c2d Data flow diagram BCD from SSC Texas SAO Quality Analysis and Improved Calibrated Data Mapping team

c2d BCD products Data Contents BCDBasic calibrated data – dark-subtracted, linearized, flat-fielded, flux-calibrated Raw16-bit unreduced array data PmaskData quality flag image for calibration images associated with the DCE DmaskData quality flag image for the DCE LatentsLatent image prediction C-RayProbability of CR event for a pixel FlatFlat field divided into raw data DarkDark image subtracted from raw data LinearityLinearity correction factor

c2d IRAC calibration and characterization  Characterize residual instrumental effects in Basic Calibrated Data (BCD).  Monitor image quality in BCD.  Provide Improved Calibrated Data (ICD).  Work with Instrument Team (IT) at SAO and Instrument Support Team (IST) at SSC to implement improved processing.  Provide feedback to c2d team on observing strategies.  Deliver ICD to mapping teams in 2-4 days. Myers, Allen, Porras

c2d Zeroth level QA  Is AOR complete?  Are images uncorrupted?  Did AOT execute correctly?  Is pointing reconstruction correct?  Do images in map overlap sufficiently?  Are images in focus?  Do images suffer from jitter?  Are the images badly under or over exposed?  Is the background level correct?  Were there dark/flat calibration errors?  Was there significant stray/scattered light? The SSC will do this checking for each BQD.

c2d Higher level QA  Do simple image statistics. median, sigma flux distribution of extracted sources flux distribution of background pixels (may be able to access SSC BCD statistics)  Monitor image quality over time – track changes in focus or PSF.  Check cosmic ray, latent identification, etc.  Create and maintain database with QA “scores” (statistics and image quality measures).  Primary tools: IRAF/IDL and “QLVT” (or similar).

c2d Putting the “I” in ICD  Improved dark subtraction or flat field division e.g. using different set of calibrator images.  Improved cosmic ray detection, latents detection. e.g. experiment with detection/sensitivity thresholds.  Improved astrometric solution. e.g. fits to 2MASS (better than SSC pipeline?)  Primary tool: SAO pipeline (hear about later).

c2d Data volume  Clouds 2 dithers x 4 bands x 2 (HDR) + 2 dithers x 4 bands) x 2320 pointings = 55,680 images  Cores = 8500 images  Stars = 2880 images  BCD = 6.71 images x 3.5 Mbytes/image = 235 Gbytes Store on 2x 144 GB NetApp data disks

c2d Data rate  Total of 67,000 images obtained over 2.5 years  1 IRAC PAO = 10 days == 17.4 PAO/yr == 43.5 PAO  67,000 images / 43.5 PAO = 1540 images/PAO = 154 images obtained per day assume 2 FTE’s == 77 images / day / person  Volume = 540 Mbytes per day  Transfer rate Texas SAO = 1.5 Mbytes/sec ???

c2d IRAC health & safety  ~500 Housekeeping channels every 30 sec.  Automatically delivered to SAO every 24 hrs, along with S/C command history and fault report.  Automatic limit checking, statistics. Web report generated.  Software already in place to do trending analysis, merging of cmd history and HK.