Related papers: A versatile classification tool for galactic activ…

To build a large, optically bright, X-ray selected AGN sample we have correlated the ROSAT-FSC catalogue of X-ray sources with the USNO catalogue limited to objects brighter than O=16.5 and then with the APS database. Each of the 3,212…

In this work, we aimed at investigating the star formation rate of active galactic nuclei host galaxies in the early Universe. To this end, we constructed a sample of 149 luminous ($\rm L_{2-10keV} > 10^{44}\,erg\,s^{-1}$) X-ray AGNs at…

This paper contains a list of new AGN candidates identified from the examination of 3500 optical spectra contained in the database of the Southern Sky Redshift Survey Extension (SSRS2). The classification of galaxies was done using standard…

We have used FMOS on Subaru to obtain near-infrared spectroscopy of 123 far-infrared selected galaxies in COSMOS and obtain the key rest-frame optical emission lines. This is the largest sample of infrared galaxies with near-infrared…

There is an obvious need for automated classification of galaxies, as the number of observed galaxies increases very fast. We examine several approaches to this problem, utilising {\em Artificial Neural Networks} (ANNs). We quote results…

Active Galactic Nuclei (AGN) and star-forming galaxies are leading candidates for being the luminous sources that reionized our Universe. Next-generation 21cm surveys are promising to break degeneracies between a broad range of reionization…

We use 80922 galaxies in the Galaxy And Mass Assembly (GAMA) survey to measure the galaxy luminosity function (LF) in different environments over the redshift range 0.04<z<0.26. The depth and size of GAMA allows us to define samples split…

Identifying Active Galactic Nuclei (AGNs) through their X-ray emission is efficient, but necessarily biased against X-ray-faint objects. We aim to characterize this bias by comparing X-ray-selected AGNs to the ones identified through…

We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within $z<1$. We first use PSFGAN to decouple host galaxy light from the central point source, then we invoke the…

Both star formation (SF) and Active Galactic Nuclei (AGN) play an important role in galaxy evolution. Statistically quantifying their relative importance can be done using radio luminosity functions. Until now these relied on galaxy…

One of the major challenges in astronomy involves accurately classifying galaxies, particularly distinguishing between different galaxy types. While many complex algorithms have shown strong performance in classification tasks, their…

We have constructed a catalog of active galactic nuclei (AGNs) with $z < 0.13$, based on optical spectroscopy, from the parent sample of galaxies in the 6dF galaxy survey (Final Release of 6dFGS), a census of the Southern hemisphere. This…

Aims. Construction of a new quasar candidate catalog from the Red-Sequence Cluster Survey 2 (RCS-2), identified solely from photometric information using an automated algorithm suitable for large surveys. The algorithm performance is tested…

We present the Advanced Camera for Surveys Active Galactic Nuclei (ACS-AGN) Catalog, a catalog of 2585 active galactic nucleus (AGN) host galaxies that are at redshifts 0.2<z<2.5 and that were imaged with the Hubble Space Telescope's…

We present here the results about the determination of the Luminosity Function (LF) for elliptical galaxies in the core of fairly rich clusters as a function of redshift and try to compare with the known LF of close, better studied clusters…

We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few…

The faint radio-source population includes sources dominated both by star formation and active galactic nuclei (AGN), encoding the evolution of activity in the Universe. To investigate its nature, we probabilistically classified 4,471 radio…

We develop a new diagnostic method to classify galaxies into AGN hosts, star-forming galaxies, and absorption-dominated galaxies by combining the [O III]/Hbeta ratio with rest-frame U-B color. This can be used to robustly select AGNs in…

In this study, a novel machine learning algorithm, restricted Boltzmann machine (RBM), is introduced. The algorithm is applied for the spectral classification in astronomy. RBM is a bipartite generative graphical model with two separate…

Identifying merging galaxies is an important - but difficult - step in galaxy evolution studies. We present random forest classifications of galaxy mergers from simulated JWST images based on various standard morphological parameters. We…