Related papers: The PAU Survey: Enhancing photometric redshift est…
ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift estimation decades ago. We enhanced the algorithm by…
Aims: We present a custom support vector machine classification package for photometric redshift estimation, including comparisons with other methods. We also explore the efficacy of including galaxy shape information in redshift…
The PAU (Physics of the Accelerating Universe) Survey goal is to obtain photometric redshifts (photo-z) and Spectral Energy Distribution (SED) of astronomical objects with a resolution roughly one order of magnitude better than current…
Determining the redshift distribution $n(z)$ of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object…
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z's). A wide plethora of methods have been developed, based either on template models fitting or on empirical…
In the era of large sky surveys, photometric redshifts (photo-z) represent crucial information for galaxy evolution and cosmology studies. In this work, we propose a new Machine Learning (ML) tool called Galaxy morphoto-Z with neural…
As a consequence of galaxy clustering, close galaxies observed on the plane of the sky should be spatially correlated with a probability that is inversely proportional to their angular separation. In principle, this information can be used…
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…
We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging dataset, and use the halo occupation distribution (HOD) framework to fit the clustering…
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will produce several billion photometric redshifts (photo-$z$'s), enabling cosmological analyses to select a subset of galaxies with the most accurate photo-$z$. We…
Several papers have recently highlighted the possibility of measuring redshift space distortions from angular auto-correlations of galaxies in photometric redshift bins. In this work we extend this idea to include as observables the…
Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy…
We present a combined galaxy-quasar approach to template-fitting photometric redshift techniques and show the method to be a powerful one. The code (ImpZ) is presented, developed and applied to two spectroscopic redshift catalogues, namely…
We employ deep learning (DL) to improve photometric redshifts (photo-$z$s) in the Kilo-Degree Survey Data Release 4 Bright galaxy sample (KiDS-Bright DR4). This dataset, used as a foreground for KiDS lensing and clustering studies, is…
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…
Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of…
We explore the behavior of the blue galaxy fraction over the redshift range 0.75 <= z <= 1.3 in the DEEP2 Survey, both for field galaxies and for galaxies in groups. The primary aim is to determine the role that groups play in driving the…
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…
In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of galaxies are needed. Correct estimation of the various…
We present a new (2+1)D galaxy cluster finder based on photometric redshifts called Wavelet Z Photometric (WaZP) applied to DES first year (Y1A1) data. The results are compared to clusters detected by the South Pole Telescope (SPT) survey…