|Space Telescope Science Institute|
|ACS Instrument Handbook Cycle 23|
The following characteristics of ACS should be considered when planning ACS observations or archival research:
• The ACS cameras are intended to be used with a single filter. Unfiltered or two-filter imaging yields significantly degraded PSFs (particularly for the WFC), so these modes are typically used only for polarization observations. The polarizers have zero optical thickness, so they can and should be used with another filter.
• 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%. Section 10.4.
• 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 ┼, 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 ┼. 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 WFPC22.214.171.124 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.Figure 5.9: HST Limiting Magnitude for extended sources in 10 hours, as a function of wavelength.
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). There are also health and safety considerations for the MAMA detector. See Section 4.6 for a discussion of bright object limits.Subsequent to the replacement of the ACS CCD Electronics Box during SM4, all WFC images show horizontal striping noise that is roughly constant across each row of read-out in all four WFC amplifiers. This striping is the result of a 1/f noise on the bias reference voltage, and has an approximately Gaussian amplitude distribution with standard deviation of 0.9 electrons. The contribution of the stripes to the global read noise statistics is small, but the correlated nature of the noise may affect photometric precision for very faint sources and very low surface brightnesses.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 or flc.fits), as long as the image meets the crowding requirement stated above. Please see the ACS website for details on running this code.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, are described in Section 3.4 of the ACS Data Handbook.