TECHNICAL
REPORT
Title: Optimization Strategies for the
NIRSpec MSA Planning Tool
Doc #:
JWST-STScI-001851, SM-12
Date:
24 August 2009
Rev:
Authors: James Muzerolle
1.0
Phone: 410338-4719
Release Date: 9 December 2009
Abstract
A GUI-based tool that allows JWST users to plan multi-object spectroscopic observations
with the NIRSpec Microshutter Array (MSA) is currently being developed for APT. This
document presents results of a study of optimization techniques that should be
incorporated into the tool to maximize the number of spectra obtained per exposure.
Using an independent and interactive “simulator” of the planning tool, I have evaluated
six test cases based on the requirements likely to be common to many observing
programs. The test cases include calculations with and without the effects of inoperable
microshutters, using different object-sky “slitlet” configurations, incorporating dither
offsets, observations of targets with different spatial distributions on the sky, and
incorporating target prioritization. From the results of these test cases, I make some
specific recommendations for the implementation of an optimization scheme and discuss
implications for related procedures such as dithering.
2.0
Introduction
2.1
The NIRSpec Microshutter Array
One of the key components of the Near-Infrared Spectrograph (NIRSpec) is the
Microshutter Array (MSA). The MSA allows multi-object spectroscopy by means of an
array of tiny shutters that are independently operable to block (in the closed state) or
transmit (in the open state) light from the sky onto the NIRSpec focal plane array. The
MSA is split into four quadrants, and each quadrant consists of a grid of 365x171 shutters
aligned with the dispersion and spatial axis, respectively (Fig. 1)1. Each shutter has a
1
In the standard MSA nomenclature, shutter “rows” are parallel to the spatial direction and “columns” are
parallel to the dispersion direction. However, I adopt the reverse definition for this document, with rows
running parallel to the dispersion direction, since that is more consistent with the astronomical standard and
what users will likely expect when working with the planning tool. It is also expected to be used
exclusively in subsequent documentation such as the proposal instructions. Thus, I recommend that this
definition be adopted in future versions of APT.
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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pitch of about 0.26” in the dispersion direction and 0.51” in the spatial direction, with an
actual open aperture size of 0.2”x0.45”. Each aperture open to sky produces a spectrum
that runs along the dispersion axis, roughly parallel to shutter rows but with some
curvature that depends on the optical distortion. Two open shutters in the same row
across both quadrants will always produce overlapping spectra for the R=1000, 2700
gratings, and sometimes with the prism if the separation between the shutters is small
enough.
2.2
The MSA Planning Tool
A tool for planning observations with the MSA is already in an advanced state of
development. A prototype is available in APT 17.0.3. An initial set of features for the
tool was outlined by Valenti et al. (2006). Briefly summarizing that report, the user can
supply a list of candidate target coordinates (hereafter referred to as “candidates”), an
orientation angle, and the coordinates for the MSA center pointing. A backend program
then calculates which of the targets fall within the projected field of view of a
microshutter at the given pointing and orientation angle. By default, the tool assumes
that each shutter containing a target has an associated “sky” shutter on either side along a
shutter column (spatial direction). The GUI displays the outlines of the field of view of
the four MSA quadrants, marks the positions of all of the targets and indicates which
ones are observable. Figure 1 shows an example of the APT display. The user can
manually change the center pointing, orientation angle, and individual shutter usage, and
can choose from a limited set of sky shutter configurations.
However, the prototype lacks a proper optimization scheme that will maximize the
number of selected targets (hereafter referred to as “targets”) in a given configuration,
prevent spectral overlap, allow the user to plan for multiple configurations when working
from the same candidate set, and account for broken shutters. In this report, I explore a
heuristic approach that can be taken to expand functionality of the tool and allow users to
optimize their observations. Note that the optimal solution in any given case is
computationally very expensive to determine. My heuristic approach is expected to yield
nearly optimal solutions, but I do not show proof that this is indeed the case. Also, I
have investigated a somewhat limited set of observing scenarios, focusing on candidate
sets consisting solely of point sources. Other scenarios, such as those with extended
sources, need to be considered when the final version of the planning tool is designed.
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Figure 1: : Display from the APT MSA planning tool. The large blue squares show the outlines of the
four MSA quadrants, and the red cross shows the center pointing. Diamonds show the candidate
positions from the input catalog (blue: candidates that fall outside of the MSA field of view; yellow:
candidates that did not fall within a shutter aperture; green: candidates that did fall within a shutter
aperture and are thus the selected targets). The bottom panel is a zoomed-in view of two of the targets,
showing the target shutter with nominal acceptance zone (or “sweet spot”) and default sky shutters.
3.0
Optimization Test Cases
For increased flexibility and efficiency in exploring parameter space, I wrote a planning
tool “simulator” in IDL (the code can be found in the accompanying zip file). The
simulator eschews the advanced graphical interface provided by the APT tool in favor of
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a command line-driven iterative program that focuses on optimizing the number of
targets that can be observed with a given MSA configuration. The user provides a
candidate table with coordinates and (optional) priority rankings, an initial MSA center
pointing coordinate, and an initial MSA position angle. The code computes the distance
of each candidate to the center of the nearest projected MSA shutter given the initial
center pointing. All candidates that lie within the 0.2”x0.45” boundaries of an open
shutter aperture (or an optional specified acceptance or “sweet spot” zone within the
shutter) are flagged.
Not all flagged candidates can necessarily be observed in the same configuration. For
example, if two candidates lie in the same shutter row, observing them both would result
in overlapping spectra in most cases. Since this will be undesirable for most observing
programs, the optimization routine must be able to select only one of these candidates.
The simulator code does this in the following manner. Stepping through each MSA row
starting from the bottom, the code identifies all flagged candidates that lie within shutters
in that row. If a slitlet pattern of 2 or more shutters along a column is desired for
obtaining sky spectra, the number of extra “sky” shutters per target can be specified, and
the code will skip the appropriate number of rows in order to avoid overlapping sky or
target spectra. When there are multiple flagged candidates, one is selected in one of two
ways: by default, on a first-come-first-served basis determined by the order of listing in
the candidate table, or optionally, based on the priority ranking read from the table (see
test case #6 below). The default method is probably not a good option, since it could
conceivably lead to a bias in target positions away from shutter centers if the input
candidate list is ordered by RA coordinate; other selection criteria should be considered
in the final implementation, for example, the candidate that is best centered in its shutter
sweet spot.
The target placement is then iterated by changing the MSA center pointing coordinate
and/or position angle. The user can specify a grid of coordinates and orients by entering
in the desired number of steps in RA, DEC, and position angle, and the size of each step
(arcseconds for the pointing and degrees for orient). The code will then calculate a
configuration at each grid point, and identify the one with the largest number of targets.
The desired step size may depend on the details of the observing program. Most
observers will likely use values of order the size of the inter-quadrant gaps in order to
recover candidates that do not fall into the MSA field of view at the default pointing. If
recovery is not a concern, then step sizes similar to the shutter pitch may be desired to
finesse the number of targets that fall within shutter (or acceptance zone) boundaries.
I have calculated MSA configurations for 6 test cases using parameters that are expected
to be common in science programs observing multiple point sources in sufficient
numbers to require multiple configurations for a majority of candidates to be observed.
To assess observing efficiency in each case, I used two primary metrics: 1) the number
of targets observed in the first configuration; 2) the number of configurations needed to
observe at least half of the candidate sample. The results are summarized at the end of
this section in Table 1. From these findings, I make some recommendations on optimal
observing strategies and key components that need to be included in the planning tool.
All of these cases assume that targets may be placed anywhere within the open area of a
shutter. In actuality, most programs will want targets to be placed within a smaller
acceptance zone to ensure accurate flux calibration, which will significantly reduce the
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fraction of candidates that are observable in a single MSA configuration compared to the
results shown here.
Test case 1: UDF catalog (1009 targets), default 3-shutter slitlets, ideal MSA
I used an input catalog (created by D. Karakla) consisting of 1009 objects selected from
the Hubble Ultra Deep Field (UDF) to serve as a fiducial candidate sample for most of
the optimization test cases. This sample provides a substantial and relatively uniform
candidate density that is well-matched to the MSA field of view. For the first run, a
default pointing corresponding to the center of the UDF field was selected. With no
optimization of the center pointing, 102 targets can be observed in the 1st configuration,
and more than half of the total number of candidates (407/770) that lie within the MSA
field of view can be observed with 5 configurations. Roughly one third of the candidates
cannot be observed because they lie behind the shutter walls or between the MSA
quadrants at this pointing. The maximum possible number of targets that could
theoretically be observed in one configuration, for the default 3-shutter slitlet, is
171 x 2/3 = 114. The first configuration in this test case has close to this number of
targets, which validates the use of the UDF-derived sample for a thorough assessment of
optimization strategies for large target sets.
In order to recover candidates that lie behind shutter walls, the center pointing or position
angle must be changed between configurations. A 3x3 grid of pointing coordinates with
step sizes of 0.3” in RA and 0.5” in DEC (roughly equal to the shutter pitch) increased
efficiency by about 20%: more than half of the total number of candidates within the
MSA FOV (395/770) can be observed with 4 configurations. The results are relatively
insensitive to the exact step size. The number of targets increases somewhat with the
number of grid points up to 9, then levels off with added grid points. Thus, to minimize
calculation time, a 3x3 grid is the best choice for pointing coordinate shifts. Similar
efficiencies are obtained by slightly varying the position angle rather than the center
pointing. For a step size of 1 degree in orientation over a set of 3 grid points centered on
the default value, a majority of candidates (394/770) can be observed with 4
configurations. Again, the numbers do not change significantly with step size or number
of grid points.
Larger center pointing or position angle step sizes are needed to recover candidates that
lie between the MSA quadrants at the default positioning. The best results are obtained
using a 3x3 grid with step size roughly equivalent to the size of the gap between MSA
quadrants. Using RA and DEC intervals of 20.1” and 36.2” (the small sub-arcsecond
additions prove to be helpful in shifting some targets that would otherwise always lie
behind shutter walls), 102 targets can be observed in the 1st configuration, 6
configurations are required to observe more than half of the candidate sample (534/1009),
and ~30 configurations are required to observe all of the candidates in the input table.
The cumulative distribution of this set of configurations is shown in Figure 2. Note that
pointing offsets greater than 20” between configurations may be imprecise enough to
require a new target acquisition. Similar results can be achieved by changing the position
angle while keeping the center pointing fixed, except that a few percent of the targets can
never be observed because they lie near the center of the MSA FOV. Since position
angle shifts do not generally yield significantly different results with rich candidate
samples, I do not consider them in any of the following test cases except for the sparse
target case (#6).
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Figure 2: The cumulative fraction of observed targets as a function of configuration number for various
test cases using the UDF-derived input sample. Black line: test case #1, ideal MSA with 20.1”x36.2”
pointing shifts; blue line: test case #2, including failed shutters; green line: test case #3, 2-shutter slitlet
pattern; solid and dashed red lines: test case #4 with dither offsets equal to 1 shutter width and the
detector gap, respectively.
Test case 2: same as 1, incorporating failed shutters
We know from ground testing of the flight quadrants that a non-negligible fraction of
shutters do not meet spec. Most are “failed closed”, including shutters that do not open
when commanded, those that have a 0 V mask applied as a result of electrical shorts (see
TR "MSA Short Detection and Mitigation" by Tumlinson), and those that have been
intentionally plugged during fabrication. A handful of shutters are “failed open”, either
subject to intermittent failure or having contrast ratios below the minimum requirement
of 2000. The failed open shutters are the most problematic, as they result in a spectrum
of whatever light (sky or random source) that falls into them that will interfere with a
science target spectrum in the same shutter row. For many programs, especially those
with faint targets, these affected rows should generally be avoided when placing targets
into shutters, although for flexibility's sake the user should have an override option. In
any case, the MSA tool must have the capability to track all failed shutters throughout the
mission.
For this (and each remaining) test case, I added failed shutter maps to the simulator.
These were taken directly from the MSA flight candidate quad test data generated by
GSFC, which included excel spreadsheets with the failed shutter locations. The simulator
takes this information and adjusts the candidate observability accordingly: no targets (or
associated sky) are allowed into any shutters that are either failed closed or in a row
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(across both quadrants) that contains a failed open shutter (again, this should be optional
in the tool). Using the optimal pointing iteration of a 3x3 grid of 20.1, 36.2” offsets, 80
targets can be observed in the 1st configuration, 8 configurations are required to observe
more than half of the total candidate sample (508/1009), and ~50 configurations are
required to observe all of the candidates. The cumulative distribution of this set of
configurations is shown in Figure 2. The effective observing efficiency drops by ~20%
from the ideal case; the failed open shutters affect about 10% of all shutter rows, with
many of these close enough that a full 3-shutter slitlet along a column cannot fit in
between them. In any given configuration, at most only a few percent of potentially
observable targets are affected by failed closed shutters.
Test case 3: same as 2, with 2-shutter slitlets
Many observers will want to use a different strategy for sky subtraction than the default
3-shutter slitlet. For example, observations in fields with bright targets where sky
subtraction is less important may benefit from fewer dedicated sky shutters or a different
distribution on the sky. This test case considers the simplest strategy, a 2-shutter slitlet
where one shutter can be used for the source and the adjacent shutter for sky. Using the
same optimal iteration scheme as in the first 2 cases, 118 targets can be observed in the
1st configuration, 5 configurations are required to observe more than half of the sample
(505/1009), and ~30 configurations are required to observe the entire sample. The
cumulative distribution of this set of configurations is shown in Figure 2. There is an
increase in observing efficiency of about 40% from the default slitlet case. This is
somewhat larger than the 30% one would naively expect given the difference in the
number of shutter rows required for each target, and occurs because the tolerance for
fitting targets between closely spaced rows affected by failed open shutters is lower.
Test case 4: same as 2, investigating effects of dither offsets
Most observing programs will require dithering of each target set, for example to improve
spectral sampling or to cover the gap between the NIRSpec FPAs. In the default case,
dithering can be accomplished simply by moving each target to a different shutter in its
slitlet, such that only 1 MSA configuration is necessary. This strategy compensates for
bad pixels, but does not necessarily provide optimal spectral sampling or fill in the gap
between the two detectors. Many observers will want to use larger dither offsets,
particularly in the dispersion direction, that will move targets into other shutters. In such
cases, a separate configuration will be needed for each dither position. As a preliminary
investigation on what effect this might have on observing efficiency, I simulated singledither observations in the following way. At each point in the 3x3 grid of center pointing
coordinates, the configuration of targets is first calculated as normal (the “primary”
position). Then, a second configuration is calculated at a user-specified offset from that
grid point (the “offset” position) using only the targets from the first configuration. Thus,
the same targets are observed in both configurations, except for those that happen to fall
outside of a shutter or the MSA FOV, or inside a failed shutter, at the offset position.
The grid point that yields the largest number of observable targets in the offset
configuration (since that number is always equal to or lower than the number of targets at
the primary position) is selected as the optimized observation. Figure 3 shows an
example of this process. Targets that are observed in both the primary and offset
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configurations are removed from the candidate list before proceeding to the next
iteration.
Figure 3: . Cartoon of a simulated optimization for a single-dithered observation. A 3x3 grid of center
pointing coordinates is constructed around the user-specified default pointing (shown in red). Each of
the 9 grid points is labeled in order, and the number of targets at each is indicated to the upper right (for
illustrative purposes only, this does not correspond to any specific test run). Starting at grid point 1, the
number of targets is calculated as normal - in this example, 52. Then, taking only those 52 targets as
input, the calculation is repeated at a position offset from grid point 1 by a user-specified “dither”; 49/52
are observable at the offset position. Next, the routine moves to grid point 2 at the primary position and
evaluates the full initial candidate sample (this time getting 69 targets), then moving to the offset position
(63/69 observable targets), and so on through all 9 grid points. The “optimized” observation is then
selected at the grid point that provides the largest number of targets at the offset position - in this case
grid point 6, shown in green, which yields 76 targets observed at both positions. Two MSA
configurations are returned, one at the primary pointing and the other at the offset pointing.
I evaluated 2 different dither offset combinations. The first was a one-shutter offset in
the dispersion direction (0.26” in the MSA plane), such as might be done to improve the
sampling of the line spread function. This case yielded 80 and 76 targets in the first set
of primary and offset configurations, respectively. A total of 9 target sets (18
configurations) were required to observe more than half the sample (545/1009). In most
cases, about 5% or less of targets placed in the primary configuration are not observable
in the offset configuration, mainly as a result of targets falling on failed closed shutters.
The second dither case simulated a dither offset to cover the gap between the NIRSpec
FPAs (17.94” in the dispersion direction). This case yielded 80 and 65 targets in the first
set of primary and offset configurations, respectively. A total of 11 target sets were
required to observe more than half the sample (510/1009). The decline in efficiency here
is largely a result of targets falling out of the MSA field of view at the offset position.
The cumulative distribution of targets for both of these dither offsets is shown in Figure
2. It should be noted that the optical distortion of the instrument was not included in the
simulator. Given current expectations, distortion may significantly reduce the efficiency
of the 17.9” dither observation by causing some targets to be unobservable in the second
configuration (depending on their location in the field of view). It should not be
important for sub-arcsecond dithers.
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Test case 5: same as 2, with different spatial distributions of candidates
centrally condensed cluster: I created an artificial candidate list using normallydistributed random numbers in order to simulate a centrally condensed stellar or galaxy
cluster. This candidate list contained 1000 objects spanning a region slightly larger than
the MSA FOV, with half of the candidates within a radius of about 55” from the cluster
center. Using the optimal pointing iteration of a 3x3 grid of 20.1”, 36.2” offsets, a
maximum of 64 targets can be observed in the 1st configuration, and 11 configurations
are needed to observe more than half of the sample (519/1000). These results indicate a
loss of efficiency of ~25% compared to the UDF case because the spatial distribution
results in more targets falling in between the MSA quadrants and more shutter row
overlap conflicts. I tried several different center pointing offsets in the iteration scheme
(including centering the cluster on one MSA quadrant), but none managed to improve the
statistics.
sparsely populated sample: For this case, I generated a candidate list of 25 objects using
uniformly-distributed random numbers. Using the optimal pointing iteration of a 3x3
grid of 20.1”, 36.2” offsets, a maximum of 7 targets can be observed in the 1st
configuration, 3 configurations are needed to observe at least half of the sample (16/25).
The relative efficiency is greater than in the case of the richer UDF sample, probably
because of fewer shutter row overlap conflicts. However, it is not possible to observe all
of the candidates with this iteration scheme; a relatively large fraction (six) could not be
placed into shutters. This is likely to be an undesirable outcome for observers with
similarly small candidate samples. In this case, varying the orientation along with the
center pointing provided a much better result: a 3x3x3 grid of 20.1” and 36.2” offsets and
2 degree shifts in orientation angle about zero resulted in 9 targets in the 1st configuration,
more than half of the sample can be observed with just 2 configurations (16/25), and the
entire sample can be done with 7 configurations.
Test case 6: same as 2, with prioritization
Most, if not all, observing programs will have a prioritized target sample. Thus, the
planning tool optimization must be able to incorporate candidate target priorities when
generating configurations. The simplest method would be to have a numeric ranking for
each candidate in the input table: 1=highest priority, 2=next highest priority, and so on
with as many levels as the user requires. The priority ranking can be used by the
planning tool in many ways; for the simulator, I included priority handling at several
steps in the optimization process. By default in all cases, when more than one candidate
is available for a given MSA shutter row, the code chooses the one with the highest
priority ranking. I also implemented an optional “brute force” algorithm where only
priority 1 candidates are considered in a first pass of the optimization, and then any
remaining empty shutter rows can be filled with available priority 2 candidates, followed
by priority 3 and so on through the user-specified minimum priority Npr. I further
included a priority weighting scheme for the selection of the “optimal” configuration in
the grid with the following options: 1) no weighting, simply find the configuration with
the largest number of targets regardless of priority ranking; 2) select the configuration
with the largest number of priority 1 targets; 3) select the configuration with the largest
number of targets of priority 1 through Npr.
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To test the efficiency of priority optimization, I ran the simulator using the brute force
iteration and two of the weighting schemes. Each candidate in the UDF table was
randomly assigned a priority ranking in the range 1 to 10, yielding roughly 100
candidates in each bin. Using Npr=2 and weighting scheme 1, a maximum of 71 targets
could be assigned to the 1st configuration, with 24/99 priority 1 and 11/100 priority 2; a
total of 9 configurations were required to observe more than half the sample (534/1009),
including a total of 83/99 priority 1 and 64/100 priority 2 targets. Using Npr=2 and
weighting scheme 3 (optimizing the number of priority 1 and 2 targets), the same results
were obtained for the 1st configuration, but only 8 configurations were required to
observe more than half of the sample (528/1009) with a total of 88/99 priority 1 and
76/100 priority 2 targets.
Case
Cand
1A
1B
1C
1D
2
3
4A
1009
1009
1009
1009
1009
1009
1009
4B
5A
1009
1000
5B
25
6A
1009
(99, 100)
1009
(99, 100)
6B
Targ
Set1
102
Targ
1/2
407
395
394
534
508
505
545
Config Config Fails Notes
1/2
All
5
0% 1 center
4
0% dx=0.3”, dy=0.5”
4
0% 1 center, 3 orients
102
6
30
0%
80
8
50
10%
118
5
50
10% 2-shutter slitlets
76
9
10% shutter dither
(0.26”)
65
510
11
10% gap dither (17.9”)
64
519
11
10% concentrated source
distribution
9
16
2
7
10% sparse sample, 3
orients
71
534
9
10% priorities, weight
(24,11) (83, 64)
scheme 1
71
528
8
10% priorities, weight
(24, 11) (88, 76)
scheme 3
Table 1: . Summary of results for the optimization test cases. The number of input candidates is given
in “Cand”. “Targ Set1” gives the number of targets in the first optimized configuration. “Targ 1/2”
gives the cumulative number of targets observed in the first “Config 1/2” configurations, the number of
configurations needed to observe more than half of all observable candidates. For test cases 6A and 6B,
the number of candidates or targets with priority 1 and 2 are also indicated in parentheses. The number
of configurations needed to observe all candidates, where calculated, is listed under “Config All”.
“Fails” indicates which cases included failed shutters and their approximate percentage of the total
number of shutters. Unless stated otherwise in the “Notes” column, all cases used the UDF-derived
candidate sample, 3-shutter slitlets, a 3x3 grid of center pointings with dx=20.1” and dy=36.2”, fixed
orient, and no dithers
4.0
Recommendations
I have investigated optimization strategies for the MSA planning tool using a simulator
written in IDL. The basic optimization maximizes the number of targets that can be
observed in a given MSA configuration. The actual observing efficiency (in terms of
number of targets per configuration) varies greatly with sky shutter configuration, dither
size/direction, number and location of failed shutters, and candidate density. From these
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results, I recommend the following features and operating parameters for the planning
tool:
•
•
•
•
•
•
The number of targets that can be observed in a given MSA configuration must be
optimized by using an iterative grid of varying center pointing coordinates and or
position angles. The user must be able to select the desired number of grid points
and the step size between points. The recommended parameters are a 3x3 grid of
pointing coordinates (with a user-supplied default pointing at the grid center), with
RA x DEC step sizes of 0.3”x0.5” (if the user does not care about candidates that
lie within the projected gaps between MSA quadrants) or 20.1”x36.2” (to recover
all candidates). Including a varying position angle within a few degrees greatly
improves results in the case of sparse targets.
Failed open and closed shutters must be tracked and updated. Targets and
associated sky must not be allowed into failed closed shutters. By default, targets
should not be allowed into any shutters in the same row as a failed open shutter in
R=1000 and 2700 modes; however, the user should be able to override this with a
warning that the overlapped target should be bright and no source except low sky
background should be in the failed open shutter. A more sophisticated checking
scheme should be implemented for prism mode, since spectral overlap occurs in
more limited circumstances.
The optimization must be able to account for dither offsets. The user must be able
to enter the desired number of offsets Noff and the offset size in arcseconds
(subject to single-observation constraints?). A total of Noff configurations will
then be required to observe a single set of targets, with some loss of efficiency
depending on the offset size. The optimization should be based on the grid point
that gives the maximum number of targets that are in all of the Noff configurations.
There must be a capability to read in target priorities from the input candidate
table, with the priority expressed as an integer value ranging from 1 (highest) to an
arbitrarily large number Npr. There should be an option to use target priority to
select among degenerate targets when spectral overlap from multiple targets in the
same shutter row is an issue. There should also be an option to use priorities as
part of the optimization routine, as described above in section 3, test case 6 (“brute
force” method).
A priority weighting scheme should be implemented where the “optimized”
configuration in the iteration grid is selected based on the total number of targets,
the number of priority 1 targets, or the number of targets with priority 1 to Npr .
A diagnostic plot summarizing target properties should be implemented. This
would depict the outline of a generic shutter with its surrounding inter-shutter bars
and open aperture, and contours of typical throughput and/or flux calibration
accuracy. The relative position of every target within its own shutter in the most
recently calculated configuration would be marked within the aperture plot using
symbol type and color to indicate properties such as priority, dither status (for
example, if the target would be unobservable in a dither offset configuration
because of a failed shutter), or possibly other user-defined criteria. Such a
diagnostic would help observers look for systematic effects like target position
biases and visualize the flux calibration accuracy that would be achieved with that
configuration.
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5.0
Further Study
There are a number of important details not addressed in this report that must be
considered before the final version of the planning tool is released. First, the optical
distortion across the NIRSpec field of view is non-negligible. A full treatment of the
distortion must be incorporated into the planning tool so that input targets can be
correctly matched to the projected shutter apertures. The tool must have the ability to
update the distortion parameters as the solution is refined during ground testing and
commissioning. Simulations including the distortion should also be run to test whether
large dither offsets will cause targets near the edge of the FOV to fall out of apertures.
Second, spectra in prism mode observations only extend about 32” in the dispersion
direction, and two open shutters per MSA row will not necessarily produce overlapping
spectra. Thus, the planning tool should prefer putting two non-overlapping prism spectra
in an MSA row to fitting only one prism spectrum in the middle row, as long as the open
shutters are sufficiently separated. Third, the target acquisition procedure must be
included: the planning tool must have an interface to allow the user to select the desired
set of reference stars for each optimized configuration. This interface must take into
account the failed closed shutter locations to ensure that all reference stars will be seen in
the external acquisition image. On the other hand, there is considerable uncertainty in
where reference stars will be positioned before target acquisition. If there are many more
failed closed shutters than currently expected, it may be preferable to ignore shutter status
and rely on outlier rejection to handle the case of closed shutters. An optimal procedure
for target acquisition planning requires more detailed consideration.
6.0
References
Tumlinson, J. 2009, "NIRSpec MSA Short Detection and Mitigation", JWST-STScI001736
Valenti, J., Boeker, T., de Marchi, G., Donaldson, T., Downes, R., Peterson, K., Regan,
M., Whitman, R. 2006, “Features of the Software Tool Used to Define
Observations with the NIRSpec Microshutter Array (MSA)”, JWST-STScI000758
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Appendix 1.
Prioritized List of Desired MSA Tool Improvements
For completeness, attached below is the detailed list (edited slightly) of desired planning
tool features and improvements produced by the NIRSpec PPS/templates team after
several months of discussions. Each item has an associated implementation priority
indicated in red. These discussions included WIT/NIRSpec members D. Karakla, T.
Beck, J. Tumlinson, and J. Muzerolle, WIT/PPS lead B. Sparks, and APT developers T.
Donaldson and R. Douglas. The list was compiled by D. Karakla.
Optimization:
1. Need an optimization algorithm to translate and rotate to find the best fit to all
sources (to center sources in the shutters). HIGH
2. Pending distortion analysis, routine needs to factor in the geometric distortion from
the sky to the MSA to know which shutters should be opened. HIGH
3. Routine needs to avoid stuck closed shutters and entire rows where an open stuck
shutter occurs. Need to avoid same row across the 2 quads. (PRISM+CLEAR setting
is an exception, will need column-specific limits that will depend on the TBD length
of spectra. Even with PRISM though, spectra from the right side of Q3, for example,
can overlap with spectra on left side of Q2, so we need to be careful to disallow that).
HIGH
4. The routine should factor in the distortion from the MSA to the detector to be able to
avoid rows with spectra from other shutters or slits. MEDIUM
5. For phase 2 proposal planning, there should be limits imposed on orient angles (e.g.
within +-5 deg of a pre-planned designated PHASE I orient, and ORIENT should be
fixed for all visits in an observation). MEDIUM
6. After the optimal location is determined, only allow moves by an integer number of
shutters. This might be useful when replanning visits on the fly if new failed open
shutters are found prior to MSA observations but after NIRCAM pre-images. OMIT?
Guiding and Acquisition Concerns:
•
MSA tool needs to be able to "see" (obtain within the 4 quads) all the reference
stars that will be used for target acquisition (For ALL target acqs needed to
complete an observation). So the MSA needs to cover all these stars at *every
pointing* used in the visit. Even missing one of the 8-20 ref stars is a failure.
•
There are 2 reasons a new TA would be needed: TA failed due to too large an rms
error in reference star residuals (e.g. caused by hot pixels or reference star
variation from pre-imaging?), or the high-gain antenna pointing time limit (10
ksec) has been exceeded (by full set of science observations?).
This may need more study:
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*** Potential solution: TA done at (0,0) position of MSA, then an offset to new pointing
to observe, then back to (0,0), then on to next offset position... This might relieve the
need to have all TA stars visible at all pointings in the observation!
- Spatial dithers which bridge the quad gap may require new guide stars. If so, they will
have to be put into a new visit (as part of the same observation, though).
For the reasons described above,
1. MSA tool or APT will need to ensure that TA covers all reference stars inside
useful area of MSA, and that they fall into permanently open or unstuck shutters.
HIGH
2. APT may need to require new TA whenever a new pointing (e.g. a move across
the quad gap) would violate the rms error accuracy needed for accurate
placement of shutters. MEDIUM
3. MSA tool will need to keep track of observation exposure times and force a
break into a new visit if 10 ksec exceeded. Will also require a new TA. IS this
one for APT or MSA tool? MEDIUM
4. Small addition to the above rule. It will also have to keep track of visit durations
and break into multiple visits if the 1 day extent is exceeded. This one may also
be for APT rather than MSA Tool. MEDIUM
5. MSA tool will need to keep track of guide stars to be able to decide if a new visit
is needed. MEDIUM
Configuration files:
1. Need to have a way to create new MSA source/target slits in Aladin (i.e. add
sources to the catalog interactively) and add them to a new or existing
configuration file or source list. HIGH
2. MSA Tool needs to be able to read in and write out configuration files. User
should be able to input an existing configuration file and display it as a pane in the
Aladin image stack. Aladin should be able to display locations of target and
background shutters and the associated Orient (and designated priorities or target
types, if implemented). This will be useful for comparison and refinement by
hand. HIGH
3. An input config file should include the known stuck (open and closed) shutters.
A stuck shutter Mask. It's possible that the stuck shutters will have changed since
last optimizing the configuration file. Masks should not add much size to the file,
though. HIGH
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4. Need to be able to recall shutter status from when the config file was created, to
determine if shutter status changed prior to observation. Want to take into account
new stuck shutters (open and closed) if/when updating a config file for use in
planning a new observation of the same region. (Config file update frequency is
TBD.) HIGH
5. Need to be able to save results for shutter selection to a shutter config file when
done, along with the masks, and easily monitor or track this. HIGH
Customizing shutter selections:
1. Highlighting the sources (using shift-select method) in the MSA Source Details
window will display sources separately in Aladin window. This is a very nice
feature, to be able to see and modify the shutters interactively. But, the tool can
only handle 16 sub-windows at once, at most. Would like to be able to display all
of them in some fixed size windows and scroll among them. MEDIUM
2. Need an easier way to change or select target and background shutters off and on
in the Aladin window(s) for each source or a set of sources. MEDIUM
a. Would like to select a set of sources in the source details list and using an
"apply to all" feature, change the type of shutter pattern from a pull down
menu. (either default, detatched, slit, custom, …)
b. When choosing custom shutter patterns, the current method works on one
source at a time, and user must click to indicate whether target or background
shutters will be changed. Should be able to select target shutters for an entire
set or subset of sources in the MSA source details list without having to
answer same question for each source. Want to modify target shutters for
many sources at once by clicking left mouse button on images of each source.
Then, select background mode (or use a different mouse button), and click to
select background shutters for each source in the Aladin windows, then select
“done” when complete to commit changes back to the Source Details window.
This has to take into account the one target per row constraint – if changing
the background shutter pattern would violate this, do not allow, or at least
provide a warning.
c. Alternatively, could have a default target-only shutter (with no background);
user can then modify for whole set of sources to change target shutters, then
commit these, then select background mode and choose as default one shutter
adjacent to each target string of shutters, or skip one shutter for detached
background shutters to apply to all selected sources at once.
3. In the MSA Source Details window, instead of presenting source positions in
percent values in X and Y, change this so that the position of the centroid of the
target is shown in milli-arcseconds from the center of the shutter in X and Y. The
X and Y values then would be positive or negative numbers, depending on the
direction away from the center of the shutter. (e.g. xposition =+55 mas, ypos=Check with the JWST SOCCER Database at: http://soccer.stsci.edu/DmsProdAgile/PLMServlet
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110mas from shutter center.) Need to be able to order targets by any of these
independently. HIGH
4. Would like also an "extended detached" pattern with 3 shutters for target, and a
detached background shutter on both sides. LOW
Visualization:
1. MSA analysis tool: add a 4th category of source type for sources that are located
behind a shutter wall (mark with blue?). MEDIUM
2. Mark (or make visible to the tool user) the positions of the fixed slits to avoid
bright targets from accidentally falling into them, or provide a warning if this
would occur. Also mark IFU aperture. HIGH
3. Aladin "postage stamp" or sub-windows should be labeled with source ID(s) that
match row numbers or target id in the MSA Source Details window, so its easy to
see which are which. Will also need to add row numbers to MSA Source Details
window. HIGH
4. Label quads 1 through 4 on FOV display in Aladin, and maybe indicate the
dispersion and spatial directions. LOW
Organization:
1. The current version of the tool does not handle MSA targets separately from the
pointing target. Also, each time sources are selected in Aladin and sent back to
APT proposal, they are simply added to the target list. APT quickly gets
overwhelmed. The same source can appear in the target list several times since
there is no attempt to weed out repeats. MSA tool should store MSA sources
separately from pointing targets, either separately for each config, or in a common
area from which each config may draw upon. If the latter is adopted, then there
needs to be some logic to determine if an added source already exists in the list to
prevent repeats. HIGH
2. The tool needs to be able to handle more than 999 sources, which seems to be the
current limit. HIGH
3. Need a convenient way to keep track of which config is associated with which
sources, so that it is easy to identify the REMAINING sources in a large set which
have not already been captured in a previously-designed config in the proposal.
This mechanism should also allow for observation of the same sources in different
configs, though, as well. Want to be able to graphically see different config
source lists as separate panes ( would be useful to be able to view and identify
sources from one or more existing configs plus distinguish all remaining sources
when designing subsequent visits). HIGH
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4. Should be able to highlight a bunch of sources at once on the "MSA Source
Details" window without individually having to click on each one. We want to
mark or unmark them all at once for use in the Aladin window, or for
setting/changing their priority, or to make other changes to as a set. HIGH
5. Implement target priorities. HIGH
For example…
- Optimize pointing and orient for high priority list. In the most limited sense,
this info could be used to help determine which of two sources with overlapping
spectra should be kept. Make a second pass for priority 2, a third for priority 3, etc.
- Visually mark high priority sources when user is choosing shutters.
Miscellaneous:
1. Want to be able to commit an ORIENT selected interactively in Aladin back to
the proposal (as a visit level requirement). NOTE that there is a draft report by
Bill Sparks which recommends adding an aperture-specific position angle to APT
templates. If implemented, we will probably want the user to enter the PA (with
respect to MSA center), and have APT automatically calculate “ORIENT”, to
make it easier for the user. HIGH
2. Fix sorting in MSA Source Details window : (for object id, I get: 9834,
9765,*968*, 9437...). Sorting in other columns also not working as expected.
MEDIUM
3. Want to be able to tweak positions of sources interactively using Aladin mouse
and commit changes back to source catalog for later pointing or other
optimization routines. MSA source analysis needs to keep track if new sources are
added or positions are changed so that user is alerted that shutter optimization
analysis is outdated. This will be useful for extended sources – e.g. galaxy center
versus one of its HII regions. MEDIUM
4. Implement object types. [Why? E.g. for setting default shutters.] For high versus
low redshift sources, or blue versus red galaxies, also could report back statistics
on them once config is set. LOW
Appendix 2.
Optimization and Simulator Code
See the associated zip file, which contains the IDL source code plus the UDF-derived
prioritized candidate table used for most of the test cases described here. Note that the
failed shutter maps used by the code are not included as they are ITAR-restricted. These
can be obtained from the author upon request.
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