A random forest-based selection of optically variable AGN in the VST-COSMOS field

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dc.contributor.authorDe Cicco, D.
dc.contributor.authorBauer, F. E.
dc.contributor.authorPaolillo, M.
dc.contributor.authorCavuoti, S.
dc.contributor.authorSánchez-Sáez, P.
dc.contributor.authorBrandt, W. N.
dc.contributor.authorPignata, G.
dc.contributor.authorVaccari, M.
dc.contributor.authorRadovich, M.
dc.date.accessioned2022-06-07T15:13:13Z
dc.date.available2022-06-07T15:13:13Z
dc.date.issued2021-01-01
dc.descriptionIndexación Scopuses
dc.description.abstractContext. The survey of the COSMOS field by the VLT Survey Telescope is an appealing testing ground for variability studies of active galactic nuclei (AGN). With 54 r-band visits over 3.3 yr and a single-visit depth of 24.6 r-band mag, the dataset is also particularly interesting in the context of performance forecasting for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Aims. This work is the fifth in a series dedicated to the development of an automated, robust, and efficient methodology to identify optically variable AGN, aimed at deploying it on future LSST data. Methods. We test the performance of a random forest (RF) algorithm in selecting optically variable AGN candidates, investigating how the use of different AGN labeled sets (LSs) and features sets affects this performance. We define a heterogeneous AGN LS and choose a set of variability features and optical and near-infrared colors based on what can be extracted from LSST data. Results. We find that an AGN LS that includes only Type I sources allows for the selection of a highly pure (91%) sample of AGN candidates, obtaining a completeness with respect to spectroscopically confirmed AGN of 69% (vs. 59% in our previous work). The addition of colors to variability features mildly improves the performance of the RF classifier, while colors alone prove less effective than variability in selecting AGN as they return contaminated samples of candidates and fail to identify most host-dominated AGN. We observe that a bright (r ≲ 21 mag) AGN LS is able to retrieve candidate samples not affected by the magnitude cut, which is of great importance as faint AGN LSs for LSST-related studies will be hard to find and likely imbalanced. We estimate a sky density of 6.2 × 106 AGN for the LSST main survey down to our current magnitude limit.en
dc.identifier.citationAstronomy and Astrophysics Volume 6451 January 2021 Article number A103en
dc.identifier.doi10.1051/0004-6361/202039193
dc.identifier.issn0004-6361
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/22733
dc.language.isoenes
dc.publisherEDP Sciencesen
dc.subjectGalaxies: activeen
dc.subjectMethods: statisticalen
dc.subjectSurveysen
dc.titleA random forest-based selection of optically variable AGN in the VST-COSMOS fielden
dc.typeArtículoen
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