Double-peaked [O III] profiles in active galactic nuclei (AGNs) may provide evidence for the existence of dual AGNs, but a good diagnostic for selecting them is currently lacking. Starting from ∼ 7000 active galaxies in SDSS DR7, we assemble a sample of 87 type 2 AGNs with double-peaked [O III] profiles. The nuclear obscuration in the type 2 AGNs allows us to determine redshifts of host galaxies through stellar absorption lines. We typically find that one peak is redshifted and another is blueshifted relative to the host galaxy. We find a strong correlation between the ratios of the shifts and the double peak fluxes. The correlation can be naturally explained by the Keplerian relation predicted by models of co-rotating dual AGNs. The current sample statistically favors that most of the [O III] double-peaked sources are dual AGNs and disfavors other explanations, such as rotating disk and outflows. These dual AGNs have a separation distance at ∼ 1 kpc scale, showing an intermediate phase of merging systems. The appearance of dual AGNs is about ∼ 10 −2 , impacting on the current observational deficit of binary supermassive black holes with a probability of ∼ 10 −4 (Boroson & Lauer).

Double-peaked [O III] profiles in active galactic nuclei (AGNs) may provide evidence for the existence of dual AGNs, but a good diagnostic for selecting them is currently lacking. Starting from ∼ 7000 active galaxies in SDSS DR7, we assemble a sample of 87 type 2 AGNs with double-peaked [O III] profiles. The nuclear obscuration in the type 2 AGNs allows us to determine redshifts of host galaxies through stellar absorption lines. We typically find that one peak is redshifted and another is blueshifted relative to the host galaxy. We find a strong correlation between the ratios of the shifts and the double peak fluxes. The correlation can be naturally explained by the Keplerian relation predicted by models of co-rotating dual AGNs. The current sample statistically favors that most of the [O III] double-peaked sources are dual AGNs and disfavors other explanations, such as rotating disk and outflows. These dual AGNs have a separation distance at ∼ 1 kpc scale, showing an intermediate phase of merging systems. The appearance of dual AGNs is about ∼ 10 −2 , impacting on the current observational deficit of binary supermassive black holes with a probability of ∼ 10 −4 (Boroson & Lauer).

In the third catalog of active galactic nuclei detected by the Fermi-LAT (3LAC) Clean Sample, there are 402 blazar candidates of uncertain type (BCUs). Due to the limitations of astronomical observation or intrinsic properties, it is difficult to classify blazars using optical spectroscopy. The potential classification of BCUs using machine-learning algorithms is essential. Based on the 3LAC Clean Sample, we collect 1420 Fermi blazars with eight parameters of γ-ray photon spectral index; radio flux; flux density; curve significance; the integral photon flux in 100–300 MeV, 0.3–1 GeV, and 10–100 GeV; and variability index. Here we apply four different supervised machine-learning (SML) algorithms (decision trees, random forests, support vector machines, and Mclust Gaussian finite mixture models) to evaluate the classification of BCUs based on the direct observational properties. All four methods can perform exceedingly well with more accuracy and can effectively forecast the classification of Fermi BCUs. The evaluating results show that the results of these methods (SML) are valid and robust, where about one-fourth of sources are flat-spectrum radio quasars (FSRQs) and three-fourths are BL Lacertae (BL Lacs) in 400 BCUs, which are consistent with some other recent results. Although a number of factors influence the accuracy of SML, the results are stable at a fixed ratio 1:3 between FSRQs and BL Lacs, which suggests that the SML can provide an effective method to evaluate the potential classification of BCUs. Among the four methods, Mclust Gaussian Mixture Modeling has the highest accuracy for our training sample (4/5, seed = 123).