Related papers: Clustering-based redshift estimation: method and a…
Many of the cosmological tests to be performed by planned dark energy experiments will require extremely well-characterized photometric redshift measurements. Current estimates are that the true mean redshift of the objects in each photo-z…
We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum…
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…
This work presents an unsupervised deep discriminant analysis for clustering. The method is based on deep neural networks and aims to minimize the intra-cluster discrepancy and maximize the inter-cluster discrepancy in an unsupervised…
Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. Whilst this strategy significantly improves…
This work uses hierarchical logistic Gaussian processes to infer true redshift distributions of samples of galaxies, through their cross-correlations with spatially overlapping spectroscopic samples. We demonstrate that this method can…
The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…
Clusters of galaxies are important laboratories for understanding both galaxy evolution and constraining cosmological quantities. Any analysis of clusters, however, is best done when one can reliably determine which galaxies are members of…
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…
Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy…
Aims: We study galaxy clustering and explore the dependence of galaxy properties on the the environment up to a redshift z~1, on the basis of a deep multi-band survey in the Chandra Deep Field South. Methods: We have developed a new method…
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…
The 2dF Galaxy Redshift Survey has now been completed and has mapped the three-dimensional distribution, and hence clustering, of galaxies in exquisite detail over an unprecedentedly large ($\sim 10^{8} h^{-3}$ Mpc$^{3}$) volume of the…
Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties.…
We discuss a method to build up and study a sample of distant galaxies, with 2<z<5, using the gravitational amplification effect in cluster-lenses for which the mass distribution is well known. The candidates are selected close to the…
The next generation of proposed galaxy surveys will increase the number of galaxies with photometric redshifts by two orders of magnitude, drastically expanding both redshift range and detection threshold from the current state of the art.…
We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic…
In this paper, we address the problem of spectroscopic redshift estimation in Astronomy. Due to the expansion of the Universe, galaxies recede from each other on average. This movement causes the emitted electromagnetic waves to shift from…
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…
As a consequence of galaxy clustering, close galaxies observed on the plane of the sky should be spatially correlated with a probability that is inversely proportional to their angular separation. In principle, this information can be used…