Related papers: Classifying Stars, Galaxies and AGN in CLAUDS+HSC-…

Galaxy mergers play an important role in the growth of galaxies and their supermassive black holes. Simulations suggest that tidal interactions could enhance black hole accretion, which can be tested by the fraction of binary active…

Image generation using diffusion models have demonstrated outstanding learning capabilities, effectively capturing the full distribution of the training dataset. They are known to generate wide variations in sampled images, albeit with a…

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…

We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community: star/galaxy separation, and photometric redshift…

Classification of sources is one of the most important tasks in astronomy. Sources detected in one wavelength band, for example using gamma rays, may have several possible associations in other wavebands, or there may be no plausible…

Particle identification is one of the core tasks in the data analysis pipeline at the Large Hadron Collider (LHC). Statistically, this entails the identification of rare signal events buried in immense backgrounds that mimic the properties…

We report on optical searches in the error circles of 93 ROSAT survey sources located at low galactic latitudes (|b| < 20 deg). These sources were extracted from the ROSAT Galactic Plane Survey using various selection criteria on hardness…

In this work we have updated the list of AGN detected by INTEGRAL taking into account the new objects listed in the last published INTEGRAL/IBIS survey. We have collected 83 new AGN increasing the number of INTEGRAL detected active galaxies…

[Abridged] We exploit the clustering of massive galaxies to perform a high efficiency imaging search for gravitational lenses. Our dataset comprises 44 fields imaged by the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS),…

X-rays offer a reliable method to identify Active Galactic Nuclei (AGN). However, in the high-redshift Universe X-ray AGN are poorly sampled due to their relatively low space density and the small areas covered by X-ray surveys. In addition…

We present the results of an analysis of a well-selected sample of galaxies with active and inactive galactic nuclei from the Sloan Digital Sky Survey, in the range 0.01 < z < 0.16. The SDSS galaxy catalogue was split into two classes of…

JWST has enabled the discovery of a statistical sample of obscured (type II) active galactic nuclei (AGN) at cosmic noon. Studies comparing those type II AGN with type I AGN at that epoch have reinforced the long-standing idea of an…

The Legacy Survey of Space and Time, to be conducted with the Vera C. Rubin Observatory, is poised to revolutionize our understanding of the Solar System by providing an unprecedented wealth of data on various objects, including the elusive…

The aim of this work is to develop a comprehensive method for classifying sources in large sky surveys and we apply the techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS). Using the optical (u*, g', r', i') and NIR data…

We use multi-band spatially resolved photometry from the Cosmic Assembly Near-IR Deep Legacy Survey (CANDELS) in the 4 MSec Chandra Deep Field-South (CDF-S) to explore the nuclear and extended colors, color gradients and stellar populations…

The study of morphology in galaxies offers a convenient and quantitative method to measure the shapes and characteristics of galaxy light distribution that reflect the evolutionary history. For AGN-host dwarf galaxies, however, there is a…

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…

Classification of stars and galaxies is a well-known astronomical problem that has been treated using different approaches, most of them relying on morphological information. In this paper, we tackle this issue using the low-resolution…

In order to analyse the large numbers of Seyfert galaxy spectra available at present, we are testing new techniques to derive their physical parameters fastly and accurately. We present an experiment on such a new technique to segregate old…

Extensive astronomical surveys, like those conducted with the {\em Chandra} X-ray Observatory, detect hundreds of thousands of unidentified cosmic sources. Machine learning (ML) methods offer an efficient, probabilistic approach to classify…