Related papers: Learning algorithms at the service of WISE survey
Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative…
In this paper we present a deep and homogeneous i-band selected multi-waveband catalogue in the COSMOS field covering an area of about 0.7 square-degree. Our catalogue with a formal 50 percent completeness limit for point sources of i~26.7…
The 2 Micron All-Sky Survey (2MASS) will observe over one-million galaxies and extended Galactic sources covering the entire sky at wavelengths between 1 and 2 microns. The survey catalog will have both high completeness and reliability…
Quasars experiencing strong lensing offer unique viewpoints on subjects related to the cosmic expansion rate, the dark matter profile within the foreground deflectors, and the quasar host galaxies. Unfortunately, identifying them in…
Machine learning has emerged as a powerful tool in the field of gamma-ray astrophysics. The algorithms can distinguish between different source types, such as blazars and pulsars, and help uncover new insights into the high-energy universe.…
We present a catalog of radio-loud candidate gamma-ray emitting blazars with WISE mid-infrared colors similar to the colors of confirmed gamma-ray blazars. The catalog is assembled from WISE sources detected in all four WISE filters, with…
Context. The identification of bright QSOs is of great importance to probe the intergalactic medium and address open questions in cosmology. Several approaches have been adopted to find such sources in currently available photometric…
At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Here we present the first application of deep…
We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks, a probabilistic graphical model, that allows us to perform inference to pre- dict missing values given observed data and…
The Wide-field Infrared Survey Explorer (WISE) has completed its all-sky survey at 3.4-22 micron. We merge the WISE data with optical SDSS data and provide a phenomenological characterization of mid-IR, extragalactic sources. WISE is most…
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…
[Abridged] To effectively investigate galaxy formation and evolution, it is of paramount importance to exploit homogeneous data for large samples of galaxies in different environments. The WINGS (WIde-field Nearby Galaxy-cluster Survey)…
We present a new algorithm to estimate quasar photometric redshifts (photo-$z$s), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the…
The Wide-Area VISTA Extragalactic Survey (WAVES) on the 4-metre Multi-Object Spectroscopic Telescope (4MOST) includes two flux-limited subsurveys with very high (95\%) completeness requirements: Wide over $\sim\!1200$ deg$^2$ and Deep over…
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…
Context. Large, high-dimensional astronomical surveys require efficient data analysis. Automatic fitting of lightcurve variability and machine learning may assist in identification of sources including candidate quasars. Aims. We aim to…
The upcoming galaxy large-scale surveys, such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), will generate photometry for billions of galaxies. The interpretation of large-scale weak lensing maps, as well as the…
In this paper we present photometric redshifts for 2.7 million galaxies in the XMM-LSS and COSMOS fields, both with rich optical and near-infrared data from VISTA and HyperSuprimeCam. Both template fitting (using galaxy and Active Galactic…
Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…
(abridged) The overwhelming majority of diagnostic tools for galactic activity are focused on active galaxies. Passive or dormant galaxies are often excluded from these diagnostics which usually employ emission line features. In this work,…