相关论文: Three-Dimensional Identification and Reconstructio…

We have developed a geometrical method based on 3D Voronoi polyhedra and Delaunay tessellation for identifying and reconstructing clusters of galaxies in the next generation of deep, flux-limited redshift surveys. We here describe this…

We use the first 25% of the DEEP2 Galaxy Redshift Survey spectroscopic data to identify groups and clusters of galaxies in redshift space. The data set contains 8370 galaxies with confirmed redshifts in the range 0.7 <= z <= 1.4, over one…

[Abridged] We present a homogeneous and complete catalogue of optical groups identified in the purely flux limited (17.5<=I<=24.0) VIMOS-VLT Deep Survey (VVDS). We use mock catalogues extracted from the MILLENNIUM simulation, to correct for…

We present a public catalog of galaxy groups constructed from the spectroscopic sample of galaxies in the fourth data release from the DEEP2 Galaxy Redshift Survey, including the Extended Groth Strip (EGS). The catalog contains 1165 groups…

We present and discuss a method to identify substructures in combined angular-redshift samples of galaxies within Clusters. The method relies on the use of Discrete Wavelet Transform (hereafter DWT) and has already been applied to the…

We present a detailed description of the Voronoi Tessellation (VT) cluster finder algorithm in 2+1 dimensions, which improves on past implementations of this technique. The need for cluster finder algorithms able to produce reliable cluster…

We identify galaxy groups and clusters in volume-limited samples of the SDSS redshift survey, using a redshift-space friends-of-friends algorithm. We optimize the friends-of-friends linking lengths to recover galaxy systems that occupy the…

Many catalogues of isolated compact groups of galaxies (CGs) have been extracted using Hickson's criteria to identify isolated, dense systems of galaxies, with at least three or four galaxies concordant in magnitude and redshift. But is not…

Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated halos. In this work, we propose a widely applicable method for…

The interstellar medium (ISM) exhibits complex, multi-scale structures that are challenging to study due to their projection into two-dimensional (2D) column density maps. We present the Volume Density Mapper, a novel algorithm based on…

We propose and test a new method based on Richardson-Lucy deconvolution to reconstruct three-dimensional gas density and temperature distributions in galaxy clusters from combined X-ray and thermal Sunyaev-Zel'dovich observations. Clusters…

We present a new cluster-finding algorithm based on a combination of the Voronoi Tessellation and Friends-Of-Friends methods. The algorithm utilises probability distribution functions derived from a photometric redshift analysis and is…

Starting from the observed distribution of galaxy clusters in redshift space we use a two--step procedure to recover their distances and peculiar velocities. After statistically correcting for the unobserved cluster distribution in the zone…

We present GLIMPSE - Gravitational Lensing Inversion and MaPping with Sparse Estimators - a new algorithm to generate density reconstructions in three dimensions from photometric weak lensing measurements. This is an extension of earlier…

We present the reconstructed real-space density and the predicted velocity fields from the Two Mass Redshift Survey (2MRS). The 2MRS is the densest all-sky redshift survey to date and includes about 23,200 galaxies with extinction corrected…

We present an automated method to detect populations of groups in galaxy redshift catalogs. This method uses both analysis of the redshift distribution along lines of sight in fixed cells to detect elementary structures and a…

We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with…

We present a refined deep-learning-based method to reconstruct the three-dimensional dark matter density, gravitational potential, and peculiar velocity fields in the Zone of Avoidance (ZOA), a region near the galactic plane with limited…

The distribution of matter that is measured through galaxy redshift and peculiar velocity surveys can be harnessed to learn about the physics of dark matter, dark energy, and the nature of gravity. To improve our understanding of the matter…

We present a new cluster-finding algorithm based on a combination of the Voronoi Tessellation and Friends-Of-Friends methods. The algorithm utilises probability distribution functions derived from a photometric redshift analysis. We test…