Related papers: Impact of Large-Scale Structure Systematics on Cos…
Current and future imaging surveys will measure cosmic shear with statistical precision that demands a deeper understanding of potential systematic biases in galaxy shape measurements than has been achieved to date. We use analytic and…
Increasingly large areas in cosmic shear surveys lead to a reduction of statistical errors, necessitating to control systematic errors increasingly better. One of these systematic effects was initially studied by Hartlap et al. in 2011,…
Wide, deep photometric surveys require robust photometric redshift estimates (photo-z's) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric…
Upcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent…
We analyse the correlation function of mock galaxy clusters in redshift space. We constructed several mock catalogues designed to mimic the selection biases inherent in a variety of observational surveys. We explore different effects that…
Galaxy structure and morphology is nearly always studied using the light originating from stars, however ideally one is interested in measuring structure using the stellar mass distribution. Not only does stellar mass trace out the…
A variety of subtle, and not-so-subtle selection effects influence the interpretation of galaxy counts, sizes and redshift distributions in the Hubble Deep Field. Comparison of the different HDF catalogs available in the literature and on…
We forecast cosmological parameter constraints for a cosmic shear analysis of the Rubin Observatory Legacy Survey of Space and Time (LSST), defining an analysis framework that can accurately recover the $\Lambda$CDM model in the presence of…
The reionization optical depth is the most poorly determined of the six $\Lambda$CDM parameters fit to CMB anisotropy data. Instrumental noise and systematics have prevented uncertainties from reaching their cosmic variance limit. At…
Spectral energy distribution (SED) modeling is one of the main methods to estimate galaxy properties, such as photometric redshifts, $z$, and stellar masses, $M_*$, for extragalactic imaging surveys. SEDs are currently modeled as light from…
We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1…
Giant arcs in strong lensing galaxy clusters can provide a purely geometric determination of cosmological parameters, such as the dark energy density and equation of state. We investigate sources of noise in cosmography with giant arcs,…
Data analysis from upcoming large galaxy redshift surveys, such as Euclid and DESI will significantly improve constraints on cosmological parameters. To optimally extract the information from these galaxy surveys, it is important to control…
Self-calibration techniques for analyzing galaxy cluster counts utilize the abundance and the clustering amplitude of dark matter halos. These properties simultaneously constrain cosmological parameters and the cluster observable-mass…
We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of…
An accurate calibration of the source redshift distribution $p(z)$ is a key aspect in the analysis of cosmic shear data. This, one way or another, requires the use of spectroscopic or high-quality photometric samples. However, the…
Cosmological constraints from cluster surveys rely on accurate mass estimates from the mass-observable relations. In order to avoid systematic biases and reduce uncertainties, we study the form and physical origin of the intrinsic scatter…
Most LSST extragalactic science will rely on photometric redshifts (photo-$z$) to extract distance information for the galaxies. However, an incomplete or non-representative training set can introduce bias into photo-$z$ estimation. It is…
Future large scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogs will require meticulous treatment of systematic contamination of the observed fields. We compare several…
We consistently analyse for the first time the impact of survey depth and spatial resolution on the most used morphological parameters for classifying galaxies through non-parametric methods: Abraham and Conselice-Bershady concentration…