Related papers: DS+: a method for the identification of cluster su…
We analyse a catalogue of simulated clusters within the theoretical framework of the Spherical Collapse Model (SCM), and demonstrate that the relation between the infall velocity of member galaxies and the cluster matter overdensity can be…
The Large-Scale Structure (LSS) of the Universe is a homogeneous network of galaxies separated in dense complexes, the superclusters of galaxies, and almost empty voids. The superclusters are young structures that did not have time to…
Galaxy clusters, the most massive, dark-matter-dominated, and most recently assembled structures in the Universe, are key tools for probing cosmology. However, uncertainties in scaling relations that connect cluster mass to observables like…
Based on a recent photometric redshift galaxy catalogue, we have searched for galaxy clusters in the Stripe~82 region of the Sloan Digital Sky Survey by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to…
We identify cosmic voids from galaxy density fields under the theory of void-cluster correspondence. We extend the previous novel void-identification method developed for the matter density field to the galaxy density field for practical…
We present a selection of candidates of clusters and protoclusters of galaxies identified in the photometric data of the HSC-SSP Wide Public Data Release 3 (PDR3), spanning the redshift range $\rm 0.1 \leq z \leq 2$. The selection method,…
In the theoretical framework of hierarchical structure formation, galaxy clusters evolve through continuous accretion and mergers of substructures. Cosmological simulations have revealed the best picture of the Universe as a 3-D filamentary…
We present a new, objectively selected, sample of galaxy overdensities detected in the Hubble Space Telescope Medium Deep Survey. These clusters/groups were found using an automated procedure which involved searching for statistically…
Joint lensing and dynamical mass profile determinations of galaxy clusters are an excellent tool to constrain modification of gravity at cosmological scales. However, search for tiny departures from General Relativity calls for an accurate…
We investigate the internal structure of clusters of galaxies in high-resolution N-body simulations of 4 different cosmologies. There is a higher proportion of disordered clusters in critical-density than in low-density universes, although…
The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties or galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for…
Clustering real world data often faced with curse of dimensionality, where real world data often consist of many dimensions. Multidimensional data clustering evaluation can be done through a density-based approach. Density approaches based…
We describe an objective and automated method for detecting clusters of galaxies from optical imaging data. This method is a variant of the so-called `matched-filter' technique pioneered by Postman et al. (1996). With simultaneous use of…
Time series clustering promises to uncover hidden structural patterns in data with applications across healthcare, finance, industrial systems, and other critical domains. However, without validated ground truth information, researchers…
We suggest how we can use the mass profile of galaxy clusters beyond their virial radius to measure their mass accretion rate, a key prediction of structure formation models. The mass profile can be estimated by applying the caustic…
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…
The links between the internal structure of galaxy groups and clusters and cosmological parameters are reviewed here. The mass density profiles of clusters, inferred from both optical analyses of the galaxy surface number density profile…
We propose a new hierarchical method which uses dynamical arguments to find and describe substructures in galaxy clusters. This method (hereafter h--method or h--analysis) uses a hierarchical clustering analysis to determine the…
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…
In this work we introduce a new method to perform the identification of groups of galaxies and present results of the identification of galaxy groups in the Seventh Data Release of the Sloan Digital Sky Survey (SDSS-DR7). Our methodology…