Related papers: Photometric Redshift Analysis using Supervised Lea…

We present a machine-learning photometric redshift analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes…

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…

For more that seventy years, the measurements of fluxes of galaxies at different wavelengths and derived colours have been used to estimate their corresponding cosmological distances. From the fields of galaxy and AGN evolution to precision…

We present a bright galaxy sample with accurate and precise photometric redshifts (photo-zs), selected using $ugriZYJHK_\mathrm{s}$ photometry from the Kilo-Degree Survey (KiDS) Data Release 4 (DR4). The highly pure and complete dataset is…

Galaxy photometric redshift (photo-$z$) is crucial in cosmological studies, such as weak gravitational lensing and galaxy angular clustering measurements. In this work, we try to extract photo-$z$ information and construct its probability…

In Lima et al. 2008 we presented a new method for estimating the redshift distribution, N(z), of a photometric galaxy sample, using photometric observables and weighted sampling from a spectroscopic subsample of the data. In this paper, we…

We present improved methods for using stars found in astronomical exposures to calibrate both star and galaxy colors as well as to adjust the instrument flat field. By developing a spectroscopic model for the SDSS stellar locus in…

We report new improved photometric redshifts of 1048 galaxies in the Hubble Deep Field (HDF). A standard chi^2 minimizing method is applied to seven-color UBVIJHK photometry by Fernandez-Soto, Lanzetta, & Yahil (1999). We use 187 template…

We present the development of a photometrically selected massive galaxy catalog, targeting Luminous Red Galaxies (LRGs) and massive blue galaxies at redshifts $z\geq 0.55$. Massive galaxy candidates are selected using infrared/optical…

This paper reports the results obtained on the photometric redshifts measurement and accuracy, and cluster tomography in the ESO Distant Cluster Survey (EDisCS) fields. Photometric redshifts were computed using two independent codes (Hyperz…

We use the deepest and most complete redshift catalog currently available (the Hubble Deep Field (HDF) North supplemented by new HDF South redshift data) to minimize residuals between photometric and spectroscopic redshift estimates. The…

Key cosmological applications require the three-dimensional galaxy distribution on the entire celestial sphere. These include measuring the gravitational pull on the Local Group, estimating the large-scale bulk flow and testing the…

Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of its high efficiency. Although various methods have been developed, template fitting is still adopted as one of the most…

We present broad band photometry and photometric redshifts for 187611 sources located in ~0.5deg^2 in the Lockman Hole area. The catalog includes 389 X-ray detected sources identified with the very deep XMM-Newton observations available for…

We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural…

We describe the construction of MegaZ-LRG, a photometric redshift catalogue of over one million luminous red galaxies (LRGs) in the redshift range 0.4 < z < 0.7 with limiting magnitude i < 20. The catalogue is selected from the imaging data…

We measure Redshift-Space Distortions (RSD) in the two-point correlation function of a sample of $63,163$ spectroscopically identified galaxies with $z < 0.2$, an epoch where there are currently only limited measurements, from the Sloan…

In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter…

We present a method, PhotoWeb, for estimating photometric redshifts of individual galaxies, and their equivalent distance, with megaparsec and even sub-megaparsec accuracy using the Cosmic Web as a constraint over photo-z estimates.…

We present the first results of our application of photometric redshifts to the study of galaxy populations in high-redshift clusters. For this survey, we are examining a sample of galaxy clusters at z > 0.6 which have already been…