Related papers: Navigating AGN variability with self-organizing ma…

While Multi-view Graph Neural Networks (MVGNNs) excel at leveraging diverse modalities for learning object representation, existing methods assume identical local topology structures across modalities that overlook real-world discrepancies.…

Observations and theoretical simulations suggest that the large scale environment plays a significant role in how galaxies form and evolve and, in particular, whether and when galaxies host an actively accreting supermassive black hole in…

Purpose: To objectively assess new medical imaging technologies via computer-simulations, it is important to account for the variability in the ensemble of objects to be imaged. This source of variability can be described by stochastic…

The detection of new clusters of galaxies or the study of known clusters of galaxies in X-rays can be complicated by the presence of X-ray point sources, the majority of which will be active galactic nuclei (AGN). This can be addressed by…

We present morphological classifications for the hosts of 1189 hard X-ray selected (14-195 keV) active galactic nuclei (AGNs) from the Swift-BAT 105-month catalog as part of the BAT AGN Spectroscopic Survey (BASS). BASS provides a powerful…

We investigate the physical nature of active galactic nuclei (AGNs) using machine learning (ML) tools. We show that the redshift, $z$, bolometric luminosity, $L_{\rm Bol}$, central mass of the supermassive black hole (SMBH), $M_{\rm BH}$,…

In order to derive statistical properties of a complete X-ray selected sample of AGN we used the classification spectra of the RASS Selected Areas-North survey to study the luminosities, redshifts, X-ray/visual flux ratios, line widths, and…

Graph Convolutional Networks (GCNs) have gained great popularity in tackling various analytics tasks on graph and network data. However, some recent studies raise concerns about whether GCNs can optimally integrate node features and…

We analyse different photometric and spectroscopic properties of active galactic nuclei (AGNs) and quasars (QSOs) selected by their mid-IR power-law and X-ray emission from the COSMOS survey. We use a set of star-forming galaxies as a…

While there are numerous criteria for photometrically identifying active galactic nuclei (AGNs), searches in the optical and UV tend to exclude galaxies that are highly dust obscured. This is problematic for constraining models of AGN…

Large time-domain surveys provide a unique opportunity to detect and explore variability of millions of sources on timescales from days to years. Broadband photometric variability can be used as the key selection criteria for weak type-I…

In this paper we explore the applicability of the unsupervised machine learning technique of Self Organizing Maps (SOM) to estimate galaxy photometric redshift probability density functions (PDFs). This technique takes a spectroscopic…

We present an optical variability analysis and comparison of the samples of Seyfert 1 and 2 galaxies, selected from the \textit{Swift} 9-month BAT catalog, using the light curves from Transiting Exoplanet Survey Satellite (TESS) and All-Sky…

Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in…

We present the identification of 42 narrow-line active galactic nuclei (type-2 AGN) candidates in the two deepest observations of the JADES spectroscopic survey with JWST/NIRSpec. The spectral coverage and the depth of our observations…

Measuring the redshift of active galactic nuclei (AGNs) requires the use of time-consuming and expensive spectroscopic analysis. However, obtaining redshift measurements of AGNs is crucial as it can enable AGN population studies, provide…

The high quality light curves of Kepler space telescope make it possible to analyze the optical variability of AGNs with an unprecedented time resolution. Studying the asymmetry in variations could give independent constraints on the…

The outshining light from active galactic nuclei (AGNs) poses significant challenges in studying the properties of AGN host galaxies. To address this issue, we propose a novel approach which combines image decomposition and spectral energy…

The anisotropic nature of active galactic nuclei (AGN) is thought to be responsible for the observational differences between type-1 (pole-on) and type-2 (edge-on) nearby Seyfert-like galaxies. In this picture, the detection of emission…

We used Transiting Exoplanet Survey Satellite (TESS) data to identify 29 candidate active galactic nuclei (AGNs) through their optical variability. The high-cadence, high-precision TESS light curves present a unique opportunity for the…