Related papers: Recovering Redshift Distributions with Cross-Corre…

Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation…

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…

Photometric galaxy surveys constitute a powerful cosmological probe but rely on the accurate characterization of their redshift distributions using only broadband imaging, and can be very sensitive to incomplete or biased priors used for…

Observations of galaxy clustering are made in redshift space, which results in distortions to the underlying isotropic distribution of galaxies. These redshift-space distortions (RSD) not only degrade important features of the matter…

We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to measure the redshift and mass…

In addition to the maximum likelihood approach, there are two other methods which are commonly used to reconstruct the true redshift distribution from photometric redshift datasets: one uses a deconvolution method, and the other a…

We analyze the clustering of large scale structure in the Universe in a model independent method, accounting for anisotropic effects along and transverse to the line of sight. The Baryon Oscillation Spectroscopy Survey Data Release 11…

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…

High-redshift clusters of galaxies are amongst the largest cosmic structures. Their properties and evolution are key ingredients to our understanding of cosmology: to study the growth of structure from the inhomogeneities of the cosmic…

We investigate how well the redshift distribution of a population of extragalactic objects can be reconstructed using angular cross-correlations with a sample whose redshifts are known. We derive the minimum variance quadratic estimator,…

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…

We present a Bayesian reconstruction method which maps a galaxy distribution from redshift-space to real-space inferring the distances of the individual galaxies. The method is based on sampling density fields assuming a lognormal prior…

We discuss the theoretical interpretation of observational data concerning the clustering of galaxies at high redshifts. Building on the theoretical machinery developed by Matarrese et al. (1997), we make detailed quantitative predictions…

The accumulation of redshifts provides a significant observational bottleneck when using galaxy cluster surveys to constrain cosmological parameters. We propose a simple method to allow the use of samples where there is a fraction of the…

The joint analysis of galaxy clustering and galaxy-shear cross-correlations (galaxy-galaxy lensing) in imaging surveys constitutes one of the main avenues to obtain cosmological information. Analyses from Stage III surveys have assumed…

This paper reviews the current status of measurements of galaxy clustering at high redshifts (z > 0.3). The focus is on the inherent limitations in the observation and interpretation of the ``evolution of clustering''. It is likely that…

We study the redshift space correlation function of galaxy clusters for observational samples constructed in different surveys. We explore correlation amplitudes, pairwise velocity distributions and bias factors. Systematics in cluster…

We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…

We discuss the effects of redshift--space distortions on the estimate of high order galaxy correlation functions. We use both the Perseus--Pisces redshift survey and the results of high--resolution N--body simulations to explore the…

Redshift-space clustering anisotropies caused by cosmic peculiar velocities provide a powerful probe to test the gravity theory on large scales. However, to extract unbiased physical constraints, the clustering pattern has to be modelled…