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Using data from the Wide-field Infrared Survey Explorer (WISE) we show that the mid infrared (MIR) colors of low-luminosity AGNs (LLAGNs) are significanlty different from those of post-asymptotic giant branch stars (PAGBs). This is due to a difference in spectral energy distribution (SEDs), the LLAGNs showing a flat component due to an AGN. Consistent with this interpretation we show that in a MIR color-color diagram the LINERs and the Seyfert~2s follow a power law with specific colors that allow to distinguish them from each other, and from star forming galaxies, according to their present level of star formation. Based on this result we present a new diagnostic diagram in the MIR that confirms the classification obtained in the optical using standard diagnostic diagrams, clearly identifying LINERs and LLAGNs as genuine AGNs.
We determine the 22$mu$m luminosity evolution and luminosity function for quasars from a data set of over 20,000 objects obtained by combining flux-limited Sloan Digital Sky Survey optical and Wide field Infrared Survey Explorer mid-infrared data. We
H{sc i} absorption studies of active galaxies enable us to probe their circumnuclear regions and the general interstellar medium, and study the supply of gas which may trigger the nuclear activity. In this paper, we investigate the detection rate of
We present an all-sky sample of ~ 1.4 million AGNs meeting a two color infrared photometric selection criteria for AGNs as applied to sources from the Wide-Field Infrared Survey Explorer final catalog release (AllWISE). We assess the spatial distribu
We present accurate resolved $WISE$ photometry of galaxies in the combined SINGS and KINGFISH sample. The luminosities in the W3 12$mu$m and W4 23$mu$m bands are calibrated to star formation rates (SFRs) derived using the total infrared luminosity, a
Low Luminosity Active Galactic Nuclei (LLAGNs) are contaminated by the light of their host galaxies, thus they cannot be detected by the usual colour techniques. For this reason their evolution in cosmic time is poorly known. Variability is a propert