+------------------------------------------------------------------------------+ Hubble Space Telescope WFC3/IR Mosaic of the Horsehead Nebula 19 April 2013 Jennifer Mack Research and Instrument Scientist Space Telescope Science Institute 3700 San Martin Drive, Baltimore, MD 21218 Table of Contents: 1. Introduction and observations 2. Data calibration and software tools 3. Image registration and combination 4. Data products and file naming convention 5. Publications 6. References +------------------------------------------------------------------------------+ 1. Introduction and observations To commemorate HST's 23rd anniversary, the Hubble Heritage Team has observed the famous Horsehead Nebula with HST's new WFC3 infrared camera. This new view of the Horsehead is strikingly different than the familiar view in visible light, revealing structures hidden by the dense dust and gas. The new WFC3 observations were obtained in October/November 2012 and include 9 tiles in a 3x3 mosaic pattern. (See Proposal 12812, PI: Levay for details, http://www.stsci.edu/hst/phase2-public/12812.pro) The broad band F110W (YJ) and F160W (H) filters highlight unique physical processes occurring in and around the nebula, and they combine to produce a dramatic new color image. Parallel observations with the ACS Wide Field Channel have also been obtained to create an H-alpha mosaic of the "horizon" feature adjacent to the Horsehead. High level products for this dataset will be released soon. Table 1: Filters Observed Detector Filter Description Pivot_Wave(nm) Rect_Width(nm) WFC3/IR F110W Wide YJ 1153.4 443.0 WFC3/IR F160W WFC3 H 1536.9 268.3 ACS/WFC F658N H-alpha 658.4 7.5 As part of the observing strategy, a small shift (dither) between tiles has been obtained to allow for the removal of detector artifacts, specifically 'blobs' in the IR detector which are blemishes on the detector where the sensitivity is 10-15% lower. We have increased the standard 5.2" shift for the IR-DITHER-BLOB pattern to 7.2" so that we may also correct for bad pixels in a large circular area with poor response to light known as the 'Death Star'. Table 2: Dither Pattern Pattern_Type WFC3-IR-DITHER-BLOB Pattern_Purpose DITHER Number_Of_Points 2 Point_Spacing 7.2 Pattern_Orient 90 The IR Horsehead mosaic was obtained in 9 orbits, with one tile per orbit (visit). With the horse's head oriented up, the tiles are labelled in the diagram below. The HST file naming convention gives the visit number in the 5th and 6th characters. For example, the archival data product ibxl58030_drz.fits corresponds to tile 58. ____ ____ ____ | | | | | 58 | 55 | 52 | |____|____|____| | | | | | 57 | 54 | 51 | |____|____|____| | | | | | 56 | 53 | 50 | |____|____|____| The target was centered in tile 54 using the IR-FIX aperture at J2000 coordinates, RA= 05H 41M 1.0696S , DEC= -02D 27' 10.79". Tables 3 & 4 summarize the observations, including the association (tile) name, the individual FLT images making up the association, the filter, date of observation, detector orientation, and the X and Y dither (POSTARG) between tiles given in arcseconds. Table 3: F110W observations SAMP_SEQ (Sample Sequence) = SPARS50 NSAMP (Number of Samples) = 13 EXPTIME (Total Exposure time) = 552.94 sec per tile ASSOCIATION FLT_FRAME FILTER DATE ORIENT POSTARG1 POSTARG2 -------------------------------------------------------------------------------------------------- IBXL50020 ibxl50cjq_flt.fits[1] F110W 2012-11-03 170.666 -123.742401 -113.112099 IBXL50020 ibxl50cnq_flt.fits[1] F110W 2012-11-03 170.666 -123.742401 -105.912102 IBXL51020 ibxl51emq_flt.fits[1] F110W 2012-10-22 166.667 0.000000 -113.112099 IBXL51020 ibxl51eqq_flt.fits[1] F110W 2012-10-22 166.667 0.000000 -105.912102 IBXL52020 ibxl52jyq_flt.fits[1] F110W 2012-10-23 166.669 123.742401 -113.112099 IBXL52020 ibxl52k2q_flt.fits[1] F110W 2012-10-23 166.669 123.742401 -105.912102 IBXL53020 ibxl53kvq_flt.fits[1] F110W 2012-10-23 165.666 -123.742401 -3.600000 IBXL53020 ibxl53l6q_flt.fits[1] F110W 2012-10-24 165.666 -123.742401 3.600000 IBXL54020 ibxl54beq_flt.fits[1] F110W 2012-10-26 166.668 0.000000 -3.600000 IBXL54020 ibxl54biq_flt.fits[1] F110W 2012-10-26 166.668 0.000000 3.600000 IBXL55020 ibxl55eyq_flt.fits[1] F110W 2012-10-27 166.669 123.742401 -3.600000 IBXL55020 ibxl55f2q_flt.fits[1] F110W 2012-10-27 166.669 123.742401 3.600000 IBXL56020 ibxl56hsq_flt.fits[1] F110W 2012-10-27 162.667 -123.742401 105.912102 IBXL56020 ibxl56hzq_flt.fits[1] F110W 2012-10-28 162.667 -123.742401 113.112099 IBXL57020 ibxl57abq_flt.fits[1] F110W 2012-11-05 166.668 0.000000 105.912102 IBXL57020 ibxl57afq_flt.fits[1] F110W 2012-11-05 166.668 0.000000 113.112099 IBXL58020 ibxl58soq_flt.fits[1] F110W 2012-11-07 166.669 123.742401 105.912102 IBXL58020 ibxl58ssq_flt.fits[1] F110W 2012-11-07 166.669 123.742401 113.112099 Table 4: F160W observations SAMP_SEQ (Sample Sequence) = SPARS50 NSAMP (Number of Samples) = 16 EXPTIME (Total Exposure time) = 702.94 sec per tile ASSOCIATION FLT_FRAME FILTER DATE ORIENT POSTARG1 POSTARG2 -------------------------------------------------------------------------------------------------- IBXL50030 ibxl50clq_flt.fits[1] F160W 2012-11-03 170.666 -123.742401 -113.112099 IBXL50030 ibxl50cqq_flt.fits[1] F160W 2012-11-03 170.666 -123.742401 -105.912102 IBXL51030 ibxl51eoq_flt.fits[1] F160W 2012-10-22 166.667 0.000000 -113.112099 IBXL51030 ibxl51etq_flt.fits[1] F160W 2012-10-22 166.667 0.000000 -105.912102 IBXL52030 ibxl52k0q_flt.fits[1] F160W 2012-10-23 166.669 123.742401 -113.112099 IBXL52030 ibxl52k5q_flt.fits[1] F160W 2012-10-23 166.669 123.742401 -105.912102 IBXL53030 ibxl53kxq_flt.fits[1] F160W 2012-10-23 165.666 -123.742401 -3.600000 IBXL53030 ibxl53l9q_flt.fits[1] F160W 2012-10-24 165.666 -123.742401 3.600000 IBXL54030 ibxl54bgq_flt.fits[1] F160W 2012-10-26 166.668 0.000000 -3.600000 IBXL54030 ibxl54blq_flt.fits[1] F160W 2012-10-26 166.668 0.000000 3.600000 IBXL55030 ibxl55f0q_flt.fits[1] F160W 2012-10-27 166.669 123.742401 -3.600000 IBXL55030 ibxl55f5q_flt.fits[1] F160W 2012-10-27 166.669 123.742401 3.600000 IBXL56030 ibxl56huq_flt.fits[1] F160W 2012-10-27 162.667 -123.742401 105.912102 IBXL56030 ibxl56i2q_flt.fits[1] F160W 2012-10-28 162.667 -123.742401 113.112099 IBXL57030 ibxl57adq_flt.fits[1] F160W 2012-11-05 166.668 0.000000 105.912102 IBXL57030 ibxl57aiq_flt.fits[1] F160W 2012-11-05 166.668 0.000000 113.112099 IBXL58030 ibxl58sqq_flt.fits[1] F160W 2012-11-07 166.669 123.742401 105.912102 IBXL58030 ibxl58svq_flt.fits[1] F160W 2012-11-07 166.669 123.742401 113.112099 +--------+---------+---------+---------+---------+---------+---------+---------+ 2. Data calibration and software tools The calibrated archival data was retrieved 'on-the-fly' from MAST with the standard CALWF3 processing for WFC3/IR data, including: zeroth read subtraction, non-linearity correction, dark subtraction, cosmic-ray rejection, and flat fielding. The software versions used are summarized below: Table 5: Software used for processing OPUS software version: OPUS_VER= 'OPUS 2012_4a' CALWF3 code version: CAL_VER = '2.7 (21-May-2012)' AstroDrizzle Version: '1.1.1dev' The calibrated FLT images from MAST were used directly with no further reprocessing. Drizzled products, on the other hand, are generally recommended to be used as 'quick-look' products. Reprocessing is highly recommended to achieve the most scientifically accurate data products. For these data, the four main areas for improvement include: (1) image alignment, (2) sky subtraction, (3) rejection of detector artifacts (including cosmic rays), and (4) final image combination into a large mosaic. AstroDrizzle (Gonzaga et al., 2012) replaced MultiDrizzle in the HST data pipeline in June 2012. AstroDrizzle, an abbreviation for Astrometric Drizzle, was designed from the ground-up to improve the handling of astrometry and geometric distortion. It is available as part of the DrizzlePac software package which replaces the Dither package in STSDAS. DrizzlePac is a suite of supporting tasks for AstroDrizzle which includes tweakreg, a useful tool for aligning images in different visits. Tweakback is used for additional image alignment applications; when tweakreg has been used to align drizzled products (i.e., different filters, pointings, or detectors), tweakback can be used to propagate the updated WCS back to the original FLT images. AstroDrizzle may then be used to reprocess those updated FLT images. Like MultiDrizzle, AstroDrizzle ties together a substantial set of algorithms, each designed to accomplish a different task, and as such has a large parameter set. MAST drizzled products were created using a default set of parameters that will work for a wide range of data. To understand the processing which took place in the pipeline, it can be helpful to inspect the drizzle parameter table or MDRIZTAB. These default parameters, however, will not produce the optimum science data quality for most programs, and those images will require post-pipeline processing. Additionally, MAST only creates drizzled products for images obtained in a single visit, so additional visits, for example those making up a large mosaic, may only be combined together by reprocessing. While single visit images are usually aligned to better than 0.1 pixels, large dithers often have residual offsets of a few tenths of a pixel and small rotations of a few thousandths of a degree. When combining data from different visits, larger tweaks to the image alignment are usually required after reacquiring guide stars, where uncertainties in the star catalogs can result in offsets of ~0.2". Misalignment can impact the accuracy the cosmic ray rejection, and when astronomical sources are flagged as cosmic rays in one or more images, the photometric accuracy of the final data products will be compromised. Additionally, a poor estimate of the sky background, for example in images where a bright target fills the field of view, may also impact the accuracy of cosmic ray rejection, and in turn, the resulting photometry. The AstroDrizzle task performs the following steps: bad pixel identification, sky subtraction, rejection of cosmic rays and other artifacts, and a final drizzle combination (Fruchter et al., 2002) into a clean image. It applies the latest filter-specific geometric distortion corrections to each image, as specified in the IDCTAB reference tables. For more on AstroDrizzle, see the DrizzlePac webpage: http://www.stsci.edu/drizzlepac +--------+---------+---------+---------+---------+---------+---------+---------+ 3. Image registration and combination Tweakreg provides an automated interface for computing residual shifts between images before they are combined by AstroDrizzle. It is especially useful for combining images taken in different visits. To begin, we aligned the 9 tiles in the F160W filter. Using information about the World Coordinate System (WCS) from the image header, AstroDrizzle does a excellent job aligning the 2 individual FLT frames within each visit. Thus, we focus here on aligning the drizzled products from MAST. This is done in two iterations. First, tiles 51, 53, 55, & 57 are aligned to the central tile (54). Unlike the corner tiles, these contain significant overlap with the central tile, where sources in common in each can be used to refine the alignment. The updated solutions are then propagated back to the original FLT image headers using tweakback. The 10 FLT frames making up these 5 tiles are drizzled together to create a 'first iteration' mosaic. Next, the corner tiles 50, 52, 56, & 58 are aligned to the preliminary mosaic. Tweakback is used to propagate the revised WCS back to the FLT image headers for those additional tiles. Finally, the full set of 18 FLT images are drizzled together to create the full mosaic. Once we have an aligned reference image to work with, the individual FLT images for F110W can be used aligned directly with the F160W mosaic. Tweakreg is used to solve for any offsets and to update the WCS in the image headers. Then the full set of 18 FLT images are drizzled to together to create the second mosaic. The summary below includes syntax for running each task from the command line in PyRAF. ****** F160W ****** A.) Create source lists for each iteration. ____ | | | 55 | ____|____|____ | | | | | 57 | 54 | 51 | |____|____|____| | | | 53 | |____| iter1_drz.list ibxl54030_drz.fits <-- Note that tile 54 is listed first ibxl51030_drz.fits ibxl53030_drz.fits ibxl55030_drz.fits ibxl57030_drz.fits ____ ____ ____ | | | | | 58 | | 52 | |____|____|____| | | | | | | | | |____|____|____| | | | | | 56 | | 50 | |____|____|____| iter2_drz.list ibxl50030_drz.fits ibxl52030_drz.fits ibxl56030_drz.fits ibxl58030_drz.fits B.) Use tweakreg to align archival DRZ products for the first set of tiles with the central tile. --> import drizzlepac --> from drizzlepac import tweakreg --> unlearn tweakreg --> unlearn imagefindpars --> tweakreg.TweakReg('@iter1_drz.list',conv_width=3.5,threshold=10,minobj=4,shiftfile=True,outshifts='shift_iter1.txt',updatehdr=True,sigma=2.5) The table below summarizes the updates made to the DRZ image headers, including the residual X/Y shifts, rotation and scale for each tile. The rms of the fit and the number of sources used to compute each fit are listed in the last 3 columns. shift_iter1.txt #VISIT TILE D_X D_Y D_ROT D_SCALE XRMS YRMS N_MATCH_54 54 ibxl54030_drz.fits 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 -- 51 ibxl51030_drz.fits -0.399332 -0.247731 0.020059 1.000148 0.129273 0.129417 19 53 ibxl53030_drz.fits -4.019313 0.123231 359.972320 1.000263 0.233400 0.352019 18 55 ibxl55030_drz.fits 0.354438 -0.051458 359.992465 1.000089 0.060623 0.075065 22 57 ibxl57030_drz.fits -3.508491 -1.435530 0.012769 0.999929 0.117617 0.103693 15 C.) Use tweakback to propagate the new 'tweaked' solutions back to their respective original FLT image headers. --> from drizzlepac import tweakback --> unlearn tweakback --> tweakback.tweakback('ibxl51030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl53030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl55030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl57030_drz.fits',verbose=True) D.) Use astrodrizzle to combine the FLT images for those tiles to produce the first iteration mosaic. iter1.list ibxl54bgq_flt.fits ibxl54blq_flt.fits ibxl51eoq_flt.fits ibxl51etq_flt.fits ibxl53kxq_flt.fits ibxl53l9q_flt.fits ibxl55f0q_flt.fits ibxl55f5q_flt.fits ibxl57adq_flt.fits ibxl57aiq_flt.fits --> from drizzlepac import astrodrizzle --> unlearn astrodrizzle --> hedit *flt.fits[1] mdrizsky 0.0 --> astrodrizzle.AstroDrizzle('@iter1.list, output='f160w_mosaic1', clean=no, build=no, skysub=no, driz_sep_bits='0', driz_cr_corr=yes, final_bits='0', final_wcs=yes, final_rot=257.) E.) Use tweakreg to align the archival DRZ products in the corner tiles with the first iteration mosaic. --> tweakreg.TweakReg('@iter2_drz.list', refimage='f160w_mosaic1_drz-sci.fits', conv_width=3.5,threshold=10,minobj=4, shiftfile=True, outshifts='shift_iter2.txt', updatehdr=True, sigma=2.5) The table below summarizes the updates made to the DRZ image headers. shift_iter2.txt #VISIT TILE D_X D_Y D_ROT D_SCALE XRMS YRMS N_MATCH 50 ibxl50030_drz.fits 0.363492 0.113653 359.997684 0.999604 0.178681 0.154320 24 52 ibxl52030_drz.fits -2.223896 3.636521 359.997908 1.000177 0.128812 0.154486 22 56 ibxl56030_drz.fits -0.193220 3.988737 0.019279 1.000541 0.208571 0.171539 23 58 ibxl58030_drz.fits -0.208480 -0.157570 359.994550 0.999740 0.080432 0.132811 36 F.) Use tweakback to propogate the new "tweaked" solutions back to their respective original FLT image headers. --> tweakback.tweakback('ibxl50030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl52030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl56030_drz.fits',verbose=True) --> tweakback.tweakback('ibxl58030_drz.fits',verbose=True) G.) Use astrodrizzle to combine the full set of updated FLT images, creating a WCS-aligned drizzled mosaic. --> astrodrizzle.AstroDrizzle('*flt.fits, output='f160w_mosaic2', clean=no, build=no, skysub=no, driz_sep_bits='0', driz_cr_corr=yes, final_bits='0', final_wcs=yes, final_rot=257.) ******F110W****** A.) Copy the F160W mosaic to a new reference image --> imcopy f160w_mosaic2_drz-sci.fits f160w_refimage.fits B.) Use tweakreg to align the full set of archival FLT products with the F160W mosaic. --> tweakreg.TweakReg('*flt.fits', refimage='f160w_refimage.fits', conv_width=3.5, threshold=10, minobj=4, shiftfile=True, outshifts='shift.txt', updatehdr=True, sigma=2.5) The table below summarizes the updates made to the DRZ image headers. shift.txt #VISIT TILE D_X D_Y D_ROT D_SCALE XRMS YRMS N_MATCH 50 ibxl50cjq_flt.fits 0.173324 -0.092492 359.996414 0.999661 0.060990 0.112006 31 50 ibxl50cnq_flt.fits 0.222975 -0.146211 359.995394 0.999614 0.108389 0.078044 30 51 ibxl51emq_flt.fits -0.416176 0.197179 0.019128 1.000168 0.066725 0.086041 39 51 ibxl51eqq_flt.fits -0.443364 0.131007 0.017243 1.000192 0.085827 0.096354 46 52 ibxl52jyq_flt.fits -2.458126 3.398392 359.999515 1.000207 0.079428 0.098503 37 52 ibxl52k2q_flt.fits -2.438299 3.384077 359.999259 1.000207 0.084185 0.075862 37 53 ibxl53kvq_flt.fits -0.122838 3.798010 359.971733 1.000222 0.105178 0.169308 21 53 ibxl53l6q_flt.fits -0.076464 3.932835 359.966014 1.000363 0.145344 0.160359 22 54 ibxl54beq_flt.fits -0.131060 -0.245805 359.996229 1.000126 0.099140 0.122641 30 54 ibxl54biq_flt.fits -0.144979 -0.238269 359.999695 1.000107 0.057762 0.125218 25 55 ibxl55eyq_flt.fits -0.185638 -0.588404 359.991526 1.000094 0.087837 0.093716 39 55 ibxl55f2q_flt.fits -0.260816 -0.614909 359.994538 1.000098 0.081410 0.074323 45 56 ibxl56hsq_flt.fits -0.440702 3.844256 0.016576 1.000518 0.105943 0.111402 29 56 ibxl56hzq_flt.fits -0.446121 3.765550 0.018936 1.000497 0.124755 0.112873 33 57 ibxl57abq_flt.fits -1.585988 3.354311 0.009712 0.999922 0.086807 0.095375 49 57 ibxl57afq_flt.fits -1.561044 3.259317 0.014834 0.999961 0.119971 0.092323 50 58 ibxl58soq_flt.fits -0.308502 -0.396188 359.994451 0.999716 0.093044 0.115988 52 58 ibxl58ssq_flt.fits -0.377107 -0.258882 359.991583 0.999661 0.079098 0.095745 55 C.) Use astrodrizzle to combine the updated FLT images, creating a WCS-aligned drizzled mosaic. --> astrodrizzle.AstroDrizzle('*flt.fits, output='f110w_mosaic', clean=no, build=no, skysub=yes, skyfile='sky_user.txt', driz_sep_bits='0', driz_cr_corr=yes, final_bits='0', final_wcs=yes, final_refimage='f160w_refimage.fits') The first time we combined the F110W mosaic, we noticed that the sky background was not continuous across the mosaic. Many astronomical fields of view cover portions of the sky devoid of large objects, and as a result, the default sky subtraction parameters are sufficient. For observations of targets that fill the field of view, however, sky background may be overestimated. For F160W, we simply turned off the sky subtraction by setting MDRIZSKY=0.0 and setting skysub=no. For F110W, however, true variations in the sky background between FLT frames were found. Thus, we provide AstroDrizzle an ascii file known as the 'skyfile' containing user-computed sky values for use with each input image. This file contains the image filename in column 1 and the sky value in column 2. The sky value should be provided in units that match the units of the input image, in this case electrons per second. Note that we start with the assumption that the minimum sky background is zero (as for F160W) and then remove the required value to make the frames match. sky_user.txt ibxl50cjq_flt.fits 0.067 ibxl50cnq_flt.fits 0.050 ibxl51emq_flt.fits 0.037 ibxl51eqq_flt.fits 0.050 ibxl52jyq_flt.fits 0.005 ibxl52k2q_flt.fits 0.000 ibxl53kvq_flt.fits 0.708 ibxl53l6q_flt.fits 0.050 ibxl54beq_flt.fits 0.030 ibxl54biq_flt.fits 0.050 ibxl55eyq_flt.fits 0.000 ibxl55f2q_flt.fits 0.200 ibxl56hsq_flt.fits 0.745 ibxl56hzq_flt.fits 0.000 ibxl57abq_flt.fits 0.010 ibxl57afq_flt.fits 0.000 ibxl58soq_flt.fits 0.047 ibxl58ssq_flt.fits 0.000 The final F110W and F160W mosaics were drizzled to the native IR detector plate scale of 0.1283 arcsec/pixel. The output images are oriented to 257 degrees, which equals the detector orientation at the time of observation (167 degrees) plus 90, such that the Horsehead is upright in the final image. The Astrodrizzle science products provided (drz-sci.fits) contain an additional extension called the HDRTAB containing merged headers from all the input frames. --> catfits *drz-sci.fits EXT# FITSNAME TYPE DIMENSION BITPIX 0 hlsp_heritage SCI 3239x3346 -32 1 BINTABLE HDRTAB 274Fx18R This new extension supercedes the global header [0] where this information used to reside for data products produced with MultiDrizzle. This older software simply used the first input image header as the basis for the final output header, modifying only a few keywords (namely, EXPSTART, EXPEND, EXPTIME, TEXPTIME and ROOTNAME) to make it appropriate for the output image. This resulted in an output header which did not accurately reflect the full set of input image information. The solution implemented for AstroDrizzle is to use the new blendheaders task, resulting in a more complete record of all keyword values from each input images. The new table extension (HDRTAB) records values which change from one input image to another while eliminating keywords that no longer apply to drizzle products. To examine the new merged header, the PyRAF 'tread' or 'tprint' tasks can be used. For example, to list the orientation and sky value for each of the 18 frames, the following command may be used: --> tprint hlsp_heritage_hst_wfc3-ir_horsehead_f110w_v1_drz-sci.fits[1] column=rootname,asn_id,orientat,mdrizsky # row ROOTNAME ASN_ID ORIENTAT MDRIZSKY 1 ibxl50cjq IBXL50020 170.6266449888127 0.067 2 ibxl50cnq IBXL50020 170.6255025680498 0.050 3 ibxl51emq IBXL51020 166.6534763054705 0.037 4 ibxl51eqq IBXL51020 166.6513656545362 0.050 5 ibxl52jyq IBXL52020 166.6329094015762 0.005 6 ibxl52k2q IBXL52020 166.6326223492597 0.000 7 ibxl53kvq IBXL53020 165.5993040222046 0.708 8 ibxl53l6q IBXL53020 165.592901908984 0.050 9 ibxl54beq IBXL54020 166.6281385940577 0.030 10 ibxl54biq IBXL54020 166.6320191978279 0.050 11 ibxl55eyq IBXL55020 166.6242774978195 0.000 12 ibxl55f2q IBXL55020 166.6276502895385 0.200 13 ibxl56hsq IBXL56020 162.6499110008485 0.745 14 ibxl56hzq IBXL56020 162.6525526029507 0.000 15 ibxl57abq IBXL57020 166.643524500674 0.010 16 ibxl57afq IBXL57020 166.6492582218191 0.000 17 ibxl58soq IBXL58020 166.6278494351785 0.047 18 ibxl58ssq IBXL58020 166.6246387036013 0.000 +--------+---------+---------+---------+---------+---------+---------+---------+ 4. Data products and file naming convention Since the Horsehead Nebula mosaics represent a significant investment of expert processing beyond the standard archival products, these drizzle-combined FITS images have now been released as a High-Level Science Product via the B. Mikulski Archive for Space Telescopes (MAST). We provide a list of downloadable FITS files and preview GIF images. The associated configuration (cfg) files list the parameters used to combine the individual frames using HST's new AstroDrizzle software. Both the drizzled science (sci) and weight (wht) images are available. The later provide an effective exposure time map for each filter. The filenames and descriptions of the drizzled mosaics are listed below. This file naming convention makes these HLSP files compatible and queryable with both MAST and the Hubble Legacy Archive (HLA). The format is: hlsp_project_mission_instrument_field-name_filter_version_product.extension ---F160W---- hlsp_heritage_hst_wfc3-ir_horsehead_f110w_v1_drz-sci.fits Drizzled Science Image hlsp_heritage_hst_wfc3-ir_horsehead_f110w_v1_drz-wht.fits Drizzled Weight Image hlsp_heritage_hst_wfc3-ir_horsehead_f110w_v1_drz.cfg AstroDrizzle Configuration File ---F110W---- hlsp_heritage_hst_wfc3-ir_horsehead_f160w_v1_drz-sci.fits Drizzled Science Image hlsp_heritage_hst_wfc3-ir_horsehead_f160w_v1_drz-wht.fits Drizzled Weight Image hlsp_heritage_hst_wfc3-ir_horsehead_f160w_v1_drz.cfg AstroDrizzle Configuration File +--------+---------+---------+---------+---------+---------+---------+---------+ 5. Acknowledgements The work described here is supported by the STScI Director's Discretionary Funds (Program 12812, PI: Levay) and the Hubble Heritage project. If you utilize these data products for scientific purposes, please reference: Mack, J., Levay, Z.G., Davis, T., Christian, C.A., Frattare, L.M., Januszewski, W., Livio, M., Mutchler, M., Noll, K.S., & Sokol, J., 2013, High-Level Science Products for the Mikulski Archive for Space Telescopes http://archive.stsci.edu/prepds/heritage/horsehead/ +--------+---------+---------+---------+---------+---------+---------+---------+ 6. References Fruchter, A. S. & Hook, R. N. 2002, PASP 114, 144 Gonzaga, S., Hack, W., Fruchter, A., Mack, J., eds. 2012, The DrizzlePac Handbook. (Baltimore, STScI) +--------+---------+---------+---------+---------+---------+---------+---------+