j8m81cd9q_flt.fits j8m824toq_flt.fits j8m84aqkq_flt.fits j8m851tmq_flt.fitsThe dispersed images observed with the G800L grism are:
j8m820leq_flt.fits j8m820llq_flt.fits j8m820lrq_flt.fits j8m820m4q_flt.fits j8m822q0q_flt.fits j8m822q4q_flt.fits j8m822qbq_flt.fits j8m822qhq_flt.fitsThe data set presented here is in the HST archive. It has been taken as part of the ACS/HRC Parallels program to the ACS Ultra Deep Field. Moreover these images are also part of the test data for grism observations (see Chapt. 2.5).
The grism/prism image combination is done for two reasons:
The combined direct image will be used to create a master catalogue with SExtractor. The master catalogue will then be projected back (see Chapt. 3.2.3) to generate Input Object Lists for each image in the MultiDrizzle combination to be used in the aXe reduction. Figure 3.1 shows an example of a combined direct image (left) and a combined grism image (right).
It is also possible to use other programs to identify cosmic ray hits on
the grism/prism images. Then the information on the cosmics must be transported
into the dq-extension of the corresponding flt-image.
aXe can exclude flagged pixels in the dq-extention from the reduction.
In the dq-extention, cosmic ray affected pixels should be marked
by adding the appropriate dq-flag 4096 (see ACS Data handbook) to the
original dq value.
For grism images it is favourable (see Chapt. 3.2.3) to combine the direct and the grism images such that the final, MultiDrizzled images have the same coordinate system. This means that each pixel represents the same position on the sky on both the combined direct as well as the combined grism image. The user can control this by e.g. specifying the identical center position and image size in the MultiDrizzle runs. The images in Fig. 3.1 fulfill this condition.
The master catalogue must contain all columns which are necessary for the spectral extraction with aXe (see format description in Chapt. 7.4). The first few lines of the master catalogue f555w_drz.cat extracted from the direct image in Fig. 3.1 are:
# 1 NUMBER Running object number # 2 X_IMAGE Object position along x [pixel] # 3 Y_IMAGE Object position along y [pixel] # 4 X_WORLD Barycenter position along world x axis [deg] # 5 Y_WORLD Barycenter position along world y axis [deg] # 6 A_IMAGE Profile RMS along major axis [pixel] # 7 B_IMAGE Profile RMS along minor axis [pixel] # 8 THETA_IMAGE Position angle (CCW/x) [deg] # 9 A_WORLD Profile RMS along major axis (world units) [deg] # 10 B_WORLD Profile RMS along minor axis (world units) [deg] # 11 THETA_WORLD Position angle (CCW/world-x) [deg] # 12 MAG_F555W Kron-like elliptical aperture magnitude [mag] 1 2116.6 815.9 5.322e+01 -2.781e+01 14.669 3.407 -79.3 1.0e-04 2.5e-05 -45.4 23.0 2 1463.7 740.1 5.322e+01 -2.781e+01 1.981 1.355 -84.5 1.3e-05 9.4e-06 -42.8 26.1 3 850.8 752.1 5.321e+01 -2.782e+01 1.877 1.749 21.9 1.2e-05 1.2e-05 37.9 24.6 4 1999.1 735.0 5.322e+01 -2.781e+01 0.952 0.465 -52.7 6.0e-06 4.1e-06 -67.4 28.0 5 760.5 761.5 5.321e+01 -2.782e+01 2.268 1.375 -54.4 1.4e-05 1.0e-05 -65.2 26.2 6 969.0 826.9 5.322e+01 -2.782e+01 3.863 1.672 37.6 2.4e-05 1.5e-05 22.2 25.0 7 781.3 831.3 5.322e+01 -2.782e+01 4.455 2.084 -58.9 2.9e-05 1.7e-05 -59.9 25.5 8 976.5 826.2 5.322e+01 -2.782e+01 2.410 0.839 -86.7 1.6e-05 5.7e-06 -41.6 26.3 9 1231.5 836.1 5.322e+01 -2.781e+01 2.522 1.177 -65.9 1.6e-05 9.3e-06 -53.8 25.9 10 981.5 834.9 5.322e+01 -2.782e+01 2.467 1.151 28.3 1.6e-05 9.5e-06 32.7 26.6In the master catalogue the original column name MAG_AUTO was changed to MAG_F555W, a column name format which indicates the filter wavelength (nm, see Chapt. 7.4). This format allows a quantitative contamination estimate with the Gaussian emission model and the computation of optimal weights.
The task iolprep searches in the header of a MultiDrizzle-combined image for the names and drizzle parameters of all input images. For each input image, the pixel coordinates of all objects in the master catalogue, which is associated with the MultiDrizzle-combined image, are projected out into the coordinate system of the input image to derive the pixel coordinates therein. For each input image an Input Object List is generated which comprises all objects which fall on the area covered by the input image. For the projections of the object positions, this aXe task uses the STSDAS task tran.
There are two general strategies to apply iolprep:
j8m81cd9q_flt_1.cat, j8m824toq_flt_1.cat, j8m84aqkq_flt_1.cat, j8m851tmq_flt_1.cat.As the file names suggest, the IOL's refer to the direct images, and during the spectral extraction a direct image must be given for every grism image (see Chapt. 7.3).
j8m820leq_flt_1.cat, j8m820llq_flt_1.cat, j8m820lrq_flt_1.cat, j8m820m4q_flt_1.cat, j8m822q0q_flt_1.cat, j8m822q4q_flt_1.cat, j8m822qbq_flt_1.cat, j8m822qhq_flt_1.cat.In this scenario the IOL's refer directly to the grism images, as their file names indicate, and in the spectral extraction no direct image is needed.
The latter strategy has small advantages, such as it is easier to
make the Input Image List (see below). It is possible to include objects
in the Input Object List which have positions outside of the area covered by
the corresponding direct image or grism image. In the case that the spectrum
of the object falls partly on the grism image, but its reference point is
outside, the spectrum covered by the grism image can still be reduced and
contribute to the coadded spectrum of the object. Also higher orders
of bright objects outside of the grism image can cause significant
contamination on the grism images.
Including them in the IOL means that their contamination is properly
recorded and evaluated, even if no spectrum is extracted.
The parameter dimension_info controls the effective area for
the inclusion of objects in the task iolprep.
Depending on whether iolprep is run on the direct image f555w_drz.fits or the grism image g800l_drz.fits, the task is executed as:
-->iolprep mdrizzle_image='f555w_drz.fits' input_cat='f555w_drz.cat' dimension_info=0,0,0,0or alternatively:
-->iolprep mdrizzle_image='g800l_drz.fits' input_cat='f555w_drz.cat' dimension_info=0,0,0,0
Similar to iolprep, the task fcubeprep (see Chapt. 4.2) uses MultiDrizzled direct and grism images to build the fluxcube files. In addition, the SExtractor segmentation image which is associated to the master catalogue must also be provided. fcubeprep searches in the header of the MultiDrizzle-combined grism image for the names and drizzle parameters of all input grism images. Using the information on wavelength and zeropoints which are part of the input, the task transforms the direct images to flux units. Then the segmentation image and all direct flux images are projected into the coordinates of each input grism image to generate cutout images which match the area of the input grism images. For each input grism image, a fluxcube image is finally created from the corresponding segmentation and flux cutout images.
All images used in the input (MultiDrizzle-combined grism image, MultiDrizzle-combined direct images and segmentation images) must have been combined such that they have the same coordinate system. This means each pixel must represent the same position on the sky on all input images (see Chapt. 3.2.1).
In case there are several MultiDrizzle-combined direct images in different filters available, the user must prepare a file and give for each image the name, central wavelength and zero point separated by ',' in a row. Provided that in addition to the direct image f555w_drz.fits, there exists also the image f606w_drz.fits, this file (name dir_ims.lis) looks like:
f555w_drz.fits, 431.8, 25.157 f606w_drz.fits, 591.8, 26.655Note that instead of the 'nominal' values 555 and 606 the more accurate pivot wavelength values have been used for the ACS filters F555W and F606W. With the segmentation image f555w_seg.fits the task fcuberep is executed as:
--> fcubeprep grism_image='g800l_drz.fits' segm_image='f555w_seg.fits' filter_info='dir_ims.lis' AB_zero='yes' dimension_info=0,0,0,0The task creates the fluxcubes:
j8m820leq_flt_2.FLX.fits, j8m820llq_flt_2.FLX.fits, j8m820lrq_flt_2.FLX.fits, j8m820m4q_flt_2.FLX.fits, j8m822q0q_flt_2.FLX.fits, j8m822q4q_flt_2.FLX.fits, j8m822qbq_flt_2.FLX.fits, j8m822qhq_flt_2.FLX.fits.
The main decisions are whether aXedrizzle is used or not and whether the background subtraction is done globally with the master background or with a local background for each beam (see Chapt. 1.6 for a comparison of the two methods).
aXedrizzle is currently not supported for prism data. Global background subtraction requires a master background for the instrumental configuration with which the data were taken with. The available master background images are posted on the instrument pages (http://www.stsci.edu/hst/acs/analysis/STECF and http://www.stsci.edu/hst/wfc3/analysis/grism_obs/), and users are urged to check whether a master background is available for their data.
If possible, the recommended reduction strategy is to do a global background subtraction and to use aXedrizzle. For the typical survey type data, this is the best way to reduce ACS grism data (see e.g. the GRAPES data paper, Pirzkal et al., 2004) or WFC3 grism data. In case only individual spectra in crowded fields are to be reduced, the reduction with a background PET may have advantages.
Depending on the reduction strategy, different High Level aXe Tasks (see Fig. 1.1) have to be applied to reduce the spectra. Table 3.1 lists the tasks and the order in which to apply them for the various reduction strategies.
In case that the IOL's refer directly to the grism images (see item 1. in Chapt. 3.2.3), the Input Image List axeprep.lis for the data presented here looks like:
j8m820leq_flt.fits j8m820leq_flt_1.cat 0.0 j8m820llq_flt.fits j8m820llq_flt_1.cat 0.0 j8m820lrq_flt.fits j8m820lrq_flt_1.cat 0.0 j8m820m4q_flt.fits j8m820m4q_flt_1.cat 0.0 j8m822q0q_flt.fits j8m822q0q_flt_1.cat 0.0 j8m822q4q_flt.fits j8m822q4q_flt_1.cat 0.0 j8m822qbq_flt.fits j8m822qbq_flt_1.cat 0.0 j8m822qhq_flt.fits j8m822qhq_flt_1.cat 0.0
If the IOL's refer to direct images, (see item 2. in Chapt. 3.2.3), the Input Image List axeprep.lis for the data presented in here looks like:
j8m820leq_flt.fits j8m84aqkq_flt.cat j8m84aqkq_flt.fits 0.0 j8m820llq_flt.fits j8m81cd9q_flt.cat j8m81cd9q_flt.fits 0.0 j8m820lrq_flt.fits j8m81cd9q_flt.cat j8m81cd9q_flt.fits 0.0 j8m820m4q_flt.fits j8m84aqkq_flt.cat j8m84aqkq_flt.fits 0.0 j8m822q0q_flt.fits j8m851tmq_flt.cat j8m851tmq_flt.fits 0.0 j8m822q4q_flt.fits j8m824toq_flt.cat j8m824toq_flt.fits 0.0 j8m822qbq_flt.fits j8m824toq_flt.cat j8m824toq_flt.fits 0.0 j8m822qhq_flt.fits j8m851tmq_flt.cat j8m851tmq_flt.fits 0.0
Every grism image is paired with the direct image taken at the closest position on the sky to provide the best overlap between objects in the IOL and the area covered by the grism image. The dmag-values are all set to the default , and therefore could be neglected here.
The exact format of the Input Image List is extensively described in Chapt. 7.3. All files are expected to be located in the directory indicated by the environment variable AXE_IMAGE_PATH (see Chapt. 5.1).
Up-to-date configuration files and the calibration files for all spectral
modes are posted on the instrument pages
The appropriate configuration file for the data presented in this Chapter
is given below. To save space the descriptions of the higher order beams
INSTRUMENT ACS CAMERA HRC # Calibrations for ACS HRC for Cycle 11 onward; released June 2004 # based on calibration data taken during SMOV and Cycle 11. # Revised (3rd order) flat field cube: # ACS.HRC.flat.cube.2.fits # # Revised 1st and 2nd order sensitivity # New 0th order dispersion solution and sensitivity # New -1st order dispersion solution and sensitivity # March 2009 (MK): keywords 'POBJSIZE' 'SMFACTOR' with dummy values added SCIENCE_EXT SCI ; Science extension DQ_EXT DQ ; DQ extension ERRORS_EXT ERR ; Error extension FFNAME ACS.HRC.flat.cube.2.fits DQMASK 16383 EXPTIME EXPTIME RDNOISE 4.71 POBJSIZE 1.0 SMFACTOR 1.0 DRZRESOLA 24.0 DRZSCALE 0.028 DRZLAMB0 4785.0 DRZXINI 15.0 DRZROOT aXedrizzle # PSF variations for optimal extraction PSFCOEFFS 8.20 -8.29e-02 4.01e-04 -9.47e-07 1.18e-09 -7.44e-13 1.87e-16 PSFRANGE 100.0 1100.0 # First order (BEAM A) BEAMA 0 185 MMAG_EXTRACT_A 25 MMAG_MARK_A 27 # Trace description, 1st order DYDX_ORDER_A 1 DYDX_A_0 0.0 0.0 0.0 0.0 0.0 0.0 DYDX_A_1 -0.796319 7.10246e-6 9.55948e-6 # X and Y Offsets XOFF_A 0. 0. 0. YOFF_A -1.78463 -0.000149007 0.000436432 # Dispersion solution, 2nd order DISP_ORDER_A 2 DLDP_A_0 4783.55 0.00657371 -0.0126691 DLDP_A_1 23.5107 -0.000677401 0.00127958 DLDP_A_2 0.00170758 1.77847e-7 1.97777e-7 # SENSITIVITY_A ACS.HRC.1st.sens.2.fits
Under normal circumstances the user can apply the aXe configuration files without any modifications. Only to speed up the computation time it might be convenient to modify some keywords (see Chapt. 3.4). The location of the configuration and calibration files is the directory indicated by the environment variable AXE_CONFIG_PATH (see Chapt. 5.1).
The ACS Wide Field Camera and the WFC3 UVIS Camera contain two CCD chips, and the data is stored in two independent extensions of the fits file. The spectral reduction in aXe is done independently, using one configuration file for every science extension. In the ACS/WFC and WFC3/UVIS configuration files, the chip number is specified in the keywords ``OPTKEY1'' and ``OPTVAL1''.
For technical reasons in both cameras the data of CCD chip No. 1 are stored in the second science extension version ([sci,2] in PyRAF-fits notation), and the data of of CCD chip No. 2 is stored in the first science extension version ([sci,1] in PyRAF-fits notation). Care must be taken to combine the correct files in the aXe input parameters, since the file names are often derived from these two counter-intuitive numbering schemes. While the file names of the configuration files follow the chip numbers (e.g. ACS.WFC.CHIP1.Cycle13.2.conf and ACS.WFC.CHIP2.Cycle13.2.conf are the configuration files for chip 1 and 2, respectively), the IOL's created in iolprep follow the extension version number (the Input Object Lists j8m822qhq_flt_1.cat and j8m822qhq_flt_2.cat contain objects located on the fits image j8m822qhq_flt.fits[sci,1] and j8m822qhq_flt.fits[sci,2], respectively). Figure 3.2 and the note on page give further examples how to combine the input for ACS/WFC data in the various High Level Tasks.
As in all further examples, optimal extraction is selected in the
parameters. In aXe the optimal extracted spectra are always delivered
in addition to the normal, equally weighted results. There is no
need to run aXe twice, the optimal extractions only entails but
a small additional amount of computing time.
The sequence of commands interactively applied in PyRAF is:
-->axeprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" backims="HRC.back.fits" backgr="YES" fwhm="2.0" norm="YES" histogram="YES" -->axecore inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" back="NO" extrfwhm=4.0 drzfwhm=3.0 backfwhm=0.0 slitless_geom="YES" orient="YES" exclude="NO" lambda_mark=800.0 cont_model="fluxcube" model_scale=3.0 inter_type="linear" lambda_psf=555.0 spectr="NO" weights="NO" sampling="drizzle" -->drzprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" opt_extr="YES" back="NO" -->axedrizzle inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" infwhm=4.0 outfwhm=3.0 back="NO" makespc="YES" adj_sens="YES" opt_extr="YES"The line breaks are added here for clarity, but on the actual command line each command should be given as one string. The most convenient way to specify the task parameters is with the PyRAF/IRAF epar mechanism.
-->axeprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" backims="HRC.back.fits" backgr="YES" fwhm="2.0" norm="YES" histogram="YES" -->axecore inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" back="NO" extrfwhm=3.0 drzfwhm=0.0 backfwhm=0.0 slitless_geom="YES" orient="YES" exclude="NO" lambda_mark=800.0 cont_model="gauss" model_scale=3.0 inter_type="linear" lambda_psf=555.0 spectr="YES" adj_sens="YES" weights="YES" sampling="drizzle"
-->axeprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" backgr="NO" fwhm="2.0" norm="YES" histogram="YES" -->axecore inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" back="YES" extrfwhm=4.0 drzfwhm=3.0 backfwhm=4.0 slitless_geom="YES" orient="YES" exclude="NO" lambda_mark=800.0 cont_model="fluxcube" model_scale=3.0 inter_type="linear" lambda_psf=555.0 spectr="NO" adj_sens="NO weights="NO" sampling="drizzle" -->drzprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" opt_extr="YES" back="YES" -->axedrizzle inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" infwhm=4.0 outfwhm=3.0 back="YES" makespc="YES" opt_extr="YES"
-->axeprep inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" backgr="NO" fwhm="2.0" norm="YES" histogram="YES" -->axecore inlist="axeprep.lis" configs="ACS.HRC.Cycle11.2.conf" back="YES" extrfwhm=3.0 drzfwhm=0.0 backfwhm=0.0 slitless_geom="YES" orient="YES" exclude="NO" lambda_mark=800.0 cont_model="gauss" model_scale=3.0 inter_type="linear" lambda_psf=555.0 spectr="YES" adj_sens="YES" weights="YES" sampling="drizzle"
As a rule of thumb, each High Level Task needs around 0.3 sec of computing time per object and image on a typical Pentium five machine (GHz). For prism data with typically a few objects per image an aXe reduction is completed within a short period of time. In a survey type project, however, a typical data set consists of 10 ACS/WFC images and 1000 objects on each image. This results in around half a day of pure computing time. The minimum RAM requirement is around 2000 MB, which should not constitute a bottleneck on modern workstations.
The aXe reduction on a particular data set is usually done several times with some small changes in the parameters to fine tune the results. The wavelength dependence of the PSF is not very large. Switching it off in the early reductions can save a lot of time without any significant influence on the results and their interpretations for the next runs.
To neglect the wavelength dependence, the keywords PSFCOEFFS and PSFRANGE must be commented out in the aXe configuration file (see Chapt.3.3.3).
For the WFC3/IR grism we were unable to detect a significant variation of the PSF with wavelength, hence there are no corresponding keywords (PSFCOEFFS and PSFRANGE) in the configuration files and aXe is always running in the ``fast'' mode.
It is therefore very reasonable to set the extraction limits for the higher order spectra to a very low magnitude limit (setting the keywords in the configuration file e.g. MMAG_EXTRACT_B 10, MMAG_EXTRACT_C 10, ....) to prevent their extraction. Even if those higher order spectra are not extracted, they are still fully taken into account in the contamination analysis, since the brightness limits for objects to be included into the contamination analysis is controled by the keyword MMAG_MARK_# (see also next Chapter).
Provided the user decides to compute the contamination down to
the ratio of or between any contaminating beam and
the target object (first order beam), and the target object has
, reasonable values for MMAG_MARK_# for
ACS/WFC data would be
These values would assure that all relevant beams are taken into account when computing the contamination, but also avoid the costly computation of negligable contamination contributions. The differential throughput values in Tab. 3.2 are derived from the order sensitivities applied to flat continuum sources; they may not be applicable to very red or very blue sources or emission line objects.