Related papers: Photometric Redshifts and Photometry Errors
Image recognition models that work in challenging environments (e.g., extremely dark, blurry, or high dynamic range conditions) must be useful. However, creating training datasets for such environments is expensive and hard due to the…
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…
Large near-future galaxy surveys offer sufficient statistical power to make our cosmology analyses data-driven, limited primarily by systematic errors. Understanding the impact of systematics is therefore critical. We perform an end-to-end…
A new approach to estimating photometric redshifts - using Artificial Neural Networks (ANNs) - is investigated. Unlike the standard template-fitting photometric redshift technique, a large spectroscopically-identified training set is…
The covariance matrix of the matter power spectrum is a key element of the statistical analysis of galaxy clustering data. Independent realisations of observational measurements can be used to sample the covariance, nevertheless statistical…
A general non-Gaussian semiparametric model is adopted to characterize the measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array. Moreover, the recently derived \textit{robust semiparametric efficient} $R$-estimator…
Knowledge of the noise distribution in magnitude diffusion MRI images is the centerpiece to quantify uncertainties arising from the acquisition process. The use of parallel imaging methods, the number of receiver coils and imaging filters…
Optical measurements often exhibit mixed Poisson-Gaussian noise statistics, which hampers image quality, particularly under low signal-to-noise ratio (SNR) conditions. Computational imaging falls short in such situations when solely…
We use the MACSIS hydrodynamical simulations to estimate the extent of gas clumping in the intracluster medium of massive galaxy clusters and how it affects the hydrostatic mass bias. By comparing the clumping to the azimuthal scatter in…
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…
We test the effectiveness of photometric redshifts based upon galaxy spectral template fitting for X-ray luminous objects, using a sample of 65 sources detected by Chandra in the field of the Caltech Faint Galaxy Redshift Survey (CFGRS). We…
We study the importance of precise modelling of the photometric redshift error distributions on the estimation of parameters from cross correlation measurements and present a working example of the scattering matrix formalism to correct for…
We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys and estimating multi-color redshifts for the extragalactic objects. We use a library of >65000 color templates for comparison with observed…
In the first paper of this series, we studied the effect of baryon acoustic oscillations (BAO), redshift space distortions (RSD) and weak lensing (WL) on measurements of angular cross-correlations in narrow redshift bins. Paper-II presented…
We explore the effects of incorporating redshift uncertainty into measurements of galaxy clustering and cross-correlations of galaxy positions and cosmic microwave background (CMB) lensing maps. We use a simple Gaussian model for a redshift…
One image processing application that is very helpful for humans is to improve image quality, poor image quality makes the image more difficult to interpret because the information conveyed by the image is reduced. In the process of the…
Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift…
We present a photometric redshift (photo-$z$) estimation technique for galaxies in the P\lowercase{an}-STARRS1 (PS1) $3\pi $ survey. Specifically, we train and test a regression and a classification Random-Forest (RF) models using…
We introduce a non-Gaussian model of structure formation, and show how it produces surprising sampling effects on the estimation of the CMB power spectrum. Estimates of the average power spectrum based on small sky patches produce…
Images taken with modern detectors require calibration via flat fielding to obtain the same flux scale across the whole image. One method for obtaining the best possible flat fielding accuracy is to derive a photometric model from dithered…