Related papers: Classifying Stars, Galaxies and AGN in CLAUDS+HSC-…
A large fraction of active galactic nuclei (AGN) are "invisible" in extant optical surveys due to either distance or dust-obscuration. The existence of this large population of dust-obscured, infrared-bright AGN is predicted by models of…
In order to find a fast and reliable method for selecting metal poor galaxies (MPGs), especially in large surveys and huge database, an Artificial Neural Network (ANN) method is applied to a sample of star-forming galaxies from the Sloan…
Variability is a main property of active galactic nuclei (AGN) and it was adopted as a selection criterion using multi epoch surveys conducted for the detection of supernovae (SNe). We have used two SN datasets. First we selected the AXAF…
Forthcoming surveys such as the Large Synoptic Survey Telescope (LSST) and Euclid necessitate automatic and efficient identification methods of strong lensing systems. We present a strong lensing identification approach that utilizes a…
Automated spectral classification is an active research area in astronomy at the age of data explosion. While new generation of sky survey telescopes (e.g. LAMOST and SDSS) produce huge amount of spectra, automated spectral classification…
With the aim of investigating galaxies with two strong simultaneous starbursts, we have extracted a sample of galaxies with double-peaked emission lines in their global spectra from the SDSS spectral database. We then fitted the emission…
An unresolved question in studies of active galactic nuclei (AGN) is whether their different classes probe different evolutionary stages of black hole--host galaxy interaction. We present the projected two-point cross-correlation function…
We used random forest algorithms to classify all objects in a large portion of the sky, using optical light curves obtained, or built from images provided, by the Zwicky Transient Facility (ZTF). We compare different selection sets based on…
The automatic classification of X-ray detections is a necessary step in extracting astrophysical information from compiled catalogs of astrophysical sources. Classification is useful for the study of individual objects, statistics for…
Context. A major challenge in astrophysics is classifying galaxies by their activity. Current methods often require multiple diagnostics to capture the full range of galactic activity. Furthermore, overlapping excitation sources with…
We collect data at all frequencies for the new sources classified as unknown active galactic nuclei (AGNs) in the latest Burst Alert Telescope (BAT) all-sky hard X-ray catalog. Focusing on the 36 sources with measured redshift, we compute…
(abridged) The overwhelming majority of diagnostic tools for galactic activity are focused on active galaxies. Passive or dormant galaxies are often excluded from these diagnostics which usually employ emission line features. In this work,…
(abridged) Infrared selection is a potentially powerful way to identify heavily obscured AGN missed in even the deepest X-ray surveys. Using a 24 micron-selected sample in GOODS-S, we test the reliability and completeness of three infrared…
Upcoming astronomical surveys such as the Large Synoptic Survey Telescope (LSST) will rely on photometric classification to identify the majority of the transients and variables that they discover. We present a set of techniques for…
The rapid increase in data on galaxy images at low and high redshift calls for re-examination of the classification schemes and for new automatic objective methods. Here we present a classification method by Artificial Neural Networks. We…
Spitzer/IRAC color selection is a promising technique to identify hot accreting nuclei, that is to say AGN, in galaxies. We demonstrate this using a small sample of SAURON galaxies, and explore this further. The goal of this study is to…
Quantitative morphological classification of galaxies is important for understanding the origin of type frequency and correlations with environment. But galaxy morphological classification is still mainly done visually by dedicated…
SHARDS is an ongoing ESO/GTC large program that is obtaining ultra-deep photometry of the GOODS-North field in 24 medium-band filters (reaching m=26.5 AB in all bands) in the 500-950 nm range with GTC/OSIRIS. It is designed to study the…
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 introduce a binary classification model, {\it the Double Filter Model}, utilizing various machine learning and deep learning methods to classify Young Stellar Objects (YSOs) and Asymptotic Giant Branch (AGB) stars. Since YSOs and AGB…