IRAC Instrument Handbook - IRSA - California Institute of Technology

Point Source Fitting IRAC Images
with a PRF
164
IRAC Instrument Handbook
2. Artifact correction: use CBCDs or preprocess your IRAC BCD data to remove or mask artifacts
as necessary.
3. Rmasks: assuming the data were taken with overlapping (C)BCDs, make a mosaic with MOPEX,
doing outlier rejection, and creating Rmasks. Then include the appropriate Rmasks with your
input data to APEX.
4. PRF: put the center Hoffmann 100x PRF (the one with ...col129_row129...) in your MOPEX cal/
subdirectory for command-line (this will be PRF_FILE_NAME in the namelist file), or type it
into the GUI. Although you can run APEX with just the center PRF, we recommend using the
whole PRF Map set, as it noticeably improves the quality of the fits for sources outside of the
central region of the arrays. To do this, create a table like the one linked from the PSF/PRF
section of the IRAC web pages (substituting appropriate filenames and paths). PRF position
refers to the bottom-left corner of the region of size NAXIS1, NAXIS2 over which the PRF is
valid (in native pixels). This will be PRFMAP_FILE_NAME in a namelist, or you can type it into
the GUI. Figure C.5 shows how the PRFs are distributed over the arrays.
5. Normalization Radius: the Hoffmann PRFs require a normalization that matches the IRAC
calibration radius. In the Sourcestimate block, set Normalization_Radius = 1000 (since it is in
PRF pixels and the sampling is 100x).
6. Run APEX. If doing command-line for IRAC1, edit the default namelist for your data and run:
apex.pl -n apex_I1_yourdata.nl
7. PRF Flux: The PRF flux column is called ''flux'' in the extract.tbl output file, and the units are
micro-Jy. These need to be divided by the appropriate photometric correction factors from Table
C.1: 1.021 (IRAC 1), 1.012 (IRAC2), 1.022 (IRAC3) and 1.014 (IRAC4).
8. PRF Flux Uncertainty: The column labelled ''delta_flux'' is the formal uncertainty from the leastsquares
fit. It will in general underestimate the flux uncertainty. Do not use the column labelled
“SNR”' for IRAC, as it only takes into account the background noise, and ignores the Poisson
(shot) noise term which typically dominates the error. The best estimate is the aperture
uncertainty (calculated from the data uncertainties) in a 3 pixel radius. This covers the majority of
the PSF without going too far out. (For the default namelist, the relevant uncertainty is in column
''ap_unc2'' [microJy].)
9. Array Location-Dependent Photometric Corrections: Multiply the (C)BCDs by the correction
image ("...photcorr...") and run APEX on the resulting images. The fluxes will be correct for
"blue" sources (where blue means having the colors of an early-type stellar photosphere). For
"red" sources (objects with colors close to that of the zodiacal light) use fluxes derived from
running APEX on unmodified CBCDs.
10. Color Correction: This is the correction needed to get the right monochromatic flux if your source
spectrum is different from the reference spectrum used to calibrate the IRAC filters
( νFν = constant). There is a good discussion of this in Chapter 4 of this Handbook.
If all these steps are followed, then the systematic error in the flux measurement for bright, isolated point
sources should be ~1%. A comparable systematic error exists in the flux density scale. Background
estimation errors will contribute significantly to the error budget for fainter sources and in confused
fie lds.