Related papers: Navigating AGN variability with self-organizing ma…
We present a machine learning model to classify Active Galactic Nuclei (AGN) and galaxies (AGN-galaxy classifier) and a model to identify type 1 (optically unabsorbed) and type 2 (optically absorbed) AGN (type 1/2 classifier). We test…
We develop a novel method to identify active galactic nuclei (AGNs) and study the nature of low-luminosity AGNs in the Sloan Digital Sky Survey. This is the second part of a series of papers and we study the correlations between the AGN…
We present the properties of active galactic nuclei (AGN) selected by optical variability in the Subaru/XMM-Newton Deep Field (SXDF). Based on the locations of variable components and light curves, 211 optically variable AGN were reliably…
We present our statistical study of near infrared (NIR) variability of X-ray selected Active Galactic Nuclei (AGN) in the COSMOS field, using UltraVISTA data. This is the largest sample of AGN light curves in YJHKs bands, making possible to…
The extremes of Active Galactic Nuclei (AGN) variability offer valuable new insights into the drivers and physics of AGN. We discuss some of the most extreme cases of AGN variability; the highest amplitudes, deep minima states, extreme…
In this study, we demonstrate some of the caveats in common statistical methods used for analysing astronomical variability timescales. We consider these issues specifically in the context of active galactic nuclei (AGNs) and use a more…
Motivated by upcoming photometric and spectroscopic surveys (Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Manuakea Spectroscopic Explorer), we design the statistical proxies to measure the cadence effects on active…
The morphological classification of active galaxies may be affected by the presence of active galactic nuclei (AGN). In this paper, we provide the most detailed analysis on how different AGN contributions, from 5% to 75%, to the total…
A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high-dimensional input space of the training samples into a low-dimensional space with the topology relations preserved. This makes SOMs…
The investigation of emission line regions within active galaxies (AGNs) has a rich and extensive history, now extending to the use of AGNs and quasars as "standardizable" cosmological indicators, shedding light on the evolution of our…
We present second epoch optical spectra for 30 changing-look (CL) candidates found by searching for Type-1 optical variability in a sample of active galactic nuclei (AGNs) spectroscopically classified as Type 2. We use a random-forest-based…
The variability of active galactic nuclei (AGN) has long held the promise of shedding light on their detailed structure, and possibly other astrophysical phenonema. Different emission mechanisms lead to different patterns of variability in…
The spectra of Active Galactic Nuclei (AGNs) are often characterized by a wealth of emission lines with different profiles and intensity ratios that led to a complicated classification. Their electro-magnetic radiation spans more than 10…
Active Galactic Nuclei (AGNs) are among the most luminous objects in the universe, making them valuable probes for studying galaxy evolution. However, understanding how AGN properties evolve over cosmic time remains a fundamental challenge.…
The advent of new time domain surveys and the imminent increase in astronomical data expose the shortcomings in traditional time series analysis (such as power spectra analysis) in characterising the abundantly varied, complex and…
This work makes use of the VST observations to select variable sources. We use also the IR photometry, SED fitting and X-ray information where available to confirm the nature of the AGN candidates. The IR data, available over the full…
Changing-look active galactic nuclei (CLAGNs) are a unique population of AGNs that exhibit the appearance (turn-on) or disappearance (turn-off) of broad emission lines. This study aims to explore the intrinsic mechanisms of CLAGNs by…
In numerous applicative contexts, data are too rich and too complex to be represented by numerical vectors. A general approach to extend machine learning and data mining techniques to such data is to really on a dissimilarity or on a kernel…
We discuss the very different methods in each wavelength band for selecting and finding Active Galactic Nuclei (AGN). We briefly review the history of the different techniques for finding AGN and compare and contrast the advantages and…
We consider the techniques to distinguish normal star forming (NSF) galaxies and active galactic nuclei (AGN) hosts using optical spectra. The observational data base is a set of 20000 galaxies extracted from the Sloan Digital Sky Survey,…