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Redshift is a key quantity for inferring cosmological model parameters. In photometric redshift estimation, cosmologists use the coarse data collected from the vast majority of galaxies to predict the redshift of individual galaxies. To…

Applications · Statistics 2016-04-07 Rafael Izbicki , Ann B. Lee , Peter E. Freeman

Photometric redshifts play an important role as a measure of distance for various cosmological topics. Spectroscopic redshifts are only available for a very limited number of objects but can be used for creating statistical models. A broad…

Instrumentation and Methods for Astrophysics · Physics 2016-08-30 Kai Lars Polsterer , Antonio D'Isanto , Fabian Gieseke

We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…

Astrophysics of Galaxies · Physics 2020-10-14 Paula Tarrío , Stefano Zarattini

The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application where such new methods improved the results, substantially.…

Instrumentation and Methods for Astrophysics · Physics 2018-01-31 Antonio D'Isanto , Kai Lars Polsterer

Photometric redshift uncertainties are a major source of systematic error for ongoing and future photometric surveys. We study different sources of redshift error caused by choosing a suboptimal redshift histogram bin width and propose…

Cosmology and Nongalactic Astrophysics · Physics 2017-05-02 Markus Michael Rau , Ben Hoyle , Kerstin Paech , Stella Seitz

The properties of galaxies in the local universe have been shown to depend upon their environment. Future large scale photometric surveys such as DES and Euclid will be vital to gain insight into the evolution of galaxy properties and the…

Astrophysics of Galaxies · Physics 2015-08-06 James Etherington , Daniel Thomas

Much of the science that is made possible by multiwavelength redshift surveys requires the use of photometric redshifts. But as these surveys become more ambitious, and as we seek to perform increasingly accurate measurements, it becomes…

Cosmology and Nongalactic Astrophysics · Physics 2010-11-23 Ryan F. Quadri , Rik J. Williams

Given multiband photometric data from the SDSS DR6, we estimate galaxy redshifts. We employ a Random Forest trained on color features and spectroscopic redshifts from 80,000 randomly chosen primary galaxies yielding a mapping from color to…

Measuring environment for large numbers of distant galaxies is still an open problem, for which we need galaxy positions and redshifts. Photometric redshifts are more easily available for large numbers of galaxies, but at the price of…

Astrophysics of Galaxies · Physics 2016-01-06 Nicola Malavasi , Lucia Pozzetti , Olga Cucciati , Sandro Bardelli , Andrea Cimatti

For more that seventy years, the measurements of fluxes of galaxies at different wavelengths and derived colours have been used to estimate their corresponding cosmological distances. From the fields of galaxy and AGN evolution to precision…

Astrophysics of Galaxies · Physics 2018-06-06 Mara Salvato , Olivier Ilbert , Ben Hoyle

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…

Astrophysics · Physics 2008-11-26 James J. Wray , James E. Gunn

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…

Cosmology and Nongalactic Astrophysics · Physics 2016-06-15 J. Asorey , M. Carrasco Kind , I. Sevilla-Noarbe , R. J. Brunner , J. Thaler

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…

Methodology · Statistics 2021-04-02 Arindam Fadikar , Stefan M. Wild , Jonas Chaves-Montero

Calibrating the photometric redshifts of >10^9 galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining the required spectroscopic redshifts for training and…

We present a simple method for evaluating the nonlinear biasing function of galaxies from a redshift survey. The nonlinear biasing is characterized by the conditional mean of the galaxy density fluctuation given the underlying mass density…

Astrophysics · Physics 2009-10-31 Yair Sigad , Enzo Branchini , Avishai Dekel

Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual…

Cosmology and Nongalactic Astrophysics · Physics 2016-07-27 Boris Leistedt , Daniel J. Mortlock , Hiranya V. Peiris

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…

The determination of the galaxy luminosity function is an active and fundamental field in observational cosmology. In this paper we propose a cost effective way of measuring galaxy luminosity functions at faint magnitudes. Our technique…

Astrophysics · Physics 2009-10-28 M. U. SubbaRao , A. J. Connolly , A. S. Szalay , D. C. Koo

We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples.…

Cosmology and Nongalactic Astrophysics · Physics 2015-07-20 Markus Michael Rau , Stella Seitz , Fabrice Brimioulle , Eibe Frank , Oliver Friedrich , Daniel Gruen , Ben Hoyle
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