Related papers: Photometric redshifts and quasar probabilities fro…
The scientific value of the next generation of large continuum surveys would be greatly increased if the redshifts of the newly detected sources could be rapidly and reliably estimated. Given the observational expense of obtaining…
MLPQNA stands for Multi Layer Perceptron with Quasi Newton Algorithm and it is a machine learning method which can be used to cope with regression and classification problems on complex and massive data sets. In this paper we give the…
Photometric redshift estimation is an indispensable tool of precision cosmology. One problem that plagues the use of this tool in the era of large-scale sky surveys is that the bright galaxies that are selected for spectroscopic observation…
Forthcoming astronomical surveys are expected to detect new sources in such large numbers that measuring their spectroscopic redshift measurements will be not be practical. Thus, there is much interest in using machine learning to yield the…
We apply instance-based machine learning in the form of a k-nearest neighbor algorithm to the task of estimating photometric redshifts for 55,746 objects spectroscopically classified as quasars in the Fifth Data Release of the Sloan Digital…
Identifications of quasars at intermediate redshifts (2.2<z<3.5) are inefficient in most previous quasar surveys as their optical colors are similar to those of stars. The near-IR K-band excess technique has been suggested to overcome this…
We use a multi-color classification method introduced by Wolf, Meisenheimer & Roeser (2000) to reliably identify stars, galaxies and quasars in the up to 16-dimensional color space provided by the filter set of the Calar Alto Deep Imaging…
We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift…
We aim to select quasar candidates based on the two large survey databases, Pan-STARRS and AllWISE. Exploring the distribution of quasars and stars in the color spaces, we find that the combination of infrared and optical photometry is more…
Red quasars constitute an important but elusive phase in the evolution of supermassive black holes, where dust obscuration can significantly alter their observed properties. They have broad emission lines, like other quasars, but their…
We construct a parametric SED model which is able to reproduce the average observed SDSS-UKIDSS-WISE quasar colours to within one tenth of a magnitude across a wide range of redshift $(0<z<5)$ and luminosity $(-22>M_i>-29)$. This model is…
Photometric redshifts are a key tool to extract as much information as possible from planned cosmic shear experiments. In this work we aim to test the performances that can be achieved with observations in the near-infrared from space and…
We release photometric redshifts, reaching $\sim$0.7, for $\sim$14M galaxies at $r\leq 20$ in the 11,500 deg$^2$ of the SDSS north and south galactic caps. These estimates were inferred from a convolution neural network (CNN) trained on…
A simple estimate of the photometric redshift would prove invaluable to forthcoming continuum surveys on the next generation of large radio telescopes, as well as mitigating the existing bias towards the most optically bright sources. While…
Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their…
A crucial test of any cosmological model is the distribution of distant objects such as quasars. Because of well defined selection criteria quasars found by a ultraviolet excess (UVX) survey are ideal candidates for testing the model out to…
We present a catalog of 1.4 million photometrically-selected quasar candidates in the southern hemisphere over the $\sim 5000\,{\rm deg^2}$ Dark Energy Survey (DES) wide survey area. We combine optical photometry from the DES second data…
We have obtained complete redshift information for a sample of 442 radio-loud quasars with flux densities S(11cm) >= 0.25Jy. These come from a completely-identified sample of 878 flat-spectrum radio sources, so there is no optical magnitude…