Related papers: Probabilistic photo-z machine learning models for …

Machine learning techniques, specifically the k-nearest neighbour algorithm applied to optical band colours, have had some success in predicting photometric redshifts of quasi-stellar objects (QSOs): Although the mean of differences between…

Accurate photometric redshifts are among the key requirements for precision weak lensing measurements. Both the large size of the Sloan Digital Sky Survey (SDSS) and the existence of large spectroscopic redshift samples that are…

With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit systematic uncertainties in this process has become…

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…

A trustworthy estimate of the redshift distribution $n(z)$ is crucial for using weak gravitational lensing and large-scale structure of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of…

Building on the first paper in this series (Duncan et al. 2018), we present a study investigating the performance of Gaussian process photometric redshift (photo-z) estimates for galaxies and active galactic nuclei detected in deep radio…

Discrepancies between cosmological parameter estimates from cosmic shear surveys and from recent Planck cosmic microwave background measurements challenge the ability of the highly successful $\Lambda$CDM model to describe the nature of the…

We use the overlap between multiband photometry of the Kilo-Degree Survey (KiDS) and spectroscopic data based on the Sloan Digital Sky Survey (SDSS) and Galaxy And Mass Assembly (GAMA) to infer the colour-magnitude relation of red-sequence…

We present a catalog of quasars and corresponding redshifts in the Kilo-Degree Survey (KiDS) Data Release 4. We trained machine learning (ML) models, using optical ugri and near-infrared ZYJHK_s bands, on objects known from Sloan Digital…

[Abbreviated] Upcoming large area sky surveys like EUCLID and eROSITA crucially depend on accurate photometric redshifts (photo-z). The identification of variable sources, such as AGNs, and the achievable redshift accuracy for varying…

When analyzing galaxy clustering in multi-band imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision,…

We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({\theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by…

We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of…

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Density Functions (PDFs) is still an open problem. First, because…

We demonstrate that highly accurate joint redshift-stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorithm, even with few photometric bands available. As an…

Four large-area Sunyaev-Zeldovich (SZ) experiments -- APEX-SZ, SPT, ACT, and Planck -- promise to detect clusters of galaxies through the distortion of Cosmic Microwave Background photons by hot (> 10^6 K) cluster gas (the SZ effect) over…

Photometric surveys produce large-area maps of the galaxy distribution, but with less accurate redshift information than is obtained from spectroscopic methods. Modern photometric redshift (photo-z) algorithms use galaxy magnitudes, or…

Aims. Construction of a new quasar candidate catalog from the Red-Sequence Cluster Survey 2 (RCS-2), identified solely from photometric information using an automated algorithm suitable for large surveys. The algorithm performance is tested…

Reconstructing sky models from dirty radio images for accurate source localization and flux estimation is crucial for studying galaxy evolution at high redshift, especially in deep fields using instruments like the Atacama Large Millimetre…

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.…