Related papers: SDSS DR7 superclusters. Principal component analys…
We study the characteristics of galaxy protoclusters using the latest L-galaxies semi-analytic model. Searching for protoclusters on a scale of $\sim 10 \, \mathrm{cMpc}$ gives an excellent compromise between the completeness and purity of…
We present a detailed investigation into which properties of CDM halos make them effective strong gravitational lenses. Strong lensing cross sections of 878 clusters from an N-body simulation are measured by ray tracing through 13,594…
One hundred and six galaxy clusters have been studied in detail using X-ray data and important global physical properties have been determined. Correlations between these properties are studied with respect to the description of clusters as…
A hierarchical scheme for clustering data is presented which applies to spaces with a high number of dimension ($N_{_{D}}>3$). The data set is first reduced to a smaller set of partitions (multi-dimensional bins). Multiple clustering…
The nearby Hydra Cluster ($\sim$50 Mpc) is an ideal laboratory to understand, in detail, the influence of the environment on the morphology and quenching of galaxies in dense environments. We study the Hydra cluster galaxies in the inner…
High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data. In this paper, we propose a new clustering procedure called…
Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial first steps…
We present a detailed study of the morphological features of 22 rich galaxy clusters. We systematically compare cluster images and morphological parameters in an attempt to reliably identify possible substructure in both optical and X-ray…
As a follow up to our recent study of a large sample of LMC clusters (astro-ph/0209031), we have conducted a similar study of the structures of ten SMC clusters, using archival Hubble Space Telescope snapshot data. We present surface…
The apparatus of correlation gamma function (\Gamma*(r)) is used to analyze volume-limited samples from the DR4 Main Galaxy Sample of the SDSS survey with the aim of determining the characteristic scales of galaxy clustering. Up to 20…
This paper presents a new clustering algorithm for symmetric positive semi-definite (SPSD) matrices, called K-Tensors. The method identifies structured subsets of the SPSD cone characterized by common principal component (CPC)…
We use the two-point correlation function to calculate the clustering properties of the recently completed SSRS2 survey. The redshift space correlation function for the magnitude-limited SSRS2 is given by xi(s)=(s/5.85 h-1 Mpc)^{-1.60} for…
We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the…
How does the clustering of galaxies depend on their inner properties like morphological type and luminosity? We address this question in the mathematical framework of marked point processes and clarify the notion of luminosity and…
We present a simultaneous analysis of galaxy cluster scaling relations between weak-lensing mass and multiple cluster observables, across a wide range of wavelengths, that probe both gas and stellar content. Our new hierarchical Bayesian…
We describe the scientific motivation behind, and the methodology of, the Stanford Cluster Search (StaCS), a program to compile a catalog of optically selected clusters of galaxies at intermediate and high (0.3 < z < 1) redshifts. The…
This work explores the morphology and dynamical properties of cores within rich superclusters, highlighting their role as transitional structures in the large-scale structure of the Universe. Using projected and radial velocity…
Strong lensing galaxy clusters provide a unique and powerful way to test simulation-derived structure predictions that follow from $\Lambda$ Cold Dark Matter ($\Lambda$CDM) cosmology. Specifically, the relative alignments of the dark matter…
In this work we used unsupervised machine learning methods in order to find possible clustering structures in superconducting materials data sets. We used the SuperCon database, as well as our own data sets complied from literature, in…
We investigate the properties and evolution of star particles in two simulations of isolated spiral galaxies, and two galaxies from cosmological simulations. Unlike previous numerical work, where typically each star particle represents one…