Related papers: Mixture Models for Photometric Redshifts
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…
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts. However, catastrophic failure is still an unsolved problem…
We present accurate photometric redshifts in the 2-deg2 COSMOS field. The redshifts are computed with 30 broad, intermediate, and narrow bands covering the UV (GALEX), Visible-NIR (Subaru, CFHT, UKIRT and NOAO) and mid-IR (Spitzer/IRAC). A…
Spectral modeling codes that estimate photometric redshifts (photo-$z$) are a powerful and often reliable method for determining redshifts of galaxies. However, there are notable instances where degeneracies in spectral energy distribution…
We present photometric redshifts and spectral energy distribution (SED) classifications for a sample of 1542 optically identified sources detected with XMM in the COSMOS field. Our template fitting classifies 46 sources as stars and 464 as…
Based on the Sloan Digital Sky Survey Data Release 5 Galaxy Sample, we explore photometric morphology classification and redshift estimation of galaxies using photometric data and known spectroscopic redshifts. An unsupervised method,…
Context. Since the advent of modern multiband digital sky surveys, photometric redshifts (photo-z's) have become relevant if not crucial to many fields of observational cosmology, from the characterization of cosmic structures, to weak and…
We present a method to simultaneously infer the interstellar extinction parameters $A_0$ and $R_0$, stellar effective temperature $T_{\rm eff}$, and distance modulus $\mu$ in a Bayesian framework. Using multi-band photometry from SDSS and…
With the availability of the huge amounts of data produced by current and future large multi-band photometric surveys, photometric redshifts have become a crucial tool for extragalactic astronomy and cosmology. In this paper we present a…
We present a study of photometric redshift performance for galaxies and active galactic nuclei detected in deep radio continuum surveys. Using two multi-wavelength datasets, over the NOAO Deep Wide Field Survey Bo\"otes and COSMOS fields,…
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…
Extreme deconvolution (XD) of broad-band photometric data can both separate stars from quasars and generate probability density functions for quasar redshifts, while incorporating flux uncertainties and missing data. Mid-infrared…
We use the deepest and the most comprehensive photometric data currently available for GOODS-South galaxies to measure their photometric redshifts. The photometry includes VLT/VIMOS (U-band), HST/ACS (F435W, F606W, F775W, and F850LP bands),…
We estimated photometric redshifts (zphot) for more than 1.1 million galaxies of the ESO Public Kilo-Degree Survey (KiDS) Data Release 2. KiDS is an optical wide-field imaging survey carried out with the VLT Survey Telescope (VST) and the…
Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training…
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…
The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of the Universe, e.g. weak lensing and galaxy clustering. In…
Accurate and reliable photometric redshift determination is one of the key aspects for wide-field photometric surveys. Determination of photometric redshift for galaxies, has been traditionally solved by use of machine-learning and…
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…
Proposed cosmological surveys will make use of photometric redshifts of galaxies that are significantly fainter than any complete spectroscopic redshift surveys that exist to train the photo-z methods. We investigate the photo-z biases that…