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| ACS Instrument Handbook |
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• ACS ISR 2012-04 contains plots of likely minimum sky backgrounds as a function of exposure time. Observers should determine if their sky backgrounds are likely to be less than 20 electrons. If this is the case, they should consult the ACS Web pages for details of the post-flash capability.
• The geometric distortion of the WFC is significant and causes the projected pixel area to vary by ±9% over the field of view. This distortion affects both the photometric accuracy and the astrometric precision, and must be accounted for when the required accuracy is better than 10%.
• The cosmic ray fluxes of HRC and WFC are comparable to those of STIS and WFPC2, respectively. Typical observations should be dithered for cosmic ray rejection. See Section 4.3.5 for more information about dithering strategies for removing cosmic rays and hot pixels.
• At wavelengths longer than ~ 8000 Å, internal scattering in the HRC CCD produced an extended PSF halo. Only a small number of observations were affected because WFC was mostly used at these wavelengths. The WFC CCDs were treated with a front-side metallization that eliminates the large angle, long wavelength halo problem for wavelengths less than 9000 Å. For observations of red targets with the F850LP refer to Section 9.3.2.5.2.1 Optical PerformanceFollowing the fine-alignment and focus activities of the SM3B Orbital Verification period, the optical qualities of all three ACS channels were judged to have met their design specifications. The encircled energy values for the WFC, HRC, and SBC obtained are given in Table 5.4. Refer to ACS ISR 2011-02 (Bohlin, R. 2011) for more details.
Figure 5.7 compares the wavelength-dependent throughputs of the ACS WFC and HRC with those of WFC3/UVIS, WFC3/IR, NICMOS/NIC3, and WFPC2.5.2.3 Limiting MagnitudesTable 5.5 contains the detection limits in Johnson-Cousins V magnitudes for unreddened O5 V, A0 V, and G2 V stars, generated using the ETC. WFC and HRC values used the parameters CR-SPLIT=2, GAIN=2, and a 0.2 arcsecond circular aperture. For the SBC, a 0.5 arcsecond circular aperture was used. An average sky background was used in these examples. However, limiting magnitudes are sensitive to the background levels; for instance, the magnitude of an A0 V in the WFC using the F606W filter changes by ±0.4 magnitudes at the background extremes. Figure 5.8 shows a comparison of the limiting magnitude for point-sources achieved by the different cameras with a signal to noise of 5 in a 10 hour exposure. Figure 5.9 shows a comparison of the time needed for extended sources to attain ABMAG=26.Figure 5.7: HST total system throughputs as a function of wavelength. The plotted quantities are end-to-end throughputs, including filter transmissions calculated at the pivot wavelength of each broad-band filter.Figure 5.8: HST Limiting Magnitude for point sources in 10 hours, as a function of wavelength. Point source limiting magnitude achieved with a signal to noise of 5 in a 10 hour long exposure with optimal extraction.
5.2.4 Signal-To-Noise RatiosChapter 10 contains plots of exposure time versus magnitude for a desired signal-to-noise ratio. These plots are useful for determining the exposure times needed for your scientific objectives. More accurate estimates require the use of the ACS ETC (http://etc.stsci.edu/).5.2.5 SaturationBoth CCD and SBC imaging observations are subject to saturation at high total accumulated counts per pixel. For the CCDs, this is due either to the depth of the full well or to the 16 bit data format. For the SBC, this is due to the 16 bit format of the buffer memory (see Section 4.3.1 and Section 4.5.2).During Cycle 17, STScI developed and tested an algorithm for removing the stripes from WFC science images. The algorithm is effective when the science image is not excessively crowded such that a row-by-row background level becomes difficult to estimate. Because the stripe removal code is not universally effective, it is not currently applied as part of the ACS calibration pipeline. Instead, STScI has released the stripe removal algorithm to the community as a stand-alone task that can be run on ACS data retrieved from the HST archive. This task, acs_destripe, has been written in Python as part of the acstools package in the public release of STScI_Python. As a Python task, it can be run from PyRAF, any Python interpreter or even the operating system command-line, to correct post-SM4 pipeline-calibrated images (_flt.fits). Please see the ACS Web site for details on running this code. Further details regarding the WFC striping and its mitigation are provided in the ACS ISR 2011-05 (Grogin et al. 2011).Because the WFC bias striping noise is so consistent among the four read-out amplifiers, and because it also manifests within the WFC pre-scan regions, STScI has incorporated a pre-scan based de-striping algorithm into the ACS calibration pipeline CALACS. This permits consistent striping-noise mitigation for all post-SM4 WFC full-frame images, including calibration images as well as arbitrary science images, given the trade-off of slightly less precise striping-noise reduction for “low-complexity” science images. This pre-scan based de-striping algorithm, as well as its implementation in CALACS, will be described in an upcoming ACS Instrument Science Report (Anderson & Grogin, in prep.). For correcting WFC sub-array images, it is still necessary to use the acs_destripe software described above.