IRAC Instrument Handbook - IRSA - California Institute of Technology
IRAC Instrument Handbook - IRSA - California Institute of Technology
IRAC Instrument Handbook - IRSA - California Institute of Technology
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<strong>IRAC</strong> <strong>Instrument</strong> <strong>Handbook</strong><br />
Figure 5.12. Pr<strong>of</strong>iles showing the column median versus row values for identifying muxstripe. The<br />
muxstripe is now identifiable between rows 125 and 200 (significantly lower values than the median<br />
background).<br />
From each <strong>of</strong> these median-subtracted arrays, a one-dimensional array <strong>of</strong> the values along each row is<br />
then created, simply by combining the pixel values along the X-dimension. A pr<strong>of</strong>ile that represents the<br />
median versus row is created. For each pr<strong>of</strong>ile, statistics arre calculated to identify any muxstripe. It will<br />
be identified as a deviation larger than 3% <strong>of</strong> the median value for several rows. This will miss the<br />
weakest muxstripe or a case where all readout channels have muxstripe in the same position (cluster <strong>of</strong><br />
very bright stars), but this will be rare. The subset <strong>of</strong> pixels that are affected by the muxstripe is identified<br />
and this column is corrected using the difference <strong>of</strong> the median <strong>of</strong> the ‘clean’ pixels and the median <strong>of</strong> the<br />
affected pixels. The readout channel arrays are then read back out to recreate the original image, and the<br />
corrected image is written to the CBCD file. More information about muxstriping can be found in Section<br />
7.2.2.<br />
5.3 Level 2 (Post-BCD) Pipeline<br />
Pipeline processing <strong>of</strong> <strong>IRAC</strong> data also includes more advanced processing <strong>of</strong> many individual <strong>IRAC</strong><br />
frames together to form more “reduced” data products. Known by the generic title <strong>of</strong> “post-BCD”<br />
processing, this extended pipeline refines the telescope pointing, attempts to correct for residual bias<br />
variations and produces mosaicked images. We do not attempt to improve (relative to the BCD) the point<br />
source or extended emission flux calibration by automatically comparing to a reference source catalog.<br />
The mosaic only includes data from a single observation or AOR.<br />
All <strong>IRAC</strong> BCD images contain a pointing estimate based on the output <strong>of</strong> the Spitzer pointing control<br />
system (star tracker and gyros), i.e., the boresight pointing history file. This initial pointing estimate is<br />
accurate to about 0.5”. The post-BCD pipeline performs additional pointing refinement for all <strong>IRAC</strong><br />
frames. This is achieved by running the SSC point source detector on the channel 1 and 2 frames and<br />
comparing the resultant list <strong>of</strong> point sources to the 2MASS catalog. The results are then averaged, and the<br />
known focal plane <strong>of</strong>fsets between all four channels are applied to produce a “superboresight” pointing<br />
history file, which is then applied to the data during end-<strong>of</strong>-campaign reprocessing. This improves the<br />
pointing accuracy <strong>of</strong> the frame to better than about 0.3”. This refined RA, Dec appears in the header as<br />
the CRVAL1, CRVAL2 keyword values.<br />
The pipeline SSC mosaicker produces a single image (one per band) from many input images. First, the<br />
BCDs are corrected for overlap consistency. The parts <strong>of</strong> the images that overlap are forced to have the<br />
same background value via addition <strong>of</strong> an <strong>of</strong>fset. Then a “fiducial frame” is derived. This is the definition<br />
for the output frame in terms <strong>of</strong> its physical size, projection, and orientation. Because <strong>IRAC</strong> has such a<br />
large fie ld <strong>of</strong> view, projection effects are non-negligible, and the mosaicking and coadding process must<br />
reproject the data. The fiducial frame finder seeks to minimize the amount <strong>of</strong> “blank” area in the output<br />
mosaic by rotating the output projection such that it is aligned with the map axes. This is useful for long<br />
Pipeline Processing 94 Level 2 (Post-BCD) Pipeline