TECHNICAL
REPORT
Title: MIRI Imaging Dither Patterns
Authors: Christine H.
Chen1
Phone: 410338-5087
Doc #:
JWST-STScI-001657, SM-12
Date:
September 15, 2009
Rev:
A
Release Date: 3 February 2010
1.0
Abstract
We present a study on direct imaging dither patterns for MIRI. We propose a
combination of a compact dither pattern (4-Point Parallelogram) that is optimized for
sub-pixel sampling and larger patterns (12-Point Reuleaux and Cycling for imaging with
the FULL, BRIGHTSKY, and SUB256 subarrays or 5-Point Gaussian for imaging with
the SUB128 and SUB64 subarrays) that mitigate the effects of bad pixels and changing
scattered light and/or thermal emission backgrounds. Although we propose a compact
pattern with a fixed size scale, we propose larger dither patterns with average step sizes
that scale approximately with wavelength because MIRI will provide diffraction-limited
imaging between 5.6 and 25.5 µm. We suggest that observers should be allowed to obtain
data with the 4-point dither alone or at each position within a Reuleaux, Cycling or
Gaussian pattern to provide optimal sub-pixel sampling and self-calibration. Spitzer
IRAC encountered some of the direct imaging issues described above; therefore, we
suggest adopting the IRAC 5-Point Gaussian,12-Point Reuleaux, and Cycling dither
patterns for MIRI direct imaging with the full- and sub-arrays. The IRAC patterns have
been well vetted during the past 5 years of Spitzer operations.
2.0
Introduction
MIRI direct imaging observations may be improved by the use of dither patterns to (1)
mitigate the effect of bad pixels, (2) obtain sub-pixel sampling, and (3) self-calibrate data
if the changing scattered light and/or thermal emission background is significant.
Dithered observations are typically made using small angle offsets (<0.5′) that will not
require the use of additional JWST guide stars. It is anticipated that dithering will
enhance the majority of direct imaging programs using full- and sub-array modes;
although, a very small number of scientific programs may prefer observations made with
no dithering. For example, observations of transiting exoplanets require high precision,
time-series photometry that may be complicated by changes in the sensitivity as a
1
We would like to thank Jay Anderson, Andy Fruchter, and Karl Gordon for their helpful comments and
suggestions.
Operated by the Association of Universities for Research in Astronomy, Inc., for the National
Aeronautics and Space Administration under Contract NAS5-03127
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function of location on a pixel. In addition, dithering will not be implemented for
observations with the Four Quadrant Phase Masks and the Lyot Mask because
observations in these modes require precise positioning of the target behind each of the
masks. The science drivers for dithering have been described by Ferguson 2000 (STScINGST-R-0002A); preliminary constraints on dither patterns have been discussed in
Koekemoer & Lindsay 2005 (JWST-STScI-000647); and super-sky and self-calibration
flat simulations have been published by Casertano & Holfeltz 2002 (STScI-JWST-R2002-0004) and Holfeltz & Casertano 2003 (STScI-JWST-R-2003-002).
There is little commonality between the dithering strategies for NIRCam and MIRI
because the instruments possess different detector layouts, backgrounds, and spatial
sampling. (1) The NIRCam FOV is observed using 8 non-contiguous SCAs while the
MIRI FOV is observed using 1 SCA; therefore, NIRCam dithering must image the gaps
between detectors and modules. (2) The NIRCam background is dominated by emission
from the Zodiacal light that can be modeled using one observation and subtracted from
the data. The MIRI background at long wavelengths is dominated by scattered light and
thermal emission from the telescope that is expected to change as a function of time in
response to changes in the telescope pointing; therefore, MIRI dithering must provide
self-calibration to self-consistently solve for the pixel-to-pixel response and the changing
background. (3) The NIRCam is under-sampled over the majority of its wavelength
range; the short and long wavelength channels are Nyquist sampled at 2 and 4 µm,
respectively, and observe from 0.6-2.3 and 2.4-5 µm. The MIRI is super-sampled over
the majority of its wavelength range; the Imager is Nyquist sampled at 7.0 µm and
observes from 5.6-25.5 µm.
In this memo, we propose to use a compact dither pattern, optimized for sub-pixel
sampling (secondary patterns), and a subset of IRAC dither patterns, designed for selfcalibration (primary patterns), and include simulations demonstrating PSF reconstruction
using mosaicking. We defer detailed studies of self-calibration and mapping with
NIRCam and MIRI to a later time.
3.0
Spitzer Dithering Strategies
Both Spitzer IRAC and MIPS employed small angle maneuvers to mitigate bad pixels
and improve sub-pixel sampling. In addition, IRAC’s dither patterns were specifically
designed to enable an optimal self-calibration of deep field observations. IRAC is
approximately a factor of 2 more undersampled than MIRI, with sampling for the longest
wavelength IRAC channel (8 µm) identical to that expected for the shortest wavelength
MIRI filter (5.6 µm). MIPS is critically sampled at 24 and 160 µm but slightly
undersampled in the 70 µm wide FOV to optimize photometry. The 70 µm narrow FOV
possesses pixels that are about a factor of 2 smaller than the wide FOV. The MIRI subpixel sampling issues at the shortest wavelengths are similar to those of Spitzer IRAC and
MIPS.
The IRAC dither patterns were based on Arendt, Fixsen, & Mosley (2000) which showed
that dither patterns that sample a variety of spatial scales are needed to self-calibrate an
imaging data set. In particular, they demonstrate the effectiveness of the Gaussian
random and Reuleaux triangle patterns for sampling a wide range of spatial frequencies
in a uniform manner. Table 1 shows a short summary of the available IRAC patterns,
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each of which is available in small, medium, and large sizes. The 5-point Gaussian, 9point Random, Cycling, and 4-point Random patterns are all random Gaussian patterns in
which each offset (x, y) from the center of the array is randomly drawn from a Gaussian
probability distribution. The Cycling pattern is a table of 311 dithering positions from
which users can select a subset of dither positions by specifying the beginning table
position and number of dither offsets to be used. These patterns have been vetted for step
sizes that are smaller than the PSF FWHM or large enough that distortion (<1% across
the array) becomes important.
Table 1 Spitzer IRAC Dither Patterns
Dither Pattern
5-point Gaussian
9-point Random
12-point Reuleaux
16-point Spiral
36-point Reuleaux
Cycling pattern
4-point Random (sub-array)
9-point Releaux (sub-array)
Sub-Pixel Dither Pattern
½ pixel
1/3 pixel
½ pixel
¼ pixel
1/3 pixel
½ pixel
½ pixel
1/3 pixel
Although the IRAC patterns were designed with self-calibration in mind, the on-orbit
Spitzer IRAC super sky flat was of sufficient quality that self-calibration did not provide
a significant improvement in the calibration (S. Casertano, private communication). Since
Spitzer was cryogenically cooled, the thermal background at near-infrared wavelengths
was extremely stable. However, the JWST primary mirror will not be cryogenically
cooled and the telescope emissivity will change depending on the sunshield orientation;
therefore, the long wavelength MIRI thermal background is expected to be substantially
less stable than the IRAC background.
For comparison, MIPS imaging provided one fixed dither pattern for each channel/mode,
available in compact and large sizes. The 24 µm dither pattern included 14 positions
arranged in 2 columns, offset using ½ pixel sub-sampling. The 70 µm large field
photometry dither pattern included 12 positions arranged in 2 columns, offset using ½
pixel sub-sampling; the 70 µm compact source photometry dither pattern included 12
positions arranged in 2 columns, offset using ½ and1/3 pixel sub-sampling in the x and y
directions, respectively. Finally, the 160 µm array is scanned across the source with ½
pixel subsampling in both the compact source and large field modes.
4.0
MIRI Direct Imaging Dithering Considerations
Several instrument properties impact the design of dither patterns. For example: (1) What
fraction of the pixels is likely to be affected by cosmic rays? (2) How severe is the pixel
undersampling? (3) What is the accuracy with which the telescope can offset? (4) What is
the telescope and instrument geometric distortion? (5) Will a dithered set of images have
to be used for a self-calibration of the background?
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Cosmic Rays: Galactic cosmic rays are expected to affect ~10% of pixels in 1000 sec. At
solar maximum, cosmic rays and solar particles may affect ~30% of pixels in 1000 sec
(see JWST Mission Ops Concept Document MO-81). However, it is currently anticipated
that cosmic rays will be identified and removed in the course of the up-the-ramp slopefitting procedure and will therefore not directly drive our dithering considerations.
However, energetic nuclei hits on the detectors may produce “hot” or “dead” pixels that
are too bright or saturated compared to the incident flux. In these cases, small angle
maneuvers may be used to recover information from areas sampled by bad pixels. In
constructing possible dither patterns, one important requirement is that bad pixels not
affect unresolved point sources at multiple dither positions; therefore, we suggest
minimum dither steps of 6λ/D for large dither patterns.
Sub-Pixel Sampling: In direct imaging mode, MIRI will operate between 5.6 and 25.5
µm with a 1024x1024 SCA which has a 0.11″/pixel plate scale. Point sources will be
critically sampled at 7 µm. At shorter wavelengths, sub-pixel sampling will be necessary
to Nyquist sample unresolved point sources. Since MIRI is not badly under-sampled, ½
pixel sub-sampling will be adequate for most science programs (Ferguson 2000,
Koekemoer 2005). To mitigate the effects of bad pixels on sub-pixel sampling in
constructing possible dither patterns, we suggest a minimum of 4 dither positions with
fractional pixel offsets (0,0), (2½,0), (4, 2½), (1½ ,2½) relative to the pixel grid. If point
sources could be placed on the array with an accuracy of better than 0.1 pixel, then these
images could simply be interlaced to recreate the scene.
Offsetting Error Budget: The accuracy with which the telescope can be offset from one
dither position to another is determined by the uncertainty in the position introduced by
image motion and offsetting the telescope. Currently, JWST is expected to introduce 7
mas jitter while pointed at a fixed target. The observatory offsetting uncertainty has been
calculated as a function of offset position (see igure 1 from Anandakrishnan et al. 2006)
and is expected to be ~5 mas for offsets less than 5″. Since 11 mas precision is required
for precise ½ pixel sub-sampling, commanded dithers smaller than 10 pixels should
provide adequate precision for applications requiring accurate source placement on the
detector. Offsets larger than this will possess >11 mas positional uncertainty, worse than
the precision required for accurate ½ pixel sub-sampling, needed for interlacing. Offsets
smaller than 0.5′ (~270 pixels) are not expected to require guide star changes (Nelan et al.
2009); however, some regions of the sky may not possess sufficient guide stars for such
large slews. In these cases, the scheduling software will indicate that the selected dither
pattern can not be executed in one visit and that the observation must be broken into
multiple visits. In this case, the user will be asked to redesign their observations.
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Figure 1 JWST observatory offset accuracy as a function of offset distance
(Anandakrishnan et al. 2006).
Background Behavior: For wavelengths longer than 15 µm, thermal emission from the
telescope mirror and other spacecraft components dominates the background (see Figure
2). Since the telescope thermal emission is not expected to be constant, self-calibration
may be needed to self-consistently solve for the background and flat field for
observations at wavelengths longer than 15 µm (Meixner 2006). Self-calibration of fields
with a time-variable pedestal has been demonstrated using NICMOS HDF-N and -S data
(Arendt, Fixsen, & Mosley 2002). We propose three IRAC dither patterns, the 5-Point
Gaussian, 12-Point Reuleaux, and Cycling patterns, to mitigate the effects of bad pixels
and allow self-calibration.
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Figure 2 Zodiacal Dust, Sunshield, and Telescope contributions to the JWST
background.
Geometric Distortion: At the current time, the geometric distortion measured in the
three MIRIM models (ETM, VM, and FM) is consistent with the Zemax model, and has a
magnitude which varies from 0.0 at the center to <0.9% at the corners where the
distortion is the ratio of the measured radial position of an image to the
predicted/undistorted position. The distortion also affects the precision to which objects
can be placed within a pixel. A distortion of 1.009 implies that an offset of 10 pixels at
the center of the detector would create an offset of 10.1 pixels at the edge of the array,
affecting our ability to acquire simultaneously good pixel sampling everywhere on the
detector. If observers wish to interlace sub-pixel sampled images, then sources will need
to be placed on the array with an accuracy better than 0.1 pixel. Since offsets as small as
10 pixels may incur a 0.1 pixel distortion uncertainty at the edge of the detector, it is
necessary to decouple sub-pixel sampling from large-scale dither patterns and define
compact patterns with offsets smaller than 10 pixels.
We propose a compact dither pattern, the 4-Point Parallelogram (see section titled “Subpixel Sampling”), that provides precise sub-pixel sampling and which can be used in
conjunction with larger patterns optimized for self-calibration. Since the offsets in this
pattern are small (<5 pixels), executing this dithering pattern at every location in the
primary pattern provides dithers that are precisely separated from one another and
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therefore observations from which observers can both accurately recreate the scene and
self-calibrate the data. Alternately, observers can specify large numbers of unique dither
positions via the Cycling pattern. Since these dithers will randomly sample pixel phase
space, using large numbers of them ensures good sub-pixel coverage. In general, (1) the
smaller geometric distortion of MIRI (<0.9%) compared to NIRCam (~2%), (2) the fewer
pixels in the Imaging FOV of MIRI (1024 pixels on a side) compared to NIRCam (4096
pixels on a side), and (3) the super sampling of the MIRI PSF suggest that MIRI data
collected with ½ pixel sub-sampling will sample the PSF on finer spatial scales than
NIRCam data collected using the smallest sub-pixel sampling (1/7 pixel) currently
available (Anderson 2009).
5.0
Proposed MIRI Dither Patterns
We discuss possible dither patterns with attention to sub-pixel sampling and selfcalibration. We focus on flexible dither patterns that will accomplish the goals outlined in
the Introduction, noting that any new pattern designed to optimize self-calibration should
be carefully vetted for spatial overlap, otherwise sufficient pixel inter-relationships may
not exist to determine robust self-calibration.
We propose using three IRAC dither patterns (designed for self-calibration) and one subpixel dither pattern that can be executed in conjunction with one another for MIRI direct
imaging: (1) the 12-point Reuleaux triangle, suitable for observing objects slightly larger
than the PSF using the FULL, BRIGHTSKY, and SUB256 subarrays, (2) the random
cycling pattern with 311 positions, suitable for deep observations of distant galaxies (see
Figure 3) using the FULL, BRIGHTSKY, and SUB256 subaarrays, (3) the 5-point
Gaussian, suitable for observing bright objects using the SUB128 and SUB64 subarrays,
and (4) a 4 point Parallelogram pattern with offsets (0,0), (2.5,0), (4,2.5), and (1.5, 2.5)
that can be executed at each point in any of the previous dither patterns to minimize the
effects of geometric distortion and telescope offsetting errors. If the Gaussian, Reuleaux
and Cycling patterns are implemented in the same fashion that they were on Spitzer, then
the Gaussian and Reuleaux patterns can be used to minimize the area affected by residual
slew images from bright sources and the slew times between dithers and the Cycling
pattern can be used to obtain arbitrary sky depths (Reach et al. 2003).
Figure 3 Proposed MIRI dither patterns, drawn from Spitzer IRAC 5-point
Gaussian, 12-point Reuleaux, and 311 Cycling patterns, shown at medium scale. See
Tables A2, A3, and A4 for offset coordinates.
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The Gaussian, Reuleaux and Cycling patterns were designed with three different size
scales. We list offset and sub-pixel sampling statistics for each dither pattern in Table 2
and the individual offsets within each pattern in Tables A1 – A4 of the Appendix. The
IRAC PSF has been well characterized using observations of bright stars dithered
according to the Reuleaux pattern. Marengo et al. (2006) constructed a deep IRAC PSF
based on a 36-Point Reuleaux observation of ε Ind and 12-Point Reuleaux observation of
Vega that was used to search for planetary companions around ε Eri. Their high dynamic
range PSF is available on the SSC homepage. It should be possible to construct such high
quality PSFs for MIRI using the 12-Point Reuleaux in conjunction with the 4-point
Parallelogram because the geometric distortion for MIRI (~0.9%) is commensurate with
that of IRAC (<1%).
Table 2 Dither Pattern Characteristics
Pattern
4-Pt
Parallelogram
Cycling
12-Pt Reuleaux
5-Pt Gaussian
(subarray)
Scale
N/A
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Max Offset
4.7 pix
Median Offset
2.9 pix
Sub-Pixel
½ pix
11 pix
119 pix
161 pix
13 pix
27 pix
55 pix
12 pix
26 pix
52 pix
10.5 pix
53 pix
97 pix
15 pix
30 pix
59 pix
9.5 pix
23 pix
46 pix
½ pix
½ pix
½ pix
½ pix
½ pix
½ pix
½ pix
½ pix
½ pix
We propose that the random Cycling pattern be implemented in an identical fashion for
MIRI as it was for IRAC. Observers should be allowed to choose the starting position in
the dither table and the number of dither positions used to maximize observational
flexibility without increasing the number of required calibration observations. For
observers who may request more than 311 dither positions, we suggest wrapping the
Cycling pattern table so that the 312th dither position is the same as the 1st position. The
Cycling pattern is designed such that each set of four consecutive dithers provides
complete ½ pixel sampling; however, it is not recommended for observations that require
precise sub-pixel sampling. Observations that require accurate sub-pixel sampling should
be made in conjunction with the 4-point Parallelogram pattern. For example, an observer
could use the 4-point Parallelogram pattern at each position in either the Reuleaux or
Cycling patterns to obtain data that would be adequate for interlacing.
The SUB128 and SUB64 subarrays are smaller than the 12-Point Reuleaux and Cycling
patterns, suggesting that a separate dither pattern with smaller offsets is needed for these
subarrays. We propose a 5-point Gaussian pattern, based on the IRAC 5-point Gaussian
pattern, for use with the SUB128 and SUB64 subarrays. The targets observed with these
subarrays are expected to be bright, indicating that a small number of dither positions
should be sufficient.
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Unlike IRAC, we propose to make one size of the 5-point Gaussian,12-point Reuleaux,
and Cycling patterns available (with an average offset >6λ/D) for each filter instead of
providing small, medium, and large-sized Reuleaux and Cycling patterns for each filter
(see Table 3). In general, large or medium scale dithers help minimize the impact of
large-scale artifacts. Small-scale dithers are useful for super-resolution or maximizing the
area of full depth coverage. For MIRI, the shortest wavelength filter will be most
susceptible to sub-sampling and the longest wavelength filter will be most susceptible to
low frequency background structure caused by variations in the thermal background
radiation; therefore, small-scale dithers will be most appropriate for short wavelength
observations and large-scale dithers will be most appropriate for long wavelength
observations. The 5-point Gaussian dither pattern is designed for use with the SUB128
and SUB64 subarrays; however, the offsets in the Large 5-point dither pattern are larger
than the SUB64 subarray. Therefore, the SUB128 and SUB64 subarrays will use different
size 5-point Gaussian patterns for 18-25.5 µm as described in Table 3.
The small Cycling pattern was specifically designed for IRAC mapping, where only a
few dithers are taken at each map position. It was also based on a Gaussian distribution,
but the center was down-weighted to decrease the fraction of <5 pixel offsets (from the
central position), and it was truncated at a maximum offset of 11 pixels (from the central
position) to ensure that maps with up to 280″ spacing have no holes, even if there is only
one dither per map point (Spitzer Observer’s Manual v8.0). Since the MIRI direct
imaging FOV (74.3″x112.6″) is significantly smaller than the IRAC FOV (307″x307″),
the IRAC small cycling pattern will produce maps with no holes if the spacing between
images in the detector x- and y-directions are smaller than 71.8″ and 110.1″, respectively.
Although MIRI’s detectors possess four times as many pixels as IRAC’s, the 11 pixel
maximum dither constraint for the small cycling pattern is appropriate for dithering at 5.6
µm because dithers larger than 10 pixels incur more than 0.1 pixel offsets in distortion.
The down-weighted center is also appropriate because it minimizes the impact of a bad
pixel on a source. For the medium and large Cycling patterns, dithers with offsets larger
than 128 pixels have been removed to mitigate the effects of distortion.
Table 3 Proposed Scaling for Dither Patterns
Filter
6λ/D
5.6 µm
7.7 µm
10 µm
11.3 µm
12.8 µm
15 µm
18 µm
21 µm
25.5 µm
10 pix
13 pix
17 pix
20 pix
22 pix
26 pix
31 pix
36 pix
44 pix
12 Pt
Reuleaux
Small
Small
Medium
Medium
Medium
Medium
Large
Large
Large
311 Pt
Cycling
Small
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Medium
5 Pt Gaussian
(Subarray)
Small
Small
Medium
Medium
Medium
Medium
Medium/Large
Medium/Large
Medium/Large
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Mitchell (2008) have estimated that the slewing time for offsets up to 3.6″ (33 pixels)
will be ~10 s independent of the slew size and that larger slews will take exponentially
more time. The step sizes in all of the proposed patterns, except the medium and large
cycling patterns, use slews smaller than 33 pixels; therefore, the slewing times for all
patterns, except the medium and large cycling patterns, are already optimized.
Figure 4 Proposed MIRI Cycling patterns, drawn from Spitzer IRAC Cycling
patterns.
6.0
PSF Reconstruction Simulations
We conducted simulations reconstructing the Point Spread Function (PSF) from
undersampled, dithered images, similar to those expected to be obtained by MIRI, to
demonstrate the theoretical effectiveness of subsampling with a 5-point Gaussian pattern
using mosaicking, including geometric distortion if the offsets could be made with
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perfect accuracy, simulating the edges of the array if the Parallelogram or Diagonal
patterns are not implemented.
We used JWST_PSSIM (Anderson 2008) to simulate what the detector would record at
5.6 µm as a star is placed at various locations on the array, corresponding to the 5-point
Gaussian dither pattern. JWST_PSSIM uses PSFs constructed from JWPSF (Cox &
Hodge 2006) to simulate how stars would look through MIRI-sized pixels. The PSF
models were constructed from Rev-T estimates from BALL of what common-path errors
a star at the center of the MIRI detector might suffer. The central position of the point
source, dithered according to the small 5 point Gaussian pattern, would fall at the
following coordinates on a 128x128 subarray with a central position (64,64) assuming
5% geometric distortion due to MIRI:
(64, 61.9)
(58.225, 45.1)
(41.95, 71.875)
(66.625, 66.625)
(87.4125, 75.8125)
We did not include the geometric distortion of the PSF which is expected to broaden
further the FWHM by 5%. We used the following JWST_PSSIM commands to generate
PSF’s at 5 positions on our 128x128 subarray, assuming a source with a total flux of
10000 DN, a background of 10 DN/pixel/10 sec, Poisson noise, a cosmic ray rate 0.001
DN/pixel/10 sec and a 1% flat-field error, integrated for 16 frames of 10 sec each:
./jwst_pssim.e MIR 128 F0560W 64 61.9 10000 10 Y 0.001 1
1001100110011001 mirsim_f560w_pos1
./jwst_pssim.e MIR 128 F0560W 58.225 45.1 10000 10 Y 0.001 1
1001100110011001 mirsim_f560w_pos2
./jwst_pssim.e MIR 128 F0560W 41.95 71.875 10000 10 Y 0.001 1
1001100110011001 mirsim_f560w_pos3
./jwst_pssim.e MIR 128 F0560W 66.625 66.625 10000 10 Y 0.001 1
1001100110011001 mirsim_f560w_pos4
./jwst_pssim.e MIR 128 F0560W 87.4125 75.8125 10000 10 Y 0.001 1
1001100110011001 mirsim_f560w_pos5
We used IPAC’s Montage v3.0 software to mosaick the frames together using
pixels in the mosaicked image that are half the size of the original pixel in each
dimension. The properties of the output mosaicked image are specified in a template.hdr
file. We specify an 128x128 pixel output image, centered at an RA and Dec of 0° (in
J2000 coordinates) with a plate scale half that of the native MIRI plate scale
(0.055″/pixel).
Example template.hdr file
SIMPLE
BITPIX
NAXIS
NAXIS1
NAXIS2
CTYPE1
CTYPE2
CRVAL1
CRVAL2
CDELT1
CDELT2
CRPIX1
=
T
=
16
=
2
=
128
=
128
= 'RA---SIN'
= 'DEC--SIN'
=
0
=
0
=
0.0000152778
=
0.0000152778
=
64
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CRPIX2 =
CROTA2 =
EQUINOX =
64
0
2000
Montage requires header information about the coordinate system, position, and plate
scale. Therefore, we modify the *.fits file header for each dither position, assuming for
simplicity that the source is located at an RA and Dec of 0°:
Example: Modified mirsim_f560w_pos1_SCENE.fits header
SIMPLE
BITPIX
NAXIS
NAXIS1
NAXIS2
CTYPE1
CTYPE2
CRPIX1
CRPIX2
CRVAL1
CRVAL2
CDELT1
CDELT2
=
T
=
16
=
2
=
128
=
128
= 'RA---SIN'
= 'DEC--SIN'
=
64
=
64
=
0
=
0.0000641668
=
0.0000305556
=
0.0000305556
/ # of Axes
/
/
/
/
/
/
/
/
Orthographic Projection
Orthographic Projection
Axis 1 Reference Pixel
Axis 2 Reference Pixel
RA at Frame Center, J2000 (deg)
Dec at Frame Center, J2000 (deg)
Axis 1 Pixel Size (degs)
Axis 2 Pixel Size (degs)
We used the following Montage commands to generate (1) an image metadata table
‘images-rawdir.tbl’ describing the SCENE images in ‘rawdir’ subdirectory to be
mosaicked, (2) reprojected images in ‘projdir’ directory and a ‘stats.tbl’ table showing
processing times, (3) a new ‘images.tbl’ metadata table describing reprojected image
properties, and (4) a non-background corrected mosaic ‘5ptgaus_uncorrected’ in the
‘final’ directory:
% mImgtbl rawdir images-rawdir.tbl
% mProjExec -p rawdir images-rawdir.tbl template.hdr projdir stats.tbl
% mImgtbl projdir images.tbl
% mAdd -p projdir images.tbl template.hdr
final/5ptgaus_uncorrected.fits
We examine a line cut through the output image, taken through the PSF maximum,
parallel to the y-axis, and compare it with a line cut through a super-resolved image of
the scene, as output by JWST_PSSIM (see Figure 5). The output image is sampled using
pixels that are a factor of two smaller than the native MIRI plate scale and the idealized
MIRI PSF is sampled using pixels that are a factor of four smaller than the native MIRI
PSF. The two line cuts appear grossly similarly; however, the reconstructed PSF has a
FWHM = 0.25″, slightly broader than that of the idealized PSF (FWHM = 0.23″).
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 12 -
JWST-STScI-001657
SM-12
Figure 5 Comparison of line cuts through idealized PSF, oversampled by a factor of
4 (red), and mosaicked PSF, oversampled by a factor of 2 (black), both normalized
to 1.
7.0
Conclusions
We recommend implementing three direct imaging dither patterns to mitigate the effects
of bad pixels, to obtain sub-pixel sampled data, and to provide the opportunity to solve
directly for the background and flat field from an observational data set. The 5-Point
Gaussian is a generic pattern suitable for bright sources that will be observed using the
smallest (SUB128 and SUB64) subarrays; the 12-Point Reuleaux is a compact pattern
suitable for maximizing the area with the deepest coverage; and the Cycling pattern
allows observations of arbitrary depth. The 4-Point Parallelogram pattern can be used
alone or in conjunction with the Gaussian, Reuleaux, or Cycling patterns to obtain better
sub-pixel sampling and allow simple interlacing of the mosaicked frames. We propose
using Gaussian, Reuleaux and Cycling patterns of different sizes, depending on the filter
selected for observation, according to the prescription given in Table 3, with shorter
wavelength observations using smaller patterns and longer wavelength patterns using
larger patterns. The x- and y- offsets of individual dithers within each pattern/size are
given in Tables A1 – A4 of the Appendix.
8.0
References
Anderson, J. 2008, “JWST_PSSIM: A Point Source Simulator for JWST,” JWST-STScI001587
Anderson, J. 2009, “Dither Patterns for NIRCam Imaging,” JWST-STScI-001738
Anandakrishnan, S. et al. 2006, “JWST Pointing Error Allocation and Performance
Prediction Analysis,” NGST, DRD#D36177, Rev. B
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 13 -
JWST-STScI-001657
SM-12
Arendt, R. G., Fixsen, D. J., & Mosley, S. H. 2000, ApJS, 128, 651
Arendt, R. G., Fixsen, D. J., & Mosley, S. H. 2002, ASP Conference Proceedings, 281,
217
Casertano, S., & Holfeltz, S. T. 2002 “Comparison of Super-Sky and Self-Calibration
Flat Fields for Simulated Mid-Infrared JWST Images”, STScI-JWST-R-2004-0004
Cox, C. & Hodge, P. 2006 SPIE 2625 26, “Point-spread function modeling for the
JamesWebb Space Telescope”
Ferguson, H. C. 2000, “Science Drivers for NGST Small-Angle Maneuvers”, STScINGST-R-0002A
Holfeltz, S. T., & Casertano, S. 2003, “Futher Comparisons of Super-Sky and SelfCalibration Flat Fields for Simulated Mid-Infrared JWST Images”, STScI-JWST-R2003-0002
Koekemoer, A. M. & Lindsay, K. 2005, “An Investigation of Optimal Dither Strategies
for JWST”, JWST-STScI-000647
Marengo, M., Megeath, S. T., Fazio, G. G., Stapelfeldt, K. R., Werner, M. W., &
Backman, D. E. 2006, ApJ, 647, 1437
Meixner, M., Ressler, M., Rieke, G., & Bothwell, G. 2006, “JWST MIRI Calibration
Plan”, ORD OPS-03
Mitchell, L. 2008 “Observatory Efficiency Allocations Report”, JWST-RPT-004166 Rev
E
Nelan, E. 2009 “Small Angle Maneuvers, OSS, FGS, and ACS Interactions”, JWSTSTScI-001819
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 14 -
JWST-STScI-001657
SM-12
9.0
Appendix
Table A1. Proposed 4-Point Parallelogram Pattern X and Y Offsets
Position
X Offset
Y Offset
1
0.0
0.0
2
2.5
0.0
3
4.0
2.5
4
1.5
2.5
Table A2. Proposed 12-Point Reuleaux Triangle Pattern X and Y Offsets
Position
Small
Medium
Large
1
6.0
-12.0
13.0
-24.0
27.0
-48.0
2
9.0
-6.5
18.5
-12.0
37.5
-24.0
3
10.5
0.0
20.0
0.5
40
0.5
4
9.5
6.5
18.5
12.5
37.5
24.5
5
6.0
12.0
13.0
24.0
27.0
48.0
6
0.0
11.5
1.5
22.0
2.5
44.0
7
-5.5
8.0
-10.0
17.5
-20.0
35.5
8
-10.5
4.5
-20.5
9.5
-40.5
19.5
9
-13.0
-0.0
-27.0
-0.0
-55.0
-0.0
10
-10.0
-4.5
-20.5
-9.0
-40.5
-19.0
11
-5.5
-8.0
-10.0
-17.5
-20.0
-35.5
12
0.5
-11.5
1.5
-22.5
2.5
-44.5
Position
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table A3. Proposed 311-Point Cycling Pattern X and Y Offsets
Small
Medium
Large
-2.0
3.0
32.0
-40.0
-16.0
10.5
2.5
4.5
2.0
8.5
8.0
-2.5
11.0
41.5
23.0
1.5
-7.0
-34.5
87.5
71.5
5.0
-4.0
35.0
-29.0
70.0
-8.5
-6.5
8.5
29.0
-77.5
-11.0
-2.5
-50.0
4.5
-101.0
-2.5
-7.0
10.5
19.5
21.5
-4.0
-11.0
10.0
-32.0
36.0
0.5
9.5
-52.5
10.0
-104.5
10.0
-2.5
35.0
-12.5
71.0
-5.5
1.0
-35.5
-63.5
0.5
-7.0
-7.0
74.0
-17.0
-6.0
6.5
-5.5
-46.5
62.0
-11.5
8.0
0.5
16.0
11.5
78.0
-0.5
-5.0
30.5
-59.5
70.5
7.0
7.0
-35.0
21.0
-71.0
-7.5
-7.5
34.5
0.0
68.5
-37.0
4.0
82.5
62.5
-58.0
-29.0
8.5
39.5
36.0
21.0
-25.5
51.5
90.0
-7.0
-17.5
-40.5
42.0
1.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 15 -
JWST-STScI-001657
SM-12
Position
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
Small
-10.0
-4.5
-7.0
7.5
-7.0
4.5
-11.0
-3.5
0.0
-7.5
-9.0
9.5
-8.0
-10.5
1.0
10.5
7.0
1.5
-8.0
-10.5
1.0
9.5
-9.0
1.5
-6.0
-6.5
5.0
5.5
-9.0
-3.5
4.0
-1.5
-3.0
4.5
6.0
9.5
6.0
-9.5
-5.0
-6.5
-5.0
7.5
1.0
-3.5
-2.5
-7.0
7.0
2.5
2.5
-2.0
1.0
-7.5
-6.5
8.0
-7.0
5.5
0.5
3.0
-5.0
0.5
-4.5
-8.0
0.0
3.5
-4.5
1.0
-4.0
9.5
9.5
4.0
-1.0
-4.5
-4.5
6.0
7.0
-7.5
10.5
-7.0
2.0
-4.5
7.5
4.0
8.0
-2.5
2.5
-6.0
4.0
5.5
Medium
18.0
18.5
20.5
-14.5
3.0
25.0
13.5
0.0
-29.0
5.5
-4.5
-15.5
0.0
6.0
-62.5
0.0
23.0
57.5
13.5
-16.5
-15.0
33.0
-49.5
-4.0
0.0
-2.5
-31.5
-15.5
-3.0
-10.0
39.5
-8.0
8.0
3.5
7.5
22.5
22.0
41.0
-1.5
69.0
4.0
-30.5
-17.5
23.5
-47.0
-32.0
-17.5
-27.0
20.0
-11.5
32.5
-10.5
8.0
-46.0
-6.5
22.0
-37.0
-16.5
13.5
34.5
33.0
63.0
-9.5
-86.0
53.0
14.5
-100.5
-12.5
1.0
46.0
-23.5
-48.0
8.0
-38.5
-7.5
-11.5
30.0
-1.0
-24.5
-34.0
-22.0
25.5
46.5
-9.5
25.0
-18.0
0.5
-33.0
Large
20.0
-8.5
6.0
26.5
-59.0
41.5
0.0
-124.5
47.0
26.5
-30.0
-98.5
0.0
-63.5
-6.0
32.5
16.0
15.5
44.0
-7.5
8.0
-34.5
41.0
-34.5
-94.0
64.5
16.0
1.5
-74.0
26.5
67.0
-15.5
107.0
31.5
2.0
-47.5
16.0
92.5
60.0
14.5
-44.0
93.5
50.0
-13.5
-65.5
-31.5
50.0
0.0
10.5
-28.5
12.0
1.0
115.5
-33.5
66.0
-9.0
-5.5
-30.5
-21.0
22.0
7.5
44.5
82.0
29.0
-61.5
47.5
-23.0
-55.0
-65.5
-20.5
-92.0
-66.0
-33.5
68.5
127.0
-23.0
28.5
-16.5
92.0
-97.0
-76.5
21.5
-3.0
77.0
50.5
-18.5
-37.0
44.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 16 -
JWST-STScI-001657
SM-12
Position
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
Small
4.0
4.5
-3.0
-5.5
-2.0
-9.5
0.0
6.5
-5.0
4.5
10.0
-9.5
-6.0
5.5
-4.0
-4.5
9.0
-8.5
0.0
-0.5
-2.0
-3.5
2.0
6.5
5.0
-6.5
-7.0
-3.5
3.0
3.5
6.0
8.5
-9.0
-6.5
-2.0
1.5
0.0
-4.5
0.0
-7.5
-8.0
1.5
2.0
8.5
-5.5
9.0
0.0
2.5
8.5
-3.0
-2.0
2.5
-1.5
0.0
4.0
5.5
6.5
4.0
0.0
-5.5
5.5
3.0
3.0
-5.5
7.5
-3.0
9.0
-8.5
-1.5
3.0
-6.0
-2.5
-6.5
4.0
-6.0
-0.5
-4.5
-1.0
-5.0
-7.5
8.5
7.0
-2.0
-3.5
-0.5
9.0
-7.0
-4.5
Medium
1.0
-30.5
79.5
8.5
-18.0
42.0
-0.5
18.0
39.0
-3.5
36.5
8.5
7.0
38.0
-37.5
22.0
-15.0
-0.5
-38.5
6.5
21.0
16.0
51.5
13.0
24.0
6.5
-21.5
13.5
-5.0
45.0
49.5
-2.0
-7.0
-14.5
-43.5
0.5
11.0
13.0
66.5
12.0
-21.0
-32.5
31.5
-11.5
-14.0
31.0
-2.5
62.0
1.0
28.5
53.5
-106.5
-24.0
5.0
-3.5
4.0
33.0
5.5
31.5
0.5
-42.0
-48.0
10.5
-3.0
44.0
32.5
-5.5
-44.5
-10.0
-5.0
-26.5
-11.0
-18.0
-11.5
-29.5
8.5
20.0
32.0
1.5
-5.0
26.0
21.5
-4.5
48.5
-35.0
0.0
76.5
-1.0
Large
-48.0
77.5
103.0
-0.5
78.0
73.5
2.0
-75.5
-30.0
-76.5
43.0
-37.5
48.0
-43.5
-10.0
-15.5
98.0
-86.5
23.0
58.5
-42.0
62.5
-29.0
-4.5
3.0
66.5
-49.0
-6.5
38.0
63.5
-3.0
21.5
88.0
-70.5
-21.0
-53.5
-36.0
-58.5
40.0
2.5
53.0
-9.5
-71.0
-16.5
-69.5
60.5
26.0
36.0
-7.5
16.5
-61.0
44.0
-0.5
12.5
32.0
84.0
13.5
26.5
90.0
-29.0
-4.5
0.5
26.0
80.0
-65.5
-22.5
63.0
125.0
57.5
11.5
11.0
8.0
-105.5
1.5
60.0
-6.0
65.5
-127.5
-11.0
-22.0
-23.5
16.5
64.0
-10.0
43.5
96.5
0.0
106.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 17 -
JWST-STScI-001657
SM-12
Position
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
Small
-7.0
0.5
-7.0
10.5
6.0
6.5
-1.0
2.5
1.0
-7.5
-5.0
5.5
-3.0
0.5
0.0
7.5
7.0
6.5
-6.0
-0.5
-9.0
-0.5
7.0
5.5
2.0
-4.5
-8.0
7.5
1.0
0.5
4.0
3.5
-3.0
-8.5
11.0
-6.5
-3.0
6.5
6.0
2.5
10.0
2.5
-6.0
0.5
4.5
-3.0
-5.0
4.5
2.5
8.0
4.0
0.5
-7.5
-3.0
5.0
6.5
-10.5
-1.0
-6.0
-7.5
1.5
6.0
5.0
2.5
3.5
-11.0
0.0
8.5
4.5
-1.0
0.0
1.5
-9.5
-6.0
8.0
4.5
2.5
-1.0
1.0
7.5
-2.5
1.0
8.0
-8.5
1.5
3.0
-3.0
9.5
Medium
37.0
48.5
19.5
-52.5
-19.0
-33.0
-1.5
30.0
0.0
25.5
1.5
19.5
28.0
42.0
-34.5
-98.0
8.0
53.5
-15.5
36.5
11.0
-2.0
-9.5
60.0
7.0
36.5
47.5
39.5
-30.0
-9.0
29.5
27.0
-24.0
-62.5
20.5
36.5
25.0
-5.0
5.5
-29.0
-46.0
-22.5
5.5
14.5
24.0
13.0
30.5
-23.0
-25.0
16.5
43.5
-14.5
-26.0
10.0
21.5
23.0
37.0
16.5
30.5
-38.5
-14.0
-6.0
6.5
4.0
5.0
20.5
13.5
-5.5
-16.0
39.0
25.5
-26.0
-30.0
-32.5
-71.5
42.5
-18.0
64.0
-5.5
-3.0
-5.0
29.5
26.5
-4.5
7.0
-13.0
47.5
77.0
Large
75.0
-38.5
-29.0
-85.5
-10.0
3.5
57.0
57.5
40.0
-61.5
23.0
-18.5
14.0
27.5
-31.0
58.5
-48.0
16.5
51.0
10.5
-93.0
10.5
49.0
61.5
-51.0
87.5
-53.0
43.5
75.0
61.5
-29.0
13.5
10.0
94.5
-33.0
51.5
-60.0
-26.5
48.0
-92.5
-11.0
53.5
-24.0
-36.5
96.5
-67.5
61.0
-96.0
-88.5
38.5
85.0
20.0
72.5
-18.5
-4.0
120.0
73.5
-10.5
72.0
55.0
-124.5
107.5
-10.0
-58.0
-44.5
29.5
27.0
-46.0
32.5
-29.5
21.0
46.0
33.5
-77.5
-12.0
9.0
41.5
78.5
78.0
-53.0
-65.5
58.5
-75.0
124.0
58.5
-9.5
-14.0
34.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 18 -
JWST-STScI-001657
SM-12
Position
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
Small
-10.0
-10.5
3.0
-2.5
8.0
7.5
-9.0
-8.5
2.0
5.5
-5.0
4.5
-4.0
8.5
4.0
1.5
-6.0
-5.5
-9.0
0.5
-8.0
1.5
5.0
-5.5
-3.0
-5.5
9.0
2.5
1.0
-7.5
-1.0
6.5
7.0
-9.5
3.0
-7.5
-3.0
2.5
7.0
3.5
2.0
-1.5
10.0
-3.5
3.5
-2.0
-8.0
9.5
-5.5
4.0
4.0
-3.5
4.5
0.0
-8.0
-9.5
-0.5
3.0
-5.0
8.5
4.5
-4.0
-4.0
-5.5
2.5
9.0
-4.0
-3.5
5.5
-10.0
1.0
-2.5
4.5
-6.0
9.0
-4.5
0.5
-1.0
-9.0
-5.5
9.5
-2.0
-5.0
2.5
-7.5
-6.0
-2.0
4.5
Medium
-41.0
-23.5
-24.5
-17.5
11.0
19.0
-9.5
-33.0
21.0
-42.5
-22.5
15.5
12.0
-22.0
-36.5
51.0
-24.0
-1.5
-12.5
-7.5
-10.0
13.0
-48.5
-4.0
-9.0
21.5
14.5
29.5
-2.0
71.0
-3.5
20.0
29.0
50.5
61.5
-26.5
35.0
-44.0
-9.5
28.0
21.0
-5.5
26.5
25.5
48.0
-6.0
-8.5
-42.0
33.0
24.5
-5.5
-1.5
23.0
-61.0
-58.5
-1.0
-27.0
41.5
22.5
-14.5
-35.0
-15.0
-27.5
-1.0
15.0
7.5
7.5
51.5
-50.0
-7.0
-9.5
19.0
-24.0
50.5
-2.5
-92.5
0.0
16.0
-45.5
-26.0
-10.0
-9.5
-5.5
-77.5
38.0
-25.0
-62.5
34.0
Large
-82.0
-48.5
22.0
-19.5
43.0
-44.5
25.0
-73.5
-48.0
14.5
-21.0
-96.5
-19.0
-19.5
-3.0
43.5
59.0
122.5
70.0
28.5
-7.0
52.5
96.0
-101.5
67.0
-11.5
46.0
-116.5
-54.0
44.5
-55.0
-70.5
0.0
14.5
-17.0
-19.5
-49.0
-0.5
-63.0
-91.5
-21.0
-3.5
77.0
-124.5
-47.5
-34.5
39.0
-66.0
-84.5
30.5
-45.0
103.0
-3.5
-27.5
27.0
-8.0
43.5
56.5
-37.0
-11.0
101.5
-53.5
-88.0
58.0
40.5
51.5
-12.0
-15.0
48.5
-2.5
-123.0
-3.0
82.5
-28.5
-3.0
-31.0
33.5
102.5
-84.0
39.0
101.5
-46.5
-34.0
-52.0
-19.5
77.5
-50.0
68.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 19 -
JWST-STScI-001657
SM-12
Position
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
Small
-10.0
-6.5
2.0
0.5
3.0
5.5
-6.0
6.5
-8.0
-5.5
4.0
6.5
2.0
-3.5
-8.0
-5.5
-10.0
-1.5
2.0
-10.5
9.0
-8.5
-7.0
-6.5
2.0
1.5
6.0
-10.5
-9.0
9.5
5.0
0.5
0.0
6.5
-8.0
9.5
7.0
2.5
-4.0
3.5
1.0
-7.5
8.0
4.5
4.5
5.0
6.0
-5.5
-9.5
-7.0
-6.0
0.5
7.5
3.0
5.0
-2.5
-6.5
9.0
-8.0
6.5
-4.5
5.0
-9.0
0.5
2.5
4.0
-2.0
7.5
-9.5
7.0
-4.0
2.5
-4.5
-2.0
-8.0
4.5
-8.5
-1.0
-4.0
3.5
-6.5
-2.0
-8.0
5.5
-6.5
-3.0
-6.0
-7.5
Medium
42.0
55.5
38.5
-18.5
54.0
-14.0
19.5
15.0
-6.0
-28.5
74.5
-28.5
12.0
-14.0
-23.5
38.0
53.0
24.5
-31.5
-17.5
56.0
35.0
-12.5
-18.0
-42.0
-11.5
-3.5
-19.5
35.0
31.0
21.5
-33.0
33.0
-18.5
-24.5
-41.5
23.0
61.0
-10.5
-11.0
29.0
-7.5
11.5
38.5
0.0
-6.0
11.5
50.0
35.0
14.5
57.5
-18.5
19.0
-9.0
62.5
8.0
-21.0
-34.5
20.5
14.5
17.0
4.0
25.5
11.0
-24.0
14.5
-17.5
22.5
-34.0
12.0
-0.5
13.0
-8.0
-22.5
37.5
34.5
16.0
-32.0
-35.5
43.0
6.0
13.5
-25.5
31.5
-23.0
26.0
23.5
-50.0
Large
85.0
77.5
109.0
38.5
-13.0
55.5
-46.0
24.5
106.0
30.5
112.0
-24.5
-85.0
-7.5
-44.0
42.5
66.0
-49.5
46.0
-21.5
59.0
23.5
0.0
114.5
70.0
33.5
38.0
75.5
-43.0
40.5
34.0
51.5
111.0
-34.5
-69.0
-0.5
-17.0
125.5
23.0
-71.5
12.0
-50.5
-47.0
46.5
110.5
-36.5
-29.0
31.0
-56.5
38.5
77.0
-28.0
49.5
15.5
70.0
-37.0
-23.5
-38.5
30.0
-67.0
-37.5
-83.5
123.0
-22.0
-14.5
76.5
-12.0
-36.0
29.5
-64.5
-18.0
68.0
-69.5
29.5
8.0
22.0
-31.5
44.5
25.0
26.0
-45.5
16.5
101.0
87.0
27.5
62.5
52.0
-100.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 20 -
JWST-STScI-001657
SM-12
Position
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
Small
7.0
2.5
-7.0
-7.5
1.0
-7.5
6.0
0.5
3.0
6.5
-8.0
8.5
-2.0
-8.5
-2.0
-10.5
-9.0
7.5
-2.0
-7.5
3.0
-5.5
6.0
-7.5
-2.0
-2.5
-2.0
7.5
3.0
-6.5
8.0
5.5
6.0
-4.5
4.0
10.5
7.0
-5.5
-4.0
1.5
-3.0
-6.5
9.0
7.5
1.5
9.0
-9.0
2.5
-5.5
-2.0
0.0
9.5
-9.5
5.0
-7.0
-2.5
-4.5
-3.0
2.0
-0.5
-6.5
3.0
5.0
-1.5
3.5
-4.0
7.0
2.5
6.5
3.0
-9.0
-7.5
-4.5
-7.0
-4.0
8.5
3.5
4.0
-5.0
-1.5
-6.5
-5.0
2.0
3.5
-7.5
4.0
-1.0
-5.5
Medium
72.0
4.5
28.5
-5.5
-3.0
31.0
-41.5
-55.0
55.0
-15.5
84.5
-40.5
23.0
-14.0
-21.5
-15.0
4.0
-1.5
-11.5
3.5
10.0
54.0
32.5
46.0
70.0
33.5
-10.5
51.5
-9.0
-45.0
23.5
-34.0
-19.0
-5.5
-6.5
-6.5
-81.0
-29.0
71.5
-48.0
46.0
-47.5
-64.5
-4.5
-28.0
32.0
-6.5
-60.0
35.0
-17.5
-22.5
17.5
-14.0
-3.0
54.5
-19.0
-77.0
20.5
27.5
34.5
-4.0
-30.0
-20.5
-62.0
14.0
-24.5
31.5
12.5
22.0
-27.0
67.5
-3.0
-9.0
-25.5
57.5
6.5
39.0
26.0
37.5
5.0
-4.0
5.5
-23.5
3.5
0.0
36.0
4.5
-25.0
Large
84.0
57.5
-7.0
-83.5
-49.0
-18.5
109.0
-42.5
8.0
-23.5
20.0
65.5
55.0
-21.5
-72.0
46.5
-39.0
-12.5
-82.0
-2.5
93.0
-29.5
-57.0
-13.5
70.0
-45.5
-28.0
47.5
-78.0
55.5
-9.0
-41.5
29.0
62.5
44.0
-27.5
-19.0
114.5
79.0
74.5
-9.0
-47.5
0.0
9.5
-37.5
-10.5
62.0
-110.0
29.5
-90.5
-38.0
-31.0
-2.5
6.5
109.0
92.0
-117.5
102.5
26.0
-68.0
-10.5
-13.5
-20.0
123.0
-95.5
-51.5
64.0
-121.0
-35.5
35.5
-6.0
-28.0
66.5
68.5
-61.0
-125.0
-49.5
25.5
-54.0
63.0
-51.5
12.5
53.0
10.0
11.5
7.5
73.0
-50.0
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 21 -
JWST-STScI-001657
SM-12
Position
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
Small
-6.0
-2.5
2.0
1.5
3.0
-7.5
-9.0
0.5
4.0
8.5
0.0
6.5
-4.0
0.5
6.0
6.5
-3.0
9.5
10.0
-1.5
5.0
4.5
-2.0
-8.5
8.0
8.5
-8.0
-3.5
-5.0
-7.5
4.0
-3.0
10.5
7.5
0.0
4.0
-9.5
1.5
-5.0
7.0
-7.5
9.5
-2.0
0.0
-3.5
0.5
-6.0
-2.0
6.5
-0.5
-6.0
2.0
0.5
-1.5
-6.0
-5.0
-4.5
-7.5
Medium
-33.0
2.5
-12.5
35.5
-27.0
-18.0
8.5
-38.0
3.0
-20.5
-17.5
36.5
36.0
-39.0
-56.5
57.0
23.0
47.5
-31.5
30.5
-28.0
-33.0
12.5
31.0
-7.0
42.5
50.5
-3.5
50.0
-20.0
-16.5
-12.0
-12.0
-3.5
-7.5
-61.5
38.0
19.0
-36.5
28.0
83.0
9.5
35.5
-20.5
-3.0
-13.0
-38.5
-14.0
15.0
20.5
3.5
-37.5
-8.0
-18.0
4.5
-22.0
-21.0
38.5
Large
-67.0
-24.5
-54.0
17.5
6.0
-35.5
73.0
-113.5
46.0
-62.5
-42.0
24.5
-14.0
101.5
101.0
-33.5
-24.0
-14.5
77.0
-72.5
-21.0
61.5
-6.0
8.5
31.0
7.5
63.0
17.5
-56.0
5.5
70.5
-36.0
-77.0
-40.5
72.5
-79.0
114.0
94.5
61.5
76.0
62.0
84.5
-6.5
-40.0
-25.0
-7.5
-122.5
38.0
57.0
-21.5
-119.5
-26.0
-45.0
41.5
-75.5
-81.0
59.0
-66.5
Table A4. Proposed 5-Point Gaussian (Subarray) Pattern X and Y Offsets
Position
Small
Medium
Large
1
0.0
-1.0
0.0
-2.0
0
-4.0
2
-2.5
-9.0
-5.5
-18.0
-10.5
-37.0
3
-11.0
3.5
-21.0
7.5
-43.0
14.5
4
1.5
1.5
2.5
2.5
4.5
5.5
5
11.25
5.25
23.15
11.25
47.25
22.25
Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
To verify that this is the current version.
- 22 -