相关论文: An automatic procedure to extract galaxy clusters …

The number density of galaxy clusters across mass and redshift has been established as a powerful cosmological probe. Cosmological analyses with galaxy clusters traditionally employ scaling relations. However, many challenges arise from…

We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number of optically-selected galaxy clusters over the approximately…

We present a catalogue of 4499 groups and clusters of galaxies from the first data release of the multi-filter (5 broad, 7 narrow) Southern Photometric Local Universe Survey (S-PLUS). These groups and clusters are distributed over 273…

We describe a new method (Poisson Probability Method, PPM) to search for high redshift galaxy clusters and groups by using photometric redshift information and galaxy number counts. The method relies on Poisson statistics and is primarily…

We define a large sample of galaxies for use in a study of the fundamental plane in the intermediate redshift cluster CL1358+62 at $z=0.33$. We have analyzed high resolution spectra for 55 members of the cluster. The data were acquired with…

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an…

We present the ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) code, which uses three different machine learning techniques to classify galaxies in, and around, clusters, according to their projected phase-space position. We…

We present the complete galaxy cluster catalog from the Northern Sky Optical Cluster Survey, a new, objectively defined catalog of candidate galaxy clusters at z<0.25 drawn from the Digitized Second Palomar Observatory Sky Survey (DPOSS).…

We present an optically-selected catalog of 1073 galaxy cluster and group candidates at 0.3<z<1. These candidates are drawn from the Las Campanas Distant Clusters Survey (LCDCS), a drift-scan imaging survey of a 130 square degree strip of…

We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy…

Galaxy cluster-scale strong gravitational lensing systems are rare yet valuable tools for investigating the properties of dark matter and dark energy, as well as providing the opportunity to study the distant universe at flux levels and…

Globular clusters (GCs) are powerful tracers of the galaxy assembly process, and have already been used to obtain a detailed picture of the progenitors of the Milky Way. Using the E-MOSAICS cosmological simulation of a (34.4 Mpc)$^3$ volume…

Galaxy clusters are the most massive gravitationally bound systems consisting of dark matter, hot baryonic gas and stars. They play an important role in observational cosmology and galaxy evolution studies. We develop a deep learning model…

We use the 2dF Galaxy Redshift Survey data to compile catalogues of superclusters for the Northern and Southern regions of the 2dFGRS, altogether 543 superclusters at redshifts 0.009 < z < 0.2. We analyse methods of compiling supercluster…

We propose to radically expand the use of extragalactic globular clusters as tools for extragalactic archaeology. We propose a large-scale spectroscopic facility to obtain high spectral resolution (R $\sim$ 20,000) spectroscopy for a…

Next-generation wide-field spectroscopic surveys will observe the infall regions around large numbers of galaxy clusters with high sampling rates for the first time. Here we assess the feasibility of extracting the large-scale cosmic web…

We introduce Z-Sequence, a novel empirical model that utilises photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a…

We propose a clustering-based generalized low rank approximation method, which takes advantage of appealing features from both the generalized low rank approximation of matrices (GLRAM) and cluster analysis. It exploits a more general form…

We show how one may expect a significant number of SZ detections in future Planck data without any of the typical assumptions needed in present component separation methods, such as about the power spectrum or the frequency dependence of…

In this paper we present CALSAGOS: Clustering ALgorithmS Applied to Galaxies in Overdense Systems which is a PYTHON package developed to select cluster members and to search, find, and identify substructures. CALSAGOS is based on clustering…