相关论文: Variability-based AGN selection using image subtra…

We present an analysis of 12 optically selected dual AGN candidates at $z < 0.34$. Each candidate was originally identified via double-peaked [O III] $\lambda$5007 emission lines, and have received follow-up $Chandra$ and $HST$…

We study the properties of a sample of 211 heavily-obscured Active Galactic Nucleus (AGN) candidates in the Extended Chandra Deep Field-South selecting objects with f_24/f_R>1000 and R-K>4.5. Of these, 18 were detected in X-rays and found…

We calculate the angular correlation function for a sample of 170,000 AGN extracted from the Wide-field Infrared Survey Explorer (WISE) catalog, selected to have red mid-IR colors (W1 - W2 > 0.8) and 4.6 micron flux densities brighter than…

We have employed a reliable technique of classification of Active Galactic Nuclei (AGN) based on the fit of well-sampled spectral energy distributions (SEDs) with a complete set of AGN and starburst galaxy templates. We have compiled…

We present a systematic investigation of extremely X-ray variable active galactic nuclei (AGNs) in the $\approx 5.3~{\rm deg}^2$ XMM-SERVS XMM-LSS region. Eight variable AGNs are identified with rest-frame 2 keV flux density variability…

We present the results of a study of different statistical methods currently used in the literature to analyse the (micro)variability of active galactic nuclei (AGNs) from ground-based optical observations. In particular, we focus on the…

Intensive broadband reverberation mapping campaigns have shown that AGN variability is significantly more complex than expected from disc reverberation of the variable X-ray illumination. The UV/optical variability is highly correlated and…

Context: Finding Active Galactic Nuclei (AGN) behind the Magellanic Clouds (MCs) is difficult because of the high stellar density in these fields. Although the first AGN behind the Small Magellanic Cloud (SMC) were reported in the 1980s, it…

Modern X-ray telescopes have detected hundreds of thousands of X-ray sources in the universe. However, current methods to classify these sources using the X-ray data themselves suffer problems - detailed X-ray spectroscopy of individual…

We present a sample of 18 optically-selected and X-ray detected spatially offset active galactic nuclei (AGN) from the Sloan Digital Sky Survey (SDSS). In 9 systems, the X-ray AGN is spatially offset from the galactic stellar core that is…

Population synthesis models of actively accreting super-massive black holes (or active galactic nuclei -- AGN) predict a large fraction that must grow behind dense, obscuring screens of gas and dust. Deep X-ray surveys are thought to have…

We explore spectroscopic and photometric methods for identifying high-redshift galaxies containing an Active Galactic Nucleus (AGN) with JWST observations. After demonstrating the limitations of standard optical methods, which appear…

The scarce optical variability studies in spectrally classified Type 2 active galactic nuclei (AGNs) have led to the discovery of anomalous objects that are incompatible with the simplest unified models (UM). This paper focuses on the…

We present a large sample of infrared-luminous candidate active galactic nuclei (AGNs) that lack X-ray detections in Chandra, XMM-Newton, and NuSTAR fields. We selected all optically detected SDSS sources with redshift measurements,…

The X-ray color (hardness ratio) of optically undetected X-ray sources can be used to distinguish obscured active galactic nuclei (AGNs) at low and intermediate redshift from viable high-redshift (i.e., z>5) AGN candidates. This will help…

For measurement of the AGN luminosity function and its evolution, X-ray selection samples all types of AGN and provides reduced obscuration bias in comparison with UV-excess or optical surveys. The apparent decline in optically-selected…

The classic classification scheme for Active Galactic Nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs (CSAGNs). The physical mechanism behind this phenomenon is still a matter of…

We use machine learning techniques to investigate their performance in classifying active galactic nuclei (AGNs), including X-ray selected AGNs (XAGNs), infrared selected AGNs (IRAGNs), and radio selected AGNs (RAGNs). Using known physical…

Optical rest-frame spectroscopic diagnostics are usually employed to distinguish between star formation and AGN-powered emission. However, this method is biased against dusty sources, hampering a complete census of the AGN population across…

We present a study of Spitzer/IRAC and X-ray active galactic nuclei (AGNs) selection techniques in order to quantify the overlap, uniqueness, contamination, and completeness of each. We investigate how the overlap and possible contamination…