2 mas/year are typical for stars around 20th magnitude. Consequently, we recommend that HST imaging used for MSATA reference stars be less than about 10 years old. Stars with larger proper motions are also commonly seen: GAIA reports an RMS scatter reaching a few to several mas/year for faint stars. However, since MSATA uses 5–8 stars, there is some built in redundancy to allow for individual reference stars to fail. Regardless, if the only available HST imaging is more than 10 years old, NIRCam pre-imaging will likely be the safest strategy.

I have recent HST imaging at optical wavelengths, but no infrared imaging

At Galactic latitudes where foreground extinction is low, or at least well-characterized, a single optical color can predict the infrared magnitudes of stars with sufficient accuracy for MSATA. Therefore, if at least 2 bands of optical imaging are available, NIRCam pre-imaging is not necessary. In the article on Predicting MSATA Reference Star Magnitudes, we present tabular data and a python notebook that can be used to predict the NIRSpec magnitudes of stars.  However, we do not recommend this method for regions where the extinction is very high, spatially variable, and not always well known (e.g. Galactic star-forming regions). In that case, NIRCam pre-imaging would be recommended.

I have recent HST imaging in the optical, and deep ground-based near-infrared imaging

NIRCam imaging should not be necessary, provided that the desired science targets are detected in the HST imaging. However, heavily extincted regions may have objects that are not detected at any optical wavelengths. In this case, despite the fact that the positions and infrared magnitudes of the TA reference stars are well-known, the positional accuracy of the science targets is likely inadequate for placing them in the MSA shutters. Hence, NIRCam pre-imaging would be recommended.

I have recent HST imaging, but it does not contain very many stars

In science fields that have low extinction, whether or not NIRCam imaging will identify more stars for MSATA will depend on the depth of the HST imaging. In some cases,  deeper pre-imaging might help to find more stars. But in other cases, the HST imaging will already be sufficiently deep, and NIRCam will only uncover new stars fainter than the MSATA magnitude limit. (This happens to be the case for the Hubble Ultra Deep Field). Fortunately, compact galaxies should be sufficient for MSATA when there are not enough stars. However, if the HST imaging is at optical wavelengths only, NIRCam imaging is still likely required to estimate the NIRSpec magnitudes of the compact TA reference galaxies. Unlike stars, where a optical colors can predict the NIRSpec magnitudes, galaxies with unknown redshifts are considerably more difficult to extrapolate to the observed-frame near-infrared.

Latest updates

  • Updated to state our current understanding of MSATA with compact galaxies

    Minor formatting fixes, and added the Publication date and Latest Updates box.
Originally published