The "Cosmic Evolution Survey" (COSMOS) enables the study of the spectral energy distributions (SEDs) of active galactic nuclei (AGNs) because of the deep coverage and rich sampling of frequencies from X-ray to radio. Here we present an SED catalog of 413 X-ray (XMM-Newton)-selected type 1 (emission line FWHM > 2000 km s −1) AGNs with Magellan, SDSS, or VLT spectrum. The SEDs are corrected for Galactic extinction, broad emission line contributions, constrained variability, and host galaxy contribution. We present the mean SED and the dispersion SEDs after the above corrections in the rest-frame 1.4 GHz to 40 keV, and show examples of the variety of SEDs encountered. In the near-infrared to optical (rest frame ∼8 μm-4000 Å), the photometry is complete for the whole sample and the mean SED is derived from detections only. Reddening and host galaxy contamination could account for a large fraction of the observed SED variety. The SEDs are all available online.
We present the first high-redshift gal axy cluster candidate sample from the HIROCS survey found in the COSMOS field. It results from a combination of public COSMOS with proprietary H-band data on a 0.66• part of the COSMOS field and comprises 12 candidates in the redshift range 1.23 ≤ z ≤ 1.55. We find an increasing fraction of blue cluster members with increasing redshift. Many of the blue and even some of the reddest member galaxies exhibit disturbed morphologies as well as signs of interaction.
Aims. We describe a survey for distant clusters of galaxies that identified clusters as local overdensities in the 3D galaxy distribution. Methods. Optical and near-IR imaging in B, R, i, z, and H are used to derive photometric redshifts for objects as faint as m* + 1 at a redshift of 1.5. We outline the astrometric and photometric data reduction. The 3D cluster search, based on the photometric redshifts, is described. Results. On the basis of the first fully reduced 1 square degree of data, we demonstrate that the objectives of HIROCS have been achieved. Four representative clusters from the list of candidates are presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.