Related papers: Superclusters and Voids in the Sloan DSS

Superclusters are the largest relatively isolated systems in the cosmic web. Using the SDSS BOSS survey we search for the largest superclusters in the redshift range $0.43<z<0.71$. We generate a luminosity-density field smoothed over $8…

We investigate the distribution of clusters of galaxies and determine the cluster correlation function and power spectrum. Clusters of galaxies located in rich superclusters with at least 8 members form a quasiregular network of…

The large supercluster structures obvious in recent galaxy redshift surveys are quantified using an one-dimensional cluster analysis (core sampling) and a three-dimensional cluster analysis based on the minimal spanning tree. The comparison…

Percolation analysis has long been used to quantify the connectivity of the cosmic web. Most of the previous work is based on density fields on grids. By smoothing into fields, we lose information about galaxy properties like shape or…

We identify gravitationally bound structures in the Ursa Major region using positions, velocities and photometry from the Sloan Digital Sky Survey (SDSS DR7) and the Third Reference Catalogue of Bright Galaxies (RC3). A friends-of-friends…

A compact group (CG) is a kind of special galaxy system where the galaxy members are separated at the distances of the order of galaxy size. The strong interaction between the galaxy members makes CGs ideal labs for studying the…

Subspace clustering (SC) is a promising clustering technology to identify clusters based on their associations with subspaces in high dimensional spaces. SC can be classified into hard subspace clustering (HSC) and soft subspace clustering…

The environment plays a critical role in galaxy evolution, with galaxy clusters and their infall regions offering diverse conditions that shape galaxies before they enter the dense cluster core, a process known as ``pre-processing''.…

We present a new determination of the cluster mass function and velocity dispersion function in a volume $\sim10^7 h^3$Mpc$^{-3}$ using the Fourth Data Release of the Sloan Digital Sky Survey (SDSS). We use the caustic technique to remove…

We identify 47,600 clusters of galaxies from photometric data of Two Micron All Sky Survey (2MASS), Wide-field Infrared Survey Explorer (WISE), and SuperCOSMOS, among which 26,125 clusters are recognized for the first time and mostly in the…

We study the mass distribution of a sample of 28 galaxy clusters using strong and weak lensing observations. The clusters are selected via their strong lensing properties as part of the Sloan Giant Arcs Survey (SGAS) from the Sloan Digital…

We investigate the accuracy requirements for field-level inference of cluster and void masses using data from galaxy surveys. We introduce a two-step framework that takes advantage of the fact that cluster masses are determined by flows on…

The progress of the studies on the orientation of galaxies in the Local Supercluster (LSC) is reviewed and a summary of recent results is given. Following a brief introduction of the LSC, we describe the results of early studies based on…

We conduct a systematic search for galaxy protoclusters at $z\sim3.8$ based on the latest internal data release (S16A) of the Hyper SuprimeCam Subaru strategic program (HSC-SSP). In the Wide layer of the HSC-SSP, we investigate the…

We have investigated the statistical clustering properties of galaxies by calculating the 2-point galaxy correlation function from the Durham/UKST Galaxy Redshift Survey. This survey is magnitude limited to bj = 17, contains 2500 galaxies…

We present a detailed study of Near-IR selected galaxies in a protocluster field at z = 3.13. Protocluster galaxies are selected using the available mutliwavelength data with the photometric redshift (photo-z) at 2.9 < z < 3.3, reaching a…

We present sDBSCAN, a scalable density-based clustering algorithm in high dimensions with cosine distance. Utilizing the neighborhood-preserving property of random projections, sDBSCAN can quickly identify core points and their…

We use deep-learning strategies to study the 2D percolation model on a square lattice. We employ standard image recognition tools with a multi-layered convolutional neural network. We test how well these strategies can characterise…

The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To enhance the UML step, we employed a dual-encoder architecture…

The nature of compact groups (CGs) of galaxies, apparently so dense that the galaxies often overlap, is still a subject of debate: Are CGs roughly as dense in 3D as they appear in projection? Or are they caused by chance alignments of…