Point source fitting of IRAC images using a PRF

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A "How To" guide for IRAC point source photometry with APEX

We recommend that APEX in point source fitting mode be used only directly on the BCD data using the Hoffmann PRFs modified for use with APEX as described in Section 4. We do not recommend trying to fit point sources on the mosaic as the mosaicking process both blurs the undersampled point sources, and loses the pixel phase information. We also do not recommend using the prf_estimate tool to derive a PRF from IRAC data, as it does not deal correctly with the undersampling of the PRF.

We list below the steps towards producing a point source list using APEX in multiframe mode (i.e. on the stack of BCDs).

1. Source fitting versus aperture fluxes: ask yourself if point source photometry is appropriate for your sources of interest. If in doubt after reading about photometry of moderately resolved sources, use aperture photometry with APEX or Sextractor.

2. Artifact correct: preprocess your IRAC data to remove or mask artifacts as necessary.

3. Rmasks: assuming the data are taken with overlapping BCDs, make a mosaic with MOPEX, doing outlier rejection, and creating Rmasks. Then include the appropriate Rmask 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 this (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 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, units are microJy These need to be divided by the appropriate photometric correction factors from Table 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 least-squares 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. For now, 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: This is described on the IRAC Photometry web page. Multiply the 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 BCDs.

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 ( ). There is a good discussion of this in the IRAC Data handbook.

If all these steps are followed, then the systematic error in the flux measurement process 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 fields.

Figure 5: The 25 PRF positions on an IRAC BCD.