This is a quick guide for performing point source photometry on IRAC images.
A. Point Source Photometry on a Mosaic
1. If you are only interested in photometry down to about 10% accuracy and have bright point sources, you can usually perform photometry on the pipeline mosaic. Set the aperture size to 10 native (≈ 1.2 arcseconds) or 20 mosaic (≈ 0.6 arcseconds) pixels and the sky annulus to between 12 and 20 native (≈ 1.2 arcseconds) pixels (or between ≈ 24 and 40 0.6 arcseconds mosaic pixels). The IRAC calibration is based on an aperture of this size (see Section 4.3), so for this aperture no aperture correction is necessary. For fainter stars, it is better to use a smaller aperture and then apply an aperture correction (see Section 4.7). Remember that the units of the images are in MJy/sr, so you need to convert your measured values into flux density units in micro-Jy, by accounting for the pixel size in steradians. Conversion into magnitudes is magnitudes = -2.5*log10(f/f(0)), where f is your measured flux density and f(0) is the zero magnitude flux density. If using software such as “phot” or “qphot” in IRAF/DAOPHOT that requires a magnitude zeropoint, the “zmag” keyword in photpars should be set to 18.80 (channel 1), 18.32 (channel 2), 17.83 (channel 3) and 17.20 (channel 4) if using a mosaic pixel scale of 0.6 arcseconds/pixel. Other zmag values will be needed for other pixel sizes. Note that if you require photometry to a higher accuracy than 10% – 20%, you should follow the steps listed below.
2. Examine your data (CBCDs) and identify artifacts that could affect your photometry and that need to be corrected. See the Contributed Software page for useful tools at
3. First perform artifact mitigation on the pipeline-produced CBCDs. While the pipeline-reduced CBCD files are mostly artifact-free, some residual artifacts remain. For example, the pipeline and contributed software have difficulty recognizing very saturated pixels that produce artifacts. As a result, they will not usually correct artifacts from very saturated point sources or from extended saturated regions. Data at 5.8 and 8.0 µm exhibiting the bandwidth effect (see Section 7.2.3) should be masked before performing photometry.
4. Make a mosaic of artifact-corrected images (see Section 8.4.3), for example with the MOPEX package. When creating the mosaic, the overlap correction option should be used in MOPEX, most importantly in channels 3 and 4, to match the backgrounds. Inspect the mosaic to confirm that outlier rejection is acceptable. If not, then re-mosaic with more appropriate MOPEX parameters. Comparing mosaics of adjacent channels on a per-pixel basis will readily identify if outliers remain in a mosaic. The mosaic coverage maps should be inspected to verify that the outlier rejection has not preferentially removed data from actual sources. If the coverage map systematically shows lower weights on actual sources, then the rejection is too aggressive and should be redone.
5. If you are interested in blue point sources (sources with spectral energy distributions, SEDs, that decline toward the longer wavelength IRAC passbands) you should create an array location-dependent photometric correction image mosaic (see Section 4.5). If you are interested in only red sources (with SEDs that rise toward the longer wavelength IRAC passbands), you do not need to apply the photometric correction images and make a mosaic out of them. We recommend making a correction mosaic, instead of multiplying the correction images with the CBCDs and then mosaicking these CBCDs together, since you may need to iterate this a few times or you may have both red and blue sources in the field, and thus the correction only applies to a subset of sources. This location-dependent effect is as large as 10%. It is the dominant source of 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 PRF-fitting 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 the uncertainties into account in each pipeline calibration step. For packages that estimate noise directly from the data assuming Poisson noise, in low background cases 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).
8. Observers should apply the array location-dependent photometric correction for blue sources and the appropriate color correction (see Section 4.4) 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 will need the IRAC spectral response curves a
9. Color corrections are typically a few percent for stellar and blackbody sources, but can be more significant for sources with ISM-like source functions (50% – 250% depending on spectrum and passband). Measured flux density is the flux density at the effective wavelength of the array: 3.550, 4.493, 5.731, and 7.872 µm, for channels 1 – 4, respectively.
10. A pixel phase correction (see Section 4.6) to the measured channel 1 flux densities should then be considered. More information on the pixel phase correction can be found in Chapter 4 of this Handbook. This effect is as large as 4% peak-to-peak at 3.6 µm and < 1% at 4.5 µm. To apply a correction for mosaicked data is difficult, as the pixel phase correction depends on the placement of the source centroid on each CBCD. For well-sampled data the pixel phase should average out for the mosaic. For precise photometry in low coverage data, the source centroids on the CBCDs should be measured and the phase corrections averaged together and applied to the final source photometry.
B. Point Source Photometry on a Mosaic
Although most of the time it is a good idea to use the mosaic for performing photometry, performing photometry on the (C)BCD stack is important for variability studies and can be useful for faint sources as one can measure N out of M statistics (how many times you found the source). Using (C)BCDs is also required when performing absolute photometry (as indicated below). For absolute photometry, you can also refer to the IRAC calibration papers by Reach et al. (2005) and Carey et al. (2012). When performing source profile fitting, performing photometry on the (C)BCD stack is better as the phase information of the PRF is preserved.
1. Examine your data (CBCDs) and identify artifacts that could affect your photometry and that need to be corrected.
2. First perform artifact mitigation, for example by using the Contributed Software at
on the pipeline-produced CBCDs. While the pipeline-reduced CBCD files are mostly artifact-free, some residual artifacts remain. The pipeline and contributed software have difficulty recognizing very saturated pixels that produce artifacts. As a result, they will not usually correct artifacts from very saturated point sources and extended saturated regions. Data at 5.8 and 8.0 µm exhibiting the bandwidth effect should be masked. If performing aperture photometry on the CBCDs, a particular CBCD should not be used for a source when there are masked (bad) data in the source aperture.
3. Make a mosaic of artifact-corrected images, for example with the MOPEX package (see Section 8.4.3). This needs to be done to create the proper rmask files to be applied to the CBCDs when performing APEX-based photometry on them, and also to get a nice comparison of CBCD-revealed and mosaic-revealed image features. When creating the mosaic, the overlap correction option should be used in MOPEX, most importantly in channels 3 and 4, to match the backgrounds. Inspect the mosaic to confirm that outlier rejection is acceptable, and if not, then remosaic with more appropriate parameters. Comparing mosaics of adjacent channels on a per-pixel basis will readily identify if outliers remain in a mosaic. The mosaic coverage maps should be inspected to verify that the outlier rejection has not preferentially removed data from actual sources. If the coverage map systematically shows lower weights on actual sources, then the rejection is too aggressive and should be redone. One result of making the mosaic is the production of rmask files which identify bad pixels in the CBCDs. One should apply the rmasks when performing the photometry in the next step so that bad pixels are not included within the apertures.
4. Perform photometry with your favorite software. The PRFs supplied can be used with APEX in multiframe mode for point source fitting. A “How To” guide and details of the validation are presented in Appendix C. 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 CBCDs 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. For accurate photometry, a good background estimate is required. When performing point source fitting with APEX, the parameters of the medfilter module should be tuned to ensure good background subtraction. For aperture photometry, the background estimate can be obtained from an annulus around the source (but note that the radii of the background annulus will affect the aperture correction). Also for aperture photometry, the centroids of the point sources can be estimated with the contributed box cenroider code:
5. Observers should apply the array location-dependent photometric correction (see Section 4.5 and Figure 4.5) for blue sources and the appropriate color correction for all sources (based on the spectral energy distribution of the source). The photometric array location-dependent correction images are linked from the IRAC web pages at
6. 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 will need the IRAC spectral response curves, which are also available on IRSA’s IRAC web pages. Color corrections are typically a few percent for stellar and blackbody sources, but can be more significant for sources with ISM-like source functions (50% - 250% depending on the spectrum and passband). The measured flux density is the flux density at the effective wavelength of the array: 3.550, 4.493, 5.731, and 7.872 µm, for channels 1 - 4, respectively.
7. Pixel phase corrections (see Section 4.6) need to be applied in channels 1 and 2. The PRFs include the pixel phase effect, so the single mean correction given in Appendix C is adequate. In the case of aperture fluxes, all the fluxes need correction. More information on the pixel phase correction can be found in Chapter 4 of this Handbook. You can use the contributed code at
for warm data. Note that this effect is as large as 4% peak-to-peak at 3.6 µm and < 1% at 4.5 µm (channels 3 and 4 do not have a pixel phase correction). Steps 5 and 6 may be conveniently performed using the contributed code at
but this assumes that you will use the 3 pixel radius for aperture photometry, with the 3 - 7 pixel radius annulus for background determination (and requires a corresponding aperture correction in the next step).
8. 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. The 10 pixel radius with 12 - 20 pixel background annulus is ideal for measuring calibration star photometry as those values were used in IRAC flux density calibration. Observers can determine their own aperture corrections by downloading IRAC calibration star observations (c.f. Table 4.1 and Table 4.8) from the Spitzer Heritage Archive and comparing the photometry to that published in the IRAC Calibration Paper (Reach et al. 2005). Aperture corrections for fitted fluxes are given in Appendix C.
9. Combine photometry from CBCDs, taking uncertainties into account, to generate a robust, weighted mean value. Verify that the dispersion in these measurements is comparable to the uncertainty of the individual measurements (if not, use the dispersion until you track down the source of extra error, e.g., bad pixels/cosmic rays in source). Note that what you have actually measured is F*K* in terms of Table 4.1. If you have tried to measure calibration stars, your results may slightly differ from those in Table 4.1, as the Table values are based on the average results for all the calibration stars, and therefore differ from the values measured for each individual star.
10. Apply a color correction. If you want a flux density that can be compared to any instrument’s absolute flux density measurement, then calculate a color correction as explained in Section 4.4, and divide F*K* by the color correction to arrive at F*.
