Related papers: QSO Photometric Redshift estimation for the XMM-Ne…
The completed 2dF QSO Redshift (2QZ) Survey has been used to search for extreme large-scale cosmological structure (around 200 Mpc) over the redshift range 0<z<2.5. We demonstrate that statistically significant overdensities and…
We present some initial results from the 2dF QSO redshift survey. The aim of the survey is to produce an optically-selected catalogue of 25000 QSOs over the redshift range 0<z<3 using the 2-degree field at the Anglo-Australian Telescope.
We present and compare in this paper new photometric redshift catalogs of the galaxies in three public fields: the NTT Deep Field, the HDF-N and the HDF-S. Photometric redshifts have been obtained for thewhole sample, by adopting a $\chi^2$…
We present the results of the X-ray spectral analysis of an XMM-Newton-selected type II QSO sample with z>0.5 and 0.5-10 keV flux of 0.3-33 x 10^{-14} erg/s/cm^2. The distribution of absorbing column densities in type II QSOs is…
Photometric redshift estimation is becoming an increasingly important technique, although the currently existing methods present several shortcomings which hinder their application. Here it is shown that most of those drawbacks are…
The Wide Field Survey Telescope (WFST) is a dedicated time-domain multi-band ($u$, $g$, $r$, $i$, and $z$) photometric survey facility under construction. In this paper, we present a preliminary study that assesses the quality of…
A new method is developed for estimating photometric redshifts, using realistic template SEDs, extending over four decades in wavelength (i.e from 0.05 $\mu m$ to 1 mm). The SEDs are constructed for four different spectral types of galaxies…
Many of the cosmological tests to be performed by planned dark energy experiments will require extremely well-characterized photometric redshift measurements. Current estimates are that the true mean redshift of the objects in each photo-z…
The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a…
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 present photometric redshifts and associated probability distributions for all detected sources in the Extended Chandra Deep Field South (ECDFS). The work makes use of the most up-to-date data from the Cosmic Assembly Near-IR Deep Legacy…
We have observed 13 z >= 4.5 QSOs using the Multiband Imaging Photometer for Spitzer, nine of which were also observed with the Infrared Array Camera. The observations probe rest wavelengths ~ 0.6-4.3 micron, bracketing the local minimum in…
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…
We propose a new method to estimate the photometric redshift of galaxies by using the full galaxy image in each measured band. This method draws from the latest techniques and advances in machine learning, in particular Deep Neural…
Photometric redshift estimation algorithms are often based on representative data from observational campaigns. Data-driven methods of this type are subject to a number of potential deficiencies, such as sample bias and incompleteness.…
We present a simple, efficient and robust approach to improve cosmological redshift measurements. The method is based on the presence of a reference sample for which a precise redshift number distribution (dN/dz) can be obtained for…
Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is…
Photometric redshifts have proven a powerful tool in identifying galaxies over a large range of lookback times. We have been generalising this technique to incorporate the selection of candidate high redshift QSOs. We have applied this to a…
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 apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS…