http://arxiv.org/abs/2111.03079
We present a sample of 318, $z < 1.5$ active galactic nuclei (AGNs) selected from optical photometric variability in three of the Dark Energy Survey (DES) deep fields (E2, C3, and X3) over a total area of 4.64 deg$^2$. We construct light curves using difference imaging aperture photometry for resolved sources and non-difference imaging PSF photometry for unresolved sources, respectively, and characterize the variability significance. Our DES light curves have a mean cadence of 7 days, a 6 year baseline, and a single-epoch imaging depth of up to $g \sim 24.5$. Using spectral energy distribution fitting, we find 181 out of total 318 variable galaxies are consistent with dwarf galaxies (with $M_{\ast}<10^{9.5}\ M_\odot$ at a median photometric redshift of 0.9). However, our stellar mass estimates are subject to strong model degeneracies and contamination from AGN light. We identify 11 dwarf AGN candidates (a subset at a median photometric redshift of 0.4) by their rapid characteristic timescales ($\sim$ weeks) of optical variability which independently supports the dwarf hypothesis. We confirm the low-mass AGN nature of one source with a high S/N optical spectrum. We present a catalog of variability-selected AGNs with optical light curves and supplementary data, such as X-ray properties and optical spectra, when available. We measure a variable AGN fraction of $\sim 0.008$ between $M_{\ast}\sim10^7\ M_\odot$ and $\sim10^{11}\ M_\odot$, with no evidence for a stellar mass dependence. This work demonstrates the feasibility of using optical variability to identify AGNs with lower black hole masses than other methods in deep fields, which may be more “pristine” analogs of supermassive black hole (SMBH) seeds. Further work is needed to study the variability characteristics of dwarf AGNs and improve the statistics to robustly distinguish between seeding mechanisms of SMBHs.
C. Burke, X. Liu, Y. Shen, et. al.
Mon, 8 Nov 21
44/69
Comments: 20 pages, 22 figures incl. 3 appendices; submitted to MNRAS
You must be logged in to post a comment.