Variability-selected Active Galactic Nuclei in the VST-SUDARE/VOICE Survey of the COSMOS Field
arXiv:1412.1488 · doi:10.1051/0004-6361/201424906
Abstract
Optical variability has proven to be an effective way of detecting AGNs in imaging surveys, lasting from weeks to years. In the present work we test its use as a tool to identify AGNs in the VST multi-epoch survey of the COSMOS field, originally tailored to detect supernova events. We make use of the multi-wavelength data provided by other COSMOS surveys to discuss the reliability of the method and the nature of our AGN candidates. Our selection returns a sample of 83 AGN candidates; based on a number of diagnostics, we conclude that 67 of them are confirmed AGNs (81% purity), 12 are classified as supernovae, while the nature of the remaining 4 is unknown. For the subsample of AGNs with some spectroscopic classification, we find that Type 1 are prevalent (89%) compared to Type 2 AGNs (11%). Overall, our approach is able to retrieve on average 15% of all AGNs in the field identified by means of spectroscopic or X-ray classification, with a strong dependence on the source apparent magnitude. In particular, the completeness for Type 1 AGNs is 25%, while it drops to 6% for Type 2 AGNs. The rest of the X-ray selected AGN population presents on average a larger r.m.s. variability than the bulk of non variable sources, indicating that variability detection for at least some of these objects is prevented only by the photometric accuracy of the data. We show how a longer observing baseline would return a larger sample of AGN candidates. Our results allow us to assess the usefulness of this AGN selection technique in view of future wide-field surveys.
17 pages, 8 figures. Accepted for publication in A&A - Edited language, corrected typos
References in corpus (9)
- The Cosmic Evolution Survey (COSMOS) -- Overview
- COSMOS Photometric Redshifts with 30-bands for 2-deg2
- The Chandra COSMOS Survey, I: Overview and Point Source Catalog
- Photometric redshift and classification for the XMM-COSMOS sources
- Variability of Active Galactic Nuclei from the Optical to X-ray Regions
- Variability-selected active galactic nuclei from supernova search in the Chandra deep field south
- Optical Variability of Infrared Power Law-Selected Galaxies & X-ray Sources in the GOODS-South Field
- Spectroscopic follow-up of variability-selected active galactic nuclei in the Chandra Deep Field South
- A multi-wavelength survey of AGN in the XMM-LSS field: I. Quasar selection via the KX technique
Cited by in corpus (20)
- Active Galactic Nuclei: what's in a name?
- Dwarf AGNs from Optical Variability for the Origins of Seeds (DAVOS): Insights from the Dark Energy Survey Deep Fields
- Searching for galaxy clusters in the Kilo-Degree Survey
- A structure function analysis of VST-COSMOS AGN
- Optically variable active galactic nuclei in the 3 yr VST survey of the COSMOS field
- SUDARE-VOICE variability-selection of Active Galaxies in the Chandra Deep Field South and the SERVS/SWIRE region
- Robust Identification of Active Galactic Nuclei through HST Optical Variability in GOODS-S: Comparison with the X-ray and mid-IR Selected Samples
- A random forest-based selection of optically variable AGN in the VST-COSMOS field
- Extending the variability selection of active galactic nuclei in the W-CDF-S and SERVS/SWIRE region
- Ensemble power spectral density of SDSS quasars in UV/optical bands
- Continuum optical-UV and X-ray variability of AGN: current results and future challenges
- Selection of optically variable active galactic nuclei via a random forest algorithm
- The Hubble Catalog of Variables (HCV)
- Variability and transient search in the SUDARE-VOICE field: a new method to extract the light curves
- Identification of problematic epochs in astronomical time series through transfer learning
- Unlocking AGN Variability with Custom ZTF Photometry for High-Fidelity Light Curves and Robust Selection
- Navigating AGN variability with self-organizing maps
- Galaxy Optical Variability of Virgo Cluster: New Tracer for Environmental Influences on Galaxies
- Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks
- VarIabiLity seLection of AstrophysIcal sources iN PTF (VILLAIN) I. Structure function fits to 71 million objects