Related papers: Using neural networks to estimate redshift distrib…
Traditional photometric redshift methods use only color information about the objects in question to estimate their redshifts. This paper introduces a new method utilizing colors, luminosity, surface brightness, and radial light profile to…
Photometric galaxy surveys constitute a powerful cosmological probe but rely on the accurate characterization of their redshift distributions using only broadband imaging, and can be very sensitive to incomplete or biased priors used for…
We conduct a detailed analysis of the photometric redshift requirements for the proposed Dark Energy Survey (DES) using two sets of mock galaxy simulations and an artificial neural network code - ANNz. In particular, we examine how optical…
Gravitational lensing can be used to analyze the redshift distribution of faint galaxies. In particular the magnification bias modifies locally the galaxy number density of lensed sources observed in lensing clusters. This depletion area…
We explore the enhanced self-calibration of photometric galaxy redshift distributions, $n(z)$, through the combination of up to six two-point functions. Our $\rm 3\times2pt$ configuration is comprised of photometric shear, spectroscopic…
We present a method for mapping variations between probability distribution functions and apply this method within the context of measuring galaxy redshift distributions from imaging survey data. This method, which we name PITPZ for the…
We present a Neural Network based emulator for the galaxy redshift-space power spectrum that enables several orders of magnitude acceleration in the galaxy clustering parameter inference, while preserving 3$\sigma$ accuracy better than…
In order to enlarge publicly available optical cluster catalogs, in particular at high redshift, we have performed a systematic search for clusters of galaxies in the CFHTLS. We used the Le Phare photometric redshifts for the galaxies…
We present a method for automated classification of galaxies with low signal-to-noise (S/N) spectra typical of redshift surveys. We develop spectral simulations based on the parameters for the 2dF Galaxy Redshift Survey, and with these…
We present a scheme based on artificial neural networks (ANN) to estimate the line-of-sight velocities of individual galaxies from an observed redshift-space galaxy distribution. We find an estimate of the peculiar velocity at a galaxy…
We present a new training set for estimating empirical photometric redshifts of galaxies, which was created as part of the 2dFLenS project. This training set is located in a 700 sq deg area of the KiDS South field and is randomly selected…
This is the first exploration of the galaxy distribution function at redshifts greater than about 0.1. Redshifts are based on the North and South GOODS Catalogs. In each catalog we examine clustering in the two redshift bands 0.47 < z < 0.8…
We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods -- ANNZ2, BPZ…
The new generation of deep photometric surveys requires unprecedentedly precise shape and photometry measurements of billions of galaxies to achieve their main science goals. At such depths, one major limiting factor is the blending of…
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…
With the advancement of technology, machine learning-based analytical methods have pervaded nearly every discipline in modern studies. Particularly, a number of methods have been employed to estimate the redshift of gamma-ray loud active…
We present a new neural network approach for deblending galaxy images in astronomical data using Residual Dense Neural network (RDN) architecture. We train the network on synthetic galaxy images similar to the typical arrangements of field…
Galaxies whose images overlap in the focal plane of a telescope, commonly referred to as blends, are often located at different redshifts. Blending introduces a challenge to weak-lensing cosmology probes since such blends are subject to…
A method for using the sub-millimeter band to determine photometric redshifts of luminous high-z dusty galaxies is presented. It is based on the observation that local ultra-luminous IR galaxies show an average spectral energy distribution…
We measure photometric redshifts and spectral types for galaxies in the COSMOS survey. We use template fitting technique combined with luminosity function priors and with the option to simultaneously estimate dust extinction (i.e. E(B-V))…