Related papers: An automated activity classification tool for opti…
The most rapidly evolving regions of galaxies often display complex optical spectra with emission lines excited by massive stars, shocks and accretion onto supermassive black holes. Standard calibrations (such as for the star formation…
We use the sample of emission-line nuclei derived from a recently completed optical spectroscopic survey of nearby galaxies to quantify the incidence of local (z = 0) nuclear activity. Consistent with previous studies, we find detectable…
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…
Coronal lines are a powerful, yet poorly understood, tool to identify and characterize Active Galactic Nuclei (AGNs). There have been few large scale surveys of coronal lines in the general galaxy population in the literature so far. Using…
Using an unconventional single line diagnostic that unambiguously identifies AGNs in composite galaxies we report statistical differences in the properties (stellar age, [OII] luminosity, colour) between active and inactive galaxies at…
In this study, we use the SWIFT/BAT AGN sample, which has received extensive multiwavelength follow-up analysis as a result of the BAT AGN Spectroscopic Survey (BASS), to develop a diagnostic for nuclear obscuration by examining the…
From a parent catalog of 561 changing-look active galactic nuclei (CL-AGNs) identified by Guo et al. (2025), we investigate the evolutionary sequence of broad emission lines using a redshift-selected subset (0.35 < z < 0.45) of 54 CL-AGNs…
Motivated by theoretical expectations that Nuclear Star Clusters (NSCs) in galactic centers may provide a favorable environment for super-massive black holes to form and/or efficiently grow, we set out to measure the fraction of nearby…
Mid-infrared diagnostics are presented for a large portion of the Spitzer Infrared Nearby Galaxies Survey (SINGS) sample plus archival data from the Infrared Space Observatory and the Spitzer Space Telescope. Our main result is that these…
The Spitzer Space Telescope revolutionized studies of Active Galactic Nuclei (AGNs). Its combined sensitivity and mapping speed at mid-infrared wavelengths revealed a substantial population of highly-obscured AGNs. This population implies a…
Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…
We present results of recurrence analysis of 46 active galactic nuclei (AGN) using light curves from the 157-month catalog of the Swift Burst Alert Telescope (BAT) in the 14-150 keV band. We generate recurrence plots and compute recurrence…
Variability has proven to be a powerful tool to detect active galactic nuclei (AGN) in multi-epoch surveys. The new-generation facilities expected to become operational in the next few years will mark a new era in time-domain astronomy and…
Low luminosity active galactic nuclei (LLAGN) probe accretion physics in the low Eddington regime and can provide additional clues about galaxy evolution. AGN variability is ubiquitous and thus provides a reliable tool for finding AGN. We…
In this paper we discuss an application of machine learning based methods to the identification of candidate AGN from optical survey data and to the automatic classification of AGNs in broad classes. We applied four different machine…
Understanding the connection between active galactic nuclei and star-formation (the AGN-SF connection) is one of the longest standing problems in modern astrophysics. In the age of large Integral Field Unit (IFU) surveys, studies of the…
The artificial neural network (ANN) is a well-established mathematical technique for data prediction, based on the identification of correlations and pattern recognition in input training sets. We present the application of ANNs to predict…
Using artificial neural network (ANN) predictions of total infra-red luminosities (LIR), we compare the host galaxy star formation rates (SFRs) of ~21,000 optically selected active galactic nuclei (AGN), 466 low excitation radio galaxies…
X-ray emission detection in a galaxy is one of the efficient tools for selecting Active Galactic Nuclei (AGNs). However, many X-ray-selected AGNs are not easily selected as AGNs by their optical emission. These galaxies, so-called optically…
We study a catalogue of over 130 emission-line galaxies with matched near infra-red (NIR) and optical spectra, where we examine the relationship between the respective nuclear activity classifications, diagnosed by the flux ratios of…