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We present a highly complete and reliable mid-infrared (MIR) colour selection of luminous AGN candidates using the 3.4, 4.6, and 12 um bands of the WISE survey. The MIR colour wedge was defined using the wide-angle Bright Ultra-Hard…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-11 S. Mateos , A. Alonso-Herrero , F. J. Carrera , A. Blain , M. G. Watson , X. Barcons , V. Braito , P. Severgnini , J. L. Donley , D. Stern

Mateos et al. (2012) presented a highly reliable and efficient mid-infrared (MIR) colour-based selection technique for luminous active galactic nuclei (AGN) using the Wide-field Infrared Survey Explorer (WISE) survey. Here we evaluate the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-16 S. Mateos , A. Alonso-Herrero , F. J. Carrera , A. Blain , P. Severgnini , A. Caccianiga , A. Ruiz

This paper analyzes a sample of 489 Spitzer/IRAC sources in the Extended Groth Strip whose spectral energy distributions fit a red power law from 3.6 to 8.0 \micron. The median for sources with known redshift is <z>=1.6. Though all or…

We investigate the nature of a sample of 92 Spitzer/MIPS 24 micron selected galaxies in the CDFS, showing power law-like emission in the Spitzer/IRAC 3.6-8 micron bands. The main goal is to determine whether the galaxies not detected in…

The X-ray color (hardness ratio) of optically undetected X-ray sources can be used to distinguish obscured active galactic nuclei (AGNs) at low and intermediate redshift from viable high-redshift (i.e., z>5) AGN candidates. This will help…

Astrophysics · Physics 2009-11-10 J. X. Wang , S. Malhotra , J. E. Rhoads , C. A. Norman

We study the properties of a sample of 211 heavily-obscured Active Galactic Nucleus (AGN) candidates in the Extended Chandra Deep Field-South selecting objects with f_24/f_R>1000 and R-K>4.5. Of these, 18 were detected in X-rays and found…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 E. Treister , C. Cardamone , K. Schawinski , C. M. Urry , E. Gawiser , S. Virani , P. Lira , J. Kartaltepe , M Damen , E. N. Taylor , E. Le Floc'h , Stephen Justham , A. Koekemoer

We use machine learning techniques to investigate their performance in classifying active galactic nuclei (AGNs), including X-ray selected AGNs (XAGNs), infrared selected AGNs (IRAGNs), and radio selected AGNs (RAGNs). Using known physical…

Astrophysics of Galaxies · Physics 2021-10-26 Yu-Yen Chang , Bau-Ching Hsieh , Wei-Hao Wang , Yen-Ting Lin , Chen-Fatt Lim , Yoshiki Toba , Yuxing Zhong , Siou-Yu Chang

We use observations from the 9 square degree multiwavelength survey in Bootes to identify hundreds of obscured active galactic nuclei (AGN) with high redshifts (z > 0.7), luminosities (L_bol > 10^45 ergs/s), and moderate obscuring columns…

Current X-ray surveys have proved to be essential tools in order to identify and study AGNs across cosmic time. However, there is evidence that the most heavily obscured AGNs are largely missing even in the deepest surveys. The search for…

Cosmology and Nongalactic Astrophysics · Physics 2013-06-04 A. Del Moro , D. M. Alexander , J. R. Mullaney , E. Daddi , F. E. Bauer , A. Pope

We use the INTEGRAL all-sky hard X-ray survey to perform a statistical study of a representative sample of nearby AGN. Our entire all-sky sample consists of 127 AGN, of which 91 are confidently detected (>5 sigma) on the time-averaged map…

Astrophysics · Physics 2016-08-30 S. Sazonov , M. Revnivtsev , R. Krivonos , E. Churazov , R. Sunyaev

In order to answer some of the major open questions in the fields of supermassive black hole (SMBH) and galaxy evolution, a complete census of SMBH growth, i.e., active galactic nuclei (AGN), is required. Thanks to deep all-sky surveys,…

We present X-ray data for a complete sample of 44 luminous infrared galaxies (LIRGs), obtained with the Chandra X-ray Observatory. These are the X-ray observations of the high luminosity portion of the Great Observatory All-sky LIRG Survey…

Hard X-ray selection is the most efficient way to discriminate between accretion-powered sources, such as AGN, from sources dominated by starlight. Hard X-rays are also less affected than other bands by obscuration. We have then carried out…

Astrophysics · Physics 2009-10-31 F. Fiore , F. La Franca , P. Giommi , M. Elvis , G. Matt , A. Comastri , S. Molendi , I. Gioia

We identify a population of 640 obscured and 839 unobscured AGNs at redshifts 0.7<z<~3 using multiwavelength observations of the 9 deg^2 NOAO Deep Wide-Field Survey (NDWFS) region in Bootes. We select AGNs on the basis of Spitzer IRAC…

Context. Active galactic nuclei (AGN) of galaxies play an important role in the life and evolution of galaxies due to the impact they exert on certain properties and the evolutionary path of galaxies. It is well known that infrared (IR)…

Astrophysics of Galaxies · Physics 2022-08-24 Carlos G. Bornancini , Gabriel A. Oio , M. Victoria Alonso , Diego García Lambas

The Wide-field Infrared Survey Explorer (WISE) is an extremely capable and efficient black hole finder. We present a simple mid-infrared color criterion, W1-W2 \geq 0.8 (i.e., [3.4]-[4.6] \geq 0.8, Vega), which identifies 61.9 \pm 5.4 AGN…

We summarize multiwavelength properties of a sample of galaxies in the CDF-N and CDF-S whose Spectral Energy Distributions (SEDs) exhibit the characteristic power-law behavior expected for AGN in the Spitzer/IRAC 3.6-8micron bands. AGN…

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…

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…

(Abridged) High-redshift ultra luminous infrared galaxies contribute the bulk of the cosmic IR background and are the best candidates for very massive galaxies in formation at z>1.5. We present Keck/LRIS optical spectroscopy of 35 z>1.4…