IRAC Instrument Handbook - IRSA - California Institute of Technology

Performing Photometry on IRAC
Images
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IRAC Instrument Handbook
uncertainty in the photometry of IRAC images. For observations that well sample the array for
each sky position the effect will average out. MOPEX software now is capable of creating these
correction mosaics for you. If you want to make the BCD-matched photometric correction images
yourself, first copy the FITS header keywords CTYPE1, CTYPE2, CRPIX1, CRPIX2, CRVAL1,
CRVAL2, CD1_1, CD1_2, CD2_1, CD2_2 from the headers of the BCDs to the headers of the
photometric correction images in each channel using your favorite FITS manipulation software.
Thus, you make the same number of photometric correction images (otherwise identical except
for the keyword information) as there are CBCDs in each channel. The correction images must be
divided by the pixel solid angle correction images before mosaicking them together, because the
pixel solid angle effect is essentially corrected for already in the photometric correction images
and thus needs to be "canceled out" before running the images through MOPEX (which corrects
for this effect). Then, copy the namelist you used to make the CBCD mosaic images into some
other name, and edit the namelist to disable all the outlier rejection modules. Do not run the
fiducial image frame module but instead point MOPEX to the existing "FIF.tbl" file used for
generating the corresponding CBCD mosaic. Next, specify the RMASK_LIST file (generate a file
listing the rmasks and their path, as created by the mosaicker run for the corresponding CBCDs).
Finally, make the correction image mosaic with MOPEX.
6. Perform photometry with your favorite software. Aperture photometry is preferred over PRFfitting
photometry due to the undersampled nature of the data. To properly estimate the
uncertainties in your photometry, the uncertainty images provided with the CBCDs can be used
and mosaicked into an uncertainty mosaic. The CBCD uncertainties are slightly conservative as
they take into account the uncertainties in each pipeline calibration step. For packages that
estimate noise directly from the data assuming Poisson noise, you can convert the mosaic into
electron units, so as to calculate the uncertainty due to source shot noise and background
correctly. The conversion from MJy/sr is ∗GAIN ∗ EXPTIME / FLUXCONV where GAIN,
EXPTIME and FLUXCONV are the keywords from the CBCD header. In determining the noise,
the coverage of the observation at the position of your target should also be taken into account
(e.g., by entering the correct number of frames in DAOPHOT or by dividing the noise by the
square root of coverage, from the coverage mosaic at the position of each target). Your aperture
photometry software should of course subtract the appropriate background (usually in an annulus
around the source).
7. Apply aperture correction, found in Chapter 4 of this handbook, if you perform aperture
photometry in an aperture different from the 10 pixel radius aperture used for IRAC calibration or
determine the background by other means than an annulus. Observers can determine their own
aperture corrections by downloading IRAC calibration star observations from the Spitzer
Heritage Archive, and comparing the photometry to that published in the IRAC Calibration Paper
(Reach et al. 2005, [23]).
8. Observers should apply the array location-dependent photometric correction for blue sources and
the appropriate color correction for all sources (based on the spectral energy distribution of the
source). Determine the array location-dependent photometric correction (for blue compact
sources) from the correction mosaic, constructed in step 5 above, by looking at the values of the
pixels at the positions of the peaks of your point sources. Apply a color correction from Chapter 4
of this handbook using the tabulated values, if appropriate, or calculate the color correction for a
source spectral energy distribution as done in that chapter. To calculate a color correction, you