相关论文: A Simple Likelihood Method for Quasar Target Selec…

We present the third edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog consists of the 46,420 objects in the SDSS Third Data Release that have luminosities larger than M_i = -22 (in a cosmology with H_0 = 70…

The Dark Energy Spectroscopic Instrument (DESI) cosmology survey includes a Bright Galaxy Survey (BGS) which will yield spectra for over ten million bright galaxies (r<20.2 AB mag). The resulting sample will be valuable for both…

We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with…

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our…

Recent technological advances have led to a flood of new data on cosmology rich in information about the formation and evolution of the universe, e.g., the data collected in Sloan Digital Sky Survey (SDSS) for more than 200 million objects.…

We present a study of quasar selection using the DES supernova fields. We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color,…

The Bayesian gravitational shear estimation algorithm developed by Bernstein and Armstrong (2014) can potentially be used to overcome multiplicative noise bias and recover shear using very low signal-to-noise ratio (S/N) galaxy images. In…

We report the discovery of a unique gravitational lens system, SDSSJ2222+2745, producing five spectroscopically confirmed images of a z_s=2.82 quasar lensed by a foreground galaxy cluster at z_l=0.49. We also present photometric and…

We present two new source extraction methods, based on Bayesian model selection and using the Bayesian Information Criterion (BIC). The first is a source detection filter, able to simultaneously detect point sources and estimate the image…

High redshift quasars (HZQs) with redshifts of z >~ 6 are so rare that any photometrically-selected sample of sources with HZQ-like colours is likely to be dominated by Galactic stars and brown dwarfs scattered from the stellar locus. It is…

We have used the VLA FIRST survey and the APM catalog of the POSS-I plates as the basis for constructing a new radio-selected sample of optically bright quasars. This is the first radio-selected sample that is competitive in size with…

We measure quasar variability using the Panoramic Survey Telescope and Rapid Response System 1 Survey (Pan-STARRS1 or PS1) and the Sloan Digital Sky Survey (SDSS) and establish a method of selecting quasars via their variability in 10,000…

Here we explore the efficiency and fidelity of a purely astrometric selection of quasars as point sources with zero proper motions in the {\it Gaia} data release 2 (DR2). We have built a complete candidate sample including 104 Gaia-DR2…

We present a science forecast for the eBOSS survey, part of the SDSS-IV project, which is a spectroscopic survey using multiple tracers of large-scale structure, including luminous red galaxies (LRGs), emission line galaxies (ELGs) and…

We present the fifth edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog, which is based upon the SDSS Seventh Data Release. The catalog, which contains 105,783 spectroscopically confirmed quasars, represents the conclusion of the…

We search for the Baryon Acoustic Oscillations in the projected cross-correlation function binned into transverse comoving radius between the SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected from the DESI…

We explore the cosmological implications of anisotropic clustering measurements of the quasar sample from Data Release 14 of the Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey (eBOSS) in configuration space.…

In this work we train three decision-tree based ensemble machine learning algorithms (Random Forest Classifier, Adaptive Boosting and Gradient Boosting Decision Tree respectively) to study quasar selection in the variable source catalog in…

We present a catalog of quasars selected from broad-band photometric ugri data of the Kilo-Degree Survey Data Release 3 (KiDS DR3). The QSOs are identified by the random forest (RF) supervised machine learning model, trained on SDSS DR14…

We present the discovery of nine quasars at $z\sim6$ identified in the Sloan Digital Sky Survey (SDSS) imaging data. This completes our survey of $z\sim6$ quasars in the SDSS footprint. Our final sample consists of 52 quasars at…