Related papers: How to Find Variable Active Galactic Nuclei with M…
We show that using mid-IR color selection to find active galactic nuclei (AGN) is as effective in dense stellar fields such as the Magellanic Clouds as it is in extragalactic fields with low stellar densities using comparisons between the…
We use a combination of the XMM-Newton serendipitous X-ray survey with the optical SDSS, and the infrared WISE all-sky survey in order to check the efficiency of the low X-ray to infrared luminosity selection method in finding heavily…
Active galactic nuclei (AGN) are typically identified through radio, mid-infrared, or X-ray emission or through the presence of broad and/or narrow emission lines. AGN can also leave an imprint on a galaxy's spectral energy distribution…
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…
Context. Changing-look active galactic nuclei (CL-AGNs) challenge the unified model of AGNs and offer key insights into the physics of the accretion processes of super-massive black holes. While systematic spectroscopic comparisons have…
We are conducting an archival Swift program to measure multiwavelength variability in active galactic nuclei (AGN). This variability information will provide constraints on the geometry, physical conditions and processes of the structures…
We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of…
Identifying active galactic nuclei (AGN) is extremely important for understanding galaxy evolution and its connection with the assembly of supermassive black holes (SMBH). With the advent of deep and high angular resolution imaging surveys…
Active Galactic Nuclei (AGN) are relevant sources of radiation that might have helped reionising the Universe during its early epochs. The super-massive black holes (SMBHs) they host helped accreting material and emitting large amounts of…
This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this…
The incidence and properties of Active Galactic Nuclei (AGN) in the field, groups, and clusters can provide new information about how these objects are triggered and fueled, similar to how these environments have been employed to study…
Reliable, versatile galaxy activity diagnostics are essential for understanding galaxy evolution. Traditional methods frequently necessitate extensive preprocessing, such as starlight subtraction and emission line deblending (e.g.,…
Active Galactic Nuclei (AGN) are believed to be powered by accretion of matter onto a supermassive black hole. A fundamental ingredient in shaping our understanding of AGN is their variability across the entire electromagnetic spectrum.…
The maximum number density of Active Galactic Nuclei (AGNs), as deduced from X-ray studies, occurs at z<~1, with lower luminosity objects peaking at smaller redshifts. Optical studies lead to a different evolutionary behaviour, with a…
We investigate machine learning (ML) techniques for predicting the number of galaxies (N_gal) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for…
Molecular property prediction (e.g., energy) is an essential problem in chemistry and biology. Unfortunately, many supervised learning methods usually suffer from the problem of scarce labeled molecules in the chemical space, where such…
We study the black hole mass $-$ host galaxy stellar mass relation, $M_{\rm{BH}}-M_{\ast}$, of a sample of $z<4$ optically-variable AGNs in the COSMOS field. The parent sample of 491 COSMOS AGNs were identified by optical variability from…
We study a sample of 23 narrow-emission line galaxies (NELGs) which were selected by their strong variability as QSO candidates in the framework of a variability-and-proper motion QSO survey on digitised Schmidt plates. In previous work, we…
The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…
We present results from a study to detect variable galaxies in the Hubble Deep Field North. The goal of this project is to investigate the number density of AGN at z=1 through the detection of variable galaxy nuclei. The advantage of HST is…