Related papers: redMaPPer I: Algorithm and SDSS DR8 Catalog

Identifying galaxy clustering at high redshift (i.e. z > 1) is essential to our understanding of the current cosmological model. However, at increasing redshift, clusters evolve considerably in star-formation activity and so are less likely…

The potential of using cluster clustering for calibrating the mass-observable relation of galaxy clusters has been recognized theoretically for over a decade. Here, we demonstrate the feasibility of this technique to achieve high precision…

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…

The clustering of quasars on small scales yields fundamental constraints on models of quasar evolution and the buildup of supermassive black holes. This paper describes the first systematic survey to discover high redshift binary quasars.…

We present redshifts and optical richness properties of 21 galaxy clusters uniformly selected by their Sunyaev-Zel'dovich signature. These clusters, plus an additional, unconfirmed candidate, were detected in a 178 square-degree area…

(Abridged) Distant galaxy clusters provide important tests of the growth of large scale structure in addition to highlighting the process of galaxy evolution in a consistently defined environment at large look back time. We present a sample…

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 present a study of photometric redshift performance for galaxies and active galactic nuclei detected in deep radio continuum surveys. Using two multi-wavelength datasets, over the NOAO Deep Wide Field Survey Bo\"otes and COSMOS fields,…

The selection of high-redshift galaxies often involves spectral energy distribution (SED) fitting to photometric data, an expectation for contamination levels, and measurement of sample completeness -- all vetted through comparison to…

We present a new SED-fitting based routine for redshift determination that is optimised for mid-infrared (MIR) low-resolution spectroscopy. Its flexible template scaling increases the sensitivity to slope changes and small scale features in…

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…

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC…

The Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2) is a new survey designed as the successor of the original MaDCoWS survey. MaDCoWS2 improves upon its predecessor by using deeper optical and infrared data and a more powerful…

We present a machine learning search for high-redshift ($5.0 < z < 6.5$) quasars using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We explore the imputation of missing values for high-redshift…

We present the results of a 135-arcmin$^2$ search for high-redshift galaxies lensed by 29 clusters from the MAssive Cluster and extended MAssive Cluster Surveys (MACS and eMACS). We use relatively shallow images obtained with the Hubble…

We present an optimised galaxy cluster finder, 3D-Matched-Filter (3D-MF), which utilises galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys. This method is an…

The Red-Sequence Cluster Survey (RCS) is a 100 deg^2 galaxy cluster survey designed to provide a large sample of optically selected clusters of galaxies with redshifts 0.1<z<1.4. The survey data are also useful for a variety of lensing…

We use public V-band imaging data from the wide-angle surveys conducted by the ESO Imaging Survey project (EIS) to further investigate the nature of the EIS galaxy cluster candidates. These were originally identified by applying a…

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys and estimating multi-color redshifts for the extragalactic objects. We use a library of >65000 color templates for comparison with observed…

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep…