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Machine learning algorithms have been used to determine probabilistic classifications of unassociated sources. Often classification into two large classes, such as Galactic and extra-galactic, is considered. However, there are many more…

High Energy Astrophysical Phenomena · Physics 2023-03-29 Dmitry Malyshev , Aakash Bhat

The WISE satellite has detected hundreds of millions sources over the entire sky. Classifying them reliably is however a challenging task due to degeneracies in WISE multicolour space and low levels of detection in its two…

Astrophysics of Galaxies · Physics 2016-07-13 Agnieszka Kurcz , Maciej Bilicki , Aleksandra Solarz , Magdalena Krupa , Agnieszka Pollo , Katarzyna Małek

We propose near-infrared colour selection criteria to extract Active Galactic Nuclei (AGNs) using the near-infrared Colour-Colour Diagram (CCD) and predict near-infrared colour evolution with respect to redshift. First, we cross-identify…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-14 Shinjirou Kouzuma , Hitoshi Yamaoka

Using Spitzer-IRS spectroscopy, we investigate the ubiquity of Active Galactic Nuclei (AGN) in a complete (~94%), volume-limited sample of the most bolometrically-luminous galaxies (L_IR > (0.3-20) x 10^10 L_sun) to D < 15 Mpc. Our analyses…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 Andy Goulding , Dave Alexander

Mid-infrared photometry provides a robust technique for identifying active galaxies. While the ultraviolet to mid-infrared continuum of normal galaxies is dominated by the composite stellar black body curve and peaks at approximately 1.6…

With the aim of studying the influence of environment on the nuclear activity of galaxies, we have selected a well defined sample of 65 Compact Groups of galaxies with concordant redshift in the Hickson Catalog. In this proceeding, we…

Astrophysics · Physics 2015-06-24 M. A. Martinez , A. del Olmo , J. Perea , R. Coziol

We present two catalogues of active galactic nucleus (AGN) candidates selected from the latest data of two all-sky surveys -- Data Release 2 (DR2) of the \emph{Gaia} mission and the unWISE catalogue of the \emph{Wide-field Infrared Survey…

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…

Identifying AGNs in dwarf galaxies is critical for understanding black hole formation but remains challenging due to their low luminosities, low metallicities, and star formation-driven emission that can obscure AGN signatures. Machine…

We describe a methodology to classify periodic variable stars identified using photometric time-series measurements constructed from the Wide-field Infrared Survey Explorer (WISE) full-mission single-exposure Source Databases. This will…

Instrumentation and Methods for Astrophysics · Physics 2015-06-18 Frank J. Masci , Douglas I. Hoffman , Carl J. Grillmair , Roc M. Cutri

We present a set of low resolution empirical SED templates for AGNs and galaxies in the wavelength range from 0.03 to 30 microns based on the multi-wavelength photometric observations of the NOAO Deep-Wide Field Survey Bootes field and the…

Cosmology and Nongalactic Astrophysics · Physics 2011-02-11 R. J. Assef , C. S. Kochanek , M. Brodwin , R. Cool , W. Forman , A. H. Gonzalez , R. C. Hickox , C. Jones , E. Le Floc'h , J. Moustakas , S. S. Murray , D. Stern

We present a variability, color and morphology based classifier, designed to identify transients, persistently variable, and non-variable sources, from the Zwicky Transient Facility (ZTF) Data Release 11 (DR11) light curves of extended and…

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…

Astrophysics of Galaxies · Physics 2026-02-18 Berta Margalef-Bentabol , Lingyu Wang , Antonio La Marca , Vicente Rodriguez-Gomez

We describe a new method of combining optical and infrared photometry to select Luminous Red Galaxies (LRGs) at redshifts $z > 0.6$. We explore this technique using a combination of optical photometry from CFHTLS and HST, infrared…

Astrophysics of Galaxies · Physics 2015-04-27 Abhishek Prakash , Timothy C. Licquia , Jeffrey A. Newman , Sandhya M. Rao

Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in…

Astrophysics of Galaxies · Physics 2017-12-12 A. Solarz , M. Bilicki , A. Pollo

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…

Astrophysics · Physics 2014-11-18 P. B. Westoby , C. G. Mundell , I. K. Baldry

We report on a complete sample of 7 luminous early-type galaxies in the Hubble Ultra Deep Field (UDF) with spectroscopic redshifts between 1.39 and 2.47 and to K<23 AB. Using the BzK selection criterion we have pre-selected a set of objects…

Galaxy morphologies provide valuable insights into their formation processes, tracing the spatial distribution of ongoing star formation and encoding signatures of dynamical interactions. While such information has been extensively…

We present a census of local active galactic nuclei (AGN) at a redshift of $z\leq0.025$ selected using the high-ionization [Ne v] $\lambda14.32\,\mu$m emission line from the Infrared Database of Extragalactic Observables from Spitzer…

Astrophysics of Galaxies · Physics 2026-03-16 S. Yassir , A. Annuar

We develop a straightforward and quantitative two-step method for spectroscopically classifying galaxies from the low signal-to-noise (S/N) optical spectra typical of galaxy redshift surveys. First, using \chi^2-fitting of characteristic…

Astrophysics · Physics 2009-10-28 Dennis Zaritsky , Ann I. Zabludoff , Jeffrey A. Willick