Instrument Science Report ACS 2000-03
Software tools for ACS:
Geometrical Issues and Overall
Software Tool Development
W.B. Sparks, R. Jedrzejewski, M. Clampin, R.C. Bohlin.
June 8, 2000
ABSTRACT
We describe the issues relating to internal geometrical distortions in the ACS. A software
tool development route is outlined that will lead to provision of rectified ACS associations.
We describe other software tool development activities, including pipeline enhancement to
include postflash and ramp filter observation calibration, as well as stand-alone tools.
I. Software Tools Overview
Software tools are required in support of an HST instrument in order to (i) simulate observations with the instrument (ii) access, visualize and manipulate data arrays (iii) provide
calibration reference files in support of the calibration pipeline for the instrument (iv) provide the calibration of the instrument, i.e. removal of the instrument specific signatures
from the data, through the calibration pipeline itself and in stand-alone mode for more
complex operations (v) provide analysis tools that enhance the scientific usefulness of the
data and allow scientific measurements to be made. Here we outline the desired software
development for ACS and discuss the issues relating to each item. The present ACS
pipeline operations are described in ACS ISRs 99-03 (Hack), 99-04 (Mutchler et al) and
99-08 (Hack).
Copyright© 1999 The Association of Universities for Research in Astronomy, Inc. All Rights Reserved.
Instrument Science Report ACS 2000-03
II. The Geometric Issues
ACS has severe distortions in mapping of positions in pixel coordinates to a rectified grid,
of order 15% in terms of pixel area projected onto sky. WFC3 will have a similar level of
distortion, which is much larger than for existing instruments. There are consequences for:
•
pointing control
•
astrometry
•
photometry
ACS images “look” distorted, Fig. 1. Much of the anticipated ACS science requires accurate shape and isophotal measurements that are much more straightforward on a rectified,
well-sampled image, and obviously photometric fidelity is crucial. Hence, there is likely to
be a demand for an image rectification stage. Since there are reflective elements only, we
do not anticipate any color dependency for the case of direct imaging observations.
Most obviously, correction of relative positions requires good knowledge of the internal
distortions. Less obviously, photometry is affected as a consequence of pixel size changes
(projected onto the sky) across the field of view. Point sources and extended sources,
folded together with the flat-fielding strategy adopted, can lead to misleading results in
these circumstances. Finally, measurement of the shape of a target depends on both the
positional mapping from the detected frame to the sky frame and also on the pixel size
variations, which influences apparent isophotal levels. An observed flat-field has more relative flux for bigger pixels, as does the sky, however a point source has the same amount
of total flux irrespective of the pixel-area projected on the sky. Hence, flattening with an
as-observed (e.g. sky flat) flat-field gives a flat sky but modifes star fluxes by the changed
pixel area. Correction, in principle, can be made for the changed pixel area, to rectify the
stellar fluxes, but then the sky has gradients imprinted that show the pixel area changes.
We also anticipate that an ACS image sequence will frequently be “dithered”. That is, several images will be taken one after the other with the telescope pointing shifted by a small
amount between images. This is done to help eliminate the effects of bad pixels and to
obtain additional information on image structure in cases where the images are undersampled. If the maneuveurs are small (i) the telescope will remain on the same guide stars (ii)
the data form an “association” in the archive. (Larger telescope moves are referred to as
“mosaics” rather than “dithers”.) Combination of dithered (or mosaiced) data requires
knowledge of the geometrical distortions and of the convention employed in flat-fielding
the data. Current dithering software (algorithmically, at least) is well-capable of taking
account of these effects correctly.
Currently the ACS pipeline processing stops at the point where individual images have
been flat-fielded, with up to three types of flat-field allowed (pixel-to-pixel, or P-flat, large
scale or L-flat and delta flats to allow for time variability). Here we describe a path
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Instrument Science Report ACS 2000-03
towards attaining a goal of providing as the final ACS pipeline product a single rectified
photometrically accurate image per input association.
Stand-alone tool development that will lead to this single image is described, and also the
tools needed to process non-associated (mosaiced) data.
Recommendations and Implied Software Development: Geometry.
Storing the information
Geometric distortions are conceptually and physically completely different from sensitivity variations due to different pixel-to-pixel response. They interact with an observation in
different ways. They can both be calibrated independently.
•
Our first recommendation is that the geometric calibration be kept in a single place,
utilizing the placeholder “IDC” file (Image Distortion Correction, or GEOFILE in
ISR 99-08). Priority 1.
•
Additionally, a “metric” equivalent tool to provide RA/Dec from image x,y coordinates and vice versa, should be developed to connect the World coordinate system of
the image headers to the known internal distortions (the IDC file). Priority 2.
•
There are potentially several conventions available. In particular the SIAF and drizzle
software use similar but not identical conventions. A utility to move between conventions and to provide inverse transformations is needed. Priority 1.
Flat field strategies
There are basically two options (for straightforward imaging data): (i) divide data by an
“as observed” flat-field without any allowance for pixel size changes, such as a sky-flat, or
(ii) correct only for detector sensitivity variations so that the same number of total counts
represents the same flux everywhere.
A single pixel in the raw flat changes in area on the sky by about +/-10% (19% peak to
peak; pixel sizes differ from 0.90 to 1.07 times the central in WFC). If you flatten an
image with such a flat, the same star will, roughly, have an apparent brightness change
equivalent to the changing pixel size. An image flat-fielded in this way is essentially a
“surface brightness” image, which has pitfalls in a complex partially undersampled field.
This is method (i), the “surface brightness” method of flat-fielding, or “LPG” in the notation of Bohlin et al ACS/ISR 99-01.
To convert to a “flux per pixel” image, method (ii), which is necessary if photometric measurements are to be made on stars in the field, it is necessary to multiply the surface
brightness image by the relative pixel size, G. In principle, the flat-field reference file itself
could be manipulated according to the relative pixel size, however that introduces an
undesirable dependency of one calibration file on another (the G-flat on the IDC file).
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Instrument Science Report ACS 2000-03
•
Rather than correct for the pixel size immediately after flat-fielding, and thereby
imprinting an apparent surface brightness gradient on all ACS images, and since the
subsequent software tools are set up to deal with surface-brightness data, we recommend that the data be corrected only with an as-observed flat-field, such as a sky-flat.
•
We urge that warnings be provided about the dangers of using such data scientifically
(astrometry, photometry). It is for quick-look purposes only.
•
Given the need for photometric testing and testing of the accuracy of geometric correction, our second specific software tool request is for a tool to provide the pixel area
correction to flat-fielded data. Priority 1.
The pixel area is given by the determinant of the Jacobian of the transformation between
coordinate systems; see Appendix.
Correcting for Distortion and Combining Images
Much basic astronomy including measurement of anything relating to isophotal parameters, size, shape, quantitative morphology (e.g. a surface brightness profile), comparative
morphology (e.g. overlaying optical and radio data) and position needs to be carried out
on an image which has been corrected for the geometrical distortions that the camera
introduced. If the rectification scheme allows correctly for the modulated pixel size, then it
is straightforward to ensure the photometric fidelity of the final product. A final image
which is photometrically uniform in its response and geometrically rectified is the obvious
scientifically useful data product which we should aim to provide.
Also, a large fraction of ACS observations are likely to be dithered or mosaiced. There
already exist software techniques to combine such data, the dither package of stsdas, and
in particular drizzle. This code of necessity and from the outset is well-capable of dealing
with internal geometrical distortions. It may be used simply to geometrically rectify a single image with the appropriate parameter set (pixfrac=1), or else it may be used to
geometrically rectify multiple images, resampling onto a finer grid, and combine those
multiple images into a single rectified, photometrically useful image. (An iterative stage is
usually needed to identify and eliminate cosmic rays.) Since the HST observing strategy at
Phase 2 is also designed to accomodate this mode of operation straightforwardly using the
DITHER patterns for small offsets, we wish to move towards a pipeline implementation of
this image combination option. It is also possible to MOSAIC images to cover a larger
field of view, but such mosaics will typically not use the same guide stars and will not be
“associated” in the pipeline or archive.
Hence our route towards final implementation is as follows:
•
It is essential that by launch we have the stand-alone tools needed to combine a set of
ACS images that are shifted in pointing position from one another. The primary combination tool will be “drizzle”, or an upgraded version based on that task, which will also
be used for single image geometric and photometric rectification. The task should be
able to operate from both a user supplied table of relative offsets, and from the HST
pointing information. Priority 1.
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Instrument Science Report ACS 2000-03
•
Other appropriate utilities in the dither package, such as blot to simulate raw data,
should be checked for consistency with ACS data and fully functional in stand-alone
mode by launch. Priority 2.
•
In the case of single images, or CR-SPLIT images at a single pointing, provide as a
pipeline product a geometrically rectified, photometrically uniform image. For consistency with the next bullet, there is good reason to use drizzle, or its equivalent, to perform this operation. This may be implemented once confidence is gained in the
robustness of the task and ahead of the use of drizzle with multiple images since
parameter selection is less critical. Priority 1.
•
For multiple images, a stand-alone software tool to determine the relative offsets will
be required. The cross-correlation strategy, e.g. as employed by calnicb, should serve
as a model for this task. (Cross-correlation tools are also to be found in dither and fourier.) Priority 1.5.
•
Given the stand-alone combination tool (drizzle, first bullet), and given the confidence
developed through testing and experience, we urge that in the case of associated data
only, i.e. DITHER data, the image combination be implemented in the ACS pipeline.
HST pointing information only should be used to estimate the relative offsets in an initial implementation. Priority 1.
Any image rectification strategy must ensure correct treatement of the photometry such
that in the final data product, a star of given flux will have the same apparent brightness
anywhere in the field.
The final geometrically corrected product will appear as a single image rather than multiple imsets, or FITS extensions. In the case of single pointing, the sampling will be
essentially the same as the detector. For DITHER data we expect to output a more finely
sampled image (exact value to be determined from simulation and experience, but probably in the range 1.5 to 2).
In order to combine any sequence of images, it is necessary to normalize by the exposure
times of the individual input images. The concept of a single exposure time is no longer
valid and an exposure time image should be generated. By default, we assume that the output product will have units of “count rate” following calnicb and current drizzle
implementation options. The usual flux calibration header keywords (already present) will
allow straightforward absolute calibration of the count-rate data.
An interesting alternative may be to take the next step and instead of count-rate, provide a
flux calibrated image. Micro-Jansky would be an appropriate unit for typical ACS observations; V=28 is 0.02 microJy for reference.
Error analysis for dithered data
The variance images of dithered data become more complex, as spatially dependent
smoothing has been applied to the data, familiar to FOC observers as the “thumbprint”
noise pattern. Hence, while variances can easily be calculated, adjacent pixels are no
longer independent and covariances exist. The issue is whether this is a concern, or is the
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Instrument Science Report ACS 2000-03
variance information sufficient? Do we need to incorporate a description of the dependencies between pixels? This can lead to a preference for working in the unrectified domain as
the error statistics are more tractable. We propose that as a default path, we perform a
straightforward variance calculation and provide the usual error, or uncertainty, image
without provision for the covariance or pixel-to-pixel dependence of errors.
III. Software tools in Other Areas
Postflash correction (pipeline)
Concerns about the degradation of charge transfer efficiency (CTE) have resulted in a
hardware modification to ACS which is the inclusion of a postflash capability. It will be
necessary to subtract off the “pedestal” of post-illumination in the pipeline. The postflash
illumination pattern will be strongly non-uniform, hence it is highly desirable that good S/
N reference files be available to support this capability. Priority 2.
Ramp filter flat-field tools
Calibration of ramp filter data is not trivial. Conceptually, the process may be envisaged as
a two-stage one in which firstly, the data are flat-fielded in such a way as to enable continuum subtraction to be carried out, and secondly, the resulting monochromatic data are
flux-calibrated to correct for the changing transmission, or sensitivity, around the field of
view, knowing (or assuming) the wavelength of the monochromatic data. These tools have
not been implemented for WFPC2, however there the ramp filter field of view is so small
that an essentially point-source approach is tractable. ACS ramp filter observations cover
out to about 70 arcsec, by contrast, and hence tools to correct and manipulate the full area
of an ACS ramp filter observation are required for the data analysis stage.
Ramp filter flat-fielding
Ramp filter flat-fielding requires a tool to interpolate a flat-field from a data cube of monochromatic (or at least flats of known central wavelength) full-field flats at selected
wavlengths. The flat-field strategy is discussed Bohlin et al ACS ISR 99-01. The filter
position, determined by the wavelength specified by the observer, gives a mapping for a
specific image between position in the field and wavelength. The flat-field data cube
allows that information to be used to make an interpolated flat-field value at each pixel.
This is the appropriate flat field for a continuum source, presumed to have no strong features across the ramp bandpass and is appropriate for a proper continuum subtraction.
Note that a “delta flat” may be needed if high frequency spatial structure is present on the
flat field due to dust on the filter. Such features would appear in different places depending
on the filter rotation.
Development of this tool should initially be a stand-alone version. It should be tested with
ground-based calibration data prior to implementation in the pipeline. The data cube may
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Instrument Science Report ACS 2000-03
be either (i) a dedicated monochromatic data cube or (ii) the suite of flat-fields delivered as
reference files, with a look-up-table giving the suitable entries and their wavelengths. The
goals should be to implement this in the pipeline. Priority 2.
Flux calibration of ramp filter data
An extended monochromatic source image is the expected result of a typical ramp filter
observation following continuum subtraction. Continuum subtraction can be a rather specialized operation, so we do not envisage including it in the pipeline. Hence, we cannot
include the subsequent step of flux calibration in the pipeline over an extended area. We do
expect to provide flux calibration keywords that will be valid for the specified wavelength
of hte observation, A stand-alone utility interfacing with the synphot library of transmission curves will in addition enable an areal flux calibration to be carried out.
If the source is monochromatic and well centered in the ramp filter (spectrally) at the center of the aperture, then as one moves away from the aperture center, the response curve of
the ramp shifts in such a way that the source wavelength is no longer central. Eventually,
the ramp filter response moves far enough that the source is completely out of the bandpass. Any given ramp filter position may be thought of as providing a unique throughput
curve at each location in the image. Hence, knowing the wavelength of the source, it is
straightforward to flux calibrate using standard synphot tools. However, since this needs to
be done at every pixel, it requires a software tool to (i) at each position x,y generate the
throughput curve given the ramp filter position (ii) use the throughput curve to determine
the absolute sensitivity at the source (or externally specified) wavelength (iii) hence provide a flux calibrated image by utilizing the absolute sensitivity at each x,y position.
Optional output images would include a central wavelength map and a sensitivity map,
and an optional input wavelength-image instead of a single wavelength would be a useful
enhancement. An interim utility will be to provide information on the region within which
the throughput of the ramp is within, say, plus or minus 1%, 2% etc. of the central value.
By default, one would assume the input wavelength specified in the observation. This may
be overridden if the observer knows more about the wavelength of the source, or if multiple wavelengths are present, or if the wavelength distribution is known. Priority 3.
FPR and Cosmic Ray analysis tools for CTE.
The observed CTE degradation of WFPC2 and STIS together with the large format of the
ACS CCDs has given rise to great concern over the rate of CTE decline in ACS, particularly the WFC. Hence, CTE monitoring will form an important part of the ACS calibration
plan.
Analysis tools to facilitiate that monitoring will be helpful once the program is under way.
There are currently two options: (i) Mike Jones has designed an engineering program first
pixel response test to estimate CTE (ii) Also, Riess WFPC2 ISR 99-04 describes a technique to measure CTE from cosmic rays in dark frames.
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Instrument Science Report ACS 2000-03
The ACS group will utilise these techniques to monitor CTE and, if possible, automate the
measurement process given experience with on-orbit data. Such a process may become
straightforward with an application tool. Priority 3.5.
Polarization analysis tool
ACS has a high quality, robust imaging polarimetry capability that should lend itself well
to relatively automatic data processing, unlike previous instruments such as WFPC2 or
NICMOS where the polarization analysis is complex. Although a number of private software packages are available, there is as yet still no iraf or stsdas standard suite of imaging
polarization analysis software. The instruments with such a capability are ACS, NICMOS,
WFPC2 and the FOC, hence although the polarization community of observers is quite
small, there is signficant across-instrument relevance and interst in a general package. The
techniques are known and documented in Sparks and Axon (1999) PASP, 111, 1298. Provision of a general polarization analysis tool is entirely feasible. Priority 3.
Tools for coronagraphic analysis
ACS has a powerful coronagraphic capability that will allow faint source to be seen very
close to bright stars and quasars. In order to process data of this form, we will require techniques to determine azimuthal profiles using a variety of methods (mean, median, mode
for example), plus construction of model profiles utilising the azimuthal averaging information. Priority 3.
Contingency time
Contingency time must be allowed for, since with a new instrument, it is almost always the
case that unforeseen developments lead to new, unanticipated requirements in the area of
software support. Hands-on experience with real data could change priorities and introduce new needs, potentially at short notice and potentially as a matter of urgency.
IV. Tools which are close to completion and non-SSG tools
ACS quick display tools
A utility to examine the multiple imsets of an ACS image, and to provide a quick-look correction for the geometric distortion on display, optionally. This task has been completed
and is in test.
Quick-look products
Design carried out by Suchkov ACS ISR 99-10; coding close to completion; in testing.
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Instrument Science Report ACS 2000-03
ACS ETC
Complete basic functionality of ACS ETC (Bohlin/Shaw/Boffi efforts ongoing)
PSF modelling
Primarily oversight of the Tiny Tim implementation for ACS; Krist.
Extracted spectra for grisms
ST-ECF have agreed to collaborate on development of grism spectra analysis tools, and to
assume formal responsibility for support of the software they provide.
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Instrument Science Report ACS 2000-03
Summary
* "Launch" below implies fully developed and tested in advance of actual
launch in order that use may be made of the software from the outset of
the science mission.
Item
Timescale
Priority
Pipeline?
May 00
1
yes
“metric”: convert x,y to RA,Dec
2
no
drizzle coefficients from IDC
1
yes
May/June 00
1
no
Launch
1
no
2
no
1.5
no
provide rectification for single pointing in pipeline
1
yes
image combination of dithers (HST pointing info)
1
yes
postflash subtraction
2
yes
Ramp filter flat-field interpolation
2
yes
Ramp filter flux calibration
3
no
Establish/deliver IDC file
make pixel area map from IDC
stand-alone drizzle functionality
- HST pointing information
- user-supplied tables of pointing data
(check functionality of dither package)
measure image shifts (cross-correlation)
Launch
Cosmic ray tools
3.5
Polarization analysis tool
3
Coronagraphic analysis tool
3
Contingency time
ACS quick display
1
in testing
Quick-look PDF products
1
in testing
ACS ETC
1
Bohlin/Shaw/
Boffi
PSF modelling
1
Krist
Extracted spectra for grisms
1
STECF
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Instrument Science Report ACS 2000-03
APPENDIX: Pixel Area Correction
If x′ = fx(x, y), y′ = fy(x, y) defines two functions that map coordinate frame (x, y) into
coordinate frame (x′, y′), then if a pixel (assumed small) has area A in (x, y) at (x, y), it
will have area
∂f y ∂f x
∂f x ∂f
A′ = A ⋅  -------- ⋅ -------y- – -------- ⋅ -------- = A ⋅ J
 ∂x ∂y
∂x ∂y 
in (x′, y′) at (x′, y′). Or,
A = A′ ⁄ J
If (x, y) is the observed frame, and (x′, y′) is the rectified frame, then in the rectified frame,
all pixels have the same area A′ = 1. Hence, at (x, y), the area of the pixel A(x, y) is
A = 1⁄ J
and the functions fx and fy are the “forward” transformations from observed to rectified
planes. That is, a unit sized pixel in the output image has area A in the input image, in
units of the input pixel size, and so the actual area of the input pixel A″ in units of the output pixel size is
A″=1/ A = J
In the polynomial SIAF formalism we adopt initially, the partial derivatives may be calculated analytically.
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Instrument Science Report ACS 2000-03
Figure 1. Image taken with HRC plus coronagraphic optics, showing on the left the raw,
geometrically distorted image and on the right for comparison, the image rectified with an
initial set of distortion coefficients. Note that the coronagraphic holes appear much more
circular in the corrected image.
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