paper

The Accuracy of Morphological Decomposition of Active Galactic Nucleus Host Galaxies

arXiv:0804.1363 · doi:10.1086/589827

Abstract

In order to assess the accuracy with which we can determine the morphologies of AGN host galaxies, we have simulated more than 50,000 ACS images of galaxies with z < 1.25, using image and noise properties appropriate for the GOODS survey. We test the effect of central point-source brightness on host galaxy parameter recovery with a set of simulated AGN host galaxies made by adding point sources to the centers of normal galaxies. We extend this analysis and also quantify the recovery of intrinsic morphological parameters of AGN host galaxies with a set of fully simulated inactive and AGN host galaxies. We can reliably separate good from poor fit results using a combination of reasonable error cuts, in the regime where L_{host}:L_{PS} > 1:4. We give quantitative estimates of parameter errors as a function of host-to-point-source ratio. In general, we separate host and point-source magnitudes reliably at all redshifts; point sources are well recovered more than 90% of the time, although spurious detection of central point sources can be as high as 25% for bulge-dominated sources. We find a general correlation between Sersic index and intrinsic bulge-to-total ratio, such that a host galaxy with Sersic n < 1.5 generally has at least 80% of its light from a disk component. Likewise, "bulge-dominated" galaxies with n > 4 typically derive at least 70% of their total host galaxy light from a bulge, but this number can be as low as 55%. Single-component Sersic fits to an AGN host galaxy are statistically very reliable to z < 1.25 (for ACS survey data like ours). In contrast, two-component fits involving separate bulge and disk components tend to over-estimate the bulge fraction by ~10%, with uncertainty of order 50%.

45 pages, 20 figures, submitted to ApJ ; Accepted Version -- additions to introduction and conclusions; title changed, was "Simulations of AGN Host Galaxy Morphologies"

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