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Related papers: The Feasibility and Flexibility of Selecting Quasa…

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With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series…

Context: Quasar variability has proven to be a powerful tool to constrain the properties of their inner engine and the accretion process onto supermassive black holes. Correlations between UV/optical variability and physical properties have…

Astrophysics of Galaxies · Physics 2024-06-26 Vincenzo Petrecca , Iossif Papadakis , Maurizio Paolillo , Demetra De Cicco , Franz Bauer

We compare the performance of two automated classification algorithms: k-dimensional tree (kd-tree) and support vector machines (SVMs), to separate quasars from stars in the databases of the Sloan Digital Sky Survey (SDSS) and the Two…

Astrophysics · Physics 2009-09-29 Gao Dan , Zhang Yanxia , Zhao Yongheng

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…

Astrophysics · Physics 2008-11-26 Nicholas M. Ball , Robert J. Brunner , Adam D. Myers , David Tcheng

We explore the multidimensional, multiwavelength selection of quasars from mid-IR (MIR) plus optical data, specifically from Spitzer-IRAC and the Sloan Digital Sky Survey (SDSS). We apply modern statistical techniques to combined Spitzer…

Hundreds of Type 2 quasars have been identified in Sloan Digital Sky Survey (SDSS) data, and there is substantial evidence that they are generally galaxies with highly obscured central engines, in accord with unified models for active…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 A. J. Barth , A. Voevodkin , D. J. Carson , P. Woźniak

We present a new QSO selection algorithm using a Support Vector Machine (SVM), a supervised classification method, on a set of extracted times series features including period, amplitude, color, and autocorrelation value. We train a model…

Instrumentation and Methods for Astrophysics · Physics 2015-05-27 Dae-Won Kim , Pavlos Protopapas , Yong-Ik Byun , Charles Alcock , Roni Khardon , Markos Trichas

Sloan Digital Sky Survey (SDSS) repeat spectroscopic observations have resulted in multiple-epoch spectroscopy for roughly 2500 quasars observed more than 50 days apart. From this sample, we identify 315 quasars that have varied…

A refined sample of 64 variable objects with stellar image structure has been identified in SA 57 to $B \sim 22.5$, over a time baseline of 15 years, sampled at 11 distinct epochs. The photometric data typically have a root-mean-square…

Astrophysics · Physics 2009-10-22 D. Trevese , R. G. Kron , S. R. Majewski , M. A. Bershady , D. C. Koo

We present a catalog of quasars and corresponding redshifts in the Kilo-Degree Survey (KiDS) Data Release 4. We trained machine learning (ML) models, using optical ugri and near-infrared ZYJHK_s bands, on objects known from Sloan Digital…

Cosmology and Nongalactic Astrophysics · Physics 2021-05-19 S. J. Nakoneczny , M. Bilicki , A. Pollo , M. Asgari , A. Dvornik , T. Erben , B. Giblin , C. Heymans , H. Hildebrandt , A. Kannawadi , K. Kuijken , N. R. Napolitano , E. Valentijn

We present spectroscopy of binary quasar candidates selected from Data Release 4 of the Sloan Digital Sky Survey (SDSS DR4) using Kernel Density Estimation (KDE). We present 27 new sets of observations, 10 of which are binary quasars,…

Context. Lightcurve variability is well-suited for characterising objects in surveys with high cadence and long baseline. This is especially relevant in view of the large datasets to be produced by the Vera C. Rubin Observatory Legacy…

Astrophysics of Galaxies · Physics 2023-08-23 S. H. Bruun , A. Agnello , J. Hjorth

This paper presents a comprehensive study of quasar photometric classification and redshift estimation using machine learning techniques. We cross-matched photometric data from the Dark Energy Survey Data Release 2 (DES DR2) with…

Instrumentation and Methods for Astrophysics · Physics 2026-05-19 Pablo Motta , Filipe B. Abdalla , Elcio Abdalla , Gabriel S. Costa , Camila Cardoso

We have compiled a catalog of 903 candidates for type 1 quasars at redshifts 3<z<5.5 selected among the X-ray sources of the serendipitous XMM-Newton survey presented in the 3XMM-DR4 catalog (the median X-ray flux is 5x10^{-15} erg/s/cm^2…

Astrophysics of Galaxies · Physics 2017-02-01 G. A. Khorunzhev , R. A. Burenin , A. V. Meshcheryakov , S. Yu. Sazonov

Context: Given the current big data era in Astronomy, machine learning based methods have being applied over the last years to identify or classify objects like quasars, galaxies and stars from full sky photometric surveys. Aims: Here we…

We model the time variability of ~9,000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk. Using 2.7 million photometric measurements collected over 10 years, we confirm the results of Kelly et al. (2009) and…

Cosmology and Nongalactic Astrophysics · Physics 2010-09-07 C. L. MacLeod , Ž. Ivezić , C. S. Kochanek , S. Kozłowski , B. C. Kelly , E. Bullock , A. Kimball , B. Sesar , D. Westman , K. Brooks , R. Gibson , A. C. Becker , W. H. de Vries

Several recent works have focused on the search for bright, high-z quasars (QSOs) in the South. Among them, the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) survey has now delivered hundreds of new…

Making use of strong correlations between closely separated multiple or double sources and photometric and astrometric metadata in Gaia EDR3, we generate a catalog of candidate double and multiply imaged lensed quasars and AGNs, comprising…

Astrophysics of Galaxies · Physics 2022-12-21 Valeri V. Makarov , Nathan J. Secrest