Related papers: ORCA: The Overdense Red-sequence Cluster Algorithm
Wide-field optical imaging surveys are efficient at identifying galaxy clusters, but optically identified clusters suffer from projection effects--physically unassociated galaxies along the line of sight can be misidentified as cluster…
The Sloan Digital Sky Survey has obtained 450 square degrees of photometric scan data, in five bands (u',g',r',i',z'), which we use to identify clusters of galaxies. We illustrate how we do star-galaxy separation, and present a simple and…
To test whether clusters have rising mass to light ratios at large radii and to estimate the amplitude of the density fluctuation spectrum on the scale of 10\hmpc\ the Canadian Network for Observational Cosmology (CNOC) cluster…
Building a comprehensive catalog of galaxy clusters is a fundamental task for the studies on the structure formation and galaxy evolution. In this paper, we present COSMIC (Cluster Optical Search using Machine Intelligence in Catalogs), an…
Identifying galaxy clusters through overdensities of galaxies in photometric surveys is the oldest and arguably the most economic and mass-sensitive detection method, compared to X-ray and Sunyaev-Zel'dovich Effect surveys that detect the…
The Pan-STARRS1 survey is currently obtaining imaging in 5 bands (grizy) for the $3\pi$ steradian survey, one of the largest optical surveys ever conducted. The finished survey will have spatially varying depth, due to the survey strategy.…
The Spitzer Adaptation of the Red-sequence Cluster Survey (SpARCS) is a z'-passband imaging survey of the 50 deg^2 Spitzer SWIRE Legacy fields, designed with the primary aim of creating the first large, homogeneously selected sample of…
We present an optically selected galaxy cluster catalog from ~ 2,700 square degrees of the Digitized Second Palomar Observatory Sky Survey (DPOSS), spanning the redshift range 0.1 < z < 0.5, providing an intermediate redshift supplement to…
We present a new simulated galaxy cluster catalog based on the IllustrisTNG simulation. We use the Mulguisin (MGS) algorithm to identify galaxy overdensities. Our cluster identification differs from the previous FoF cluster identification…
We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension,…
We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red…
We present the first sample of 882 optically selected galaxy clusters in the Deep Lens Survey (DLS), selected with the Bayesian Cluster Finder. We create mock DLS data to assess completeness and purity rates, and find that both are at least…
Galaxy clusters selected based on overdensities of galaxies in photometric surveys provide the largest cluster samples. Yet modeling the selection function of such samples is complicated by non-cluster members projected along the line of…
SPIDERS is the spectroscopic follow-up effort of the Sloan Digital Sky Survey IV (SDSS-IV) project for the identification of X-ray selected galaxy clusters. We present our catalogue of 2740 visually inspected galaxy clusters as a part of…
This paper is the first in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our primary aim is to test the…
We describe an automated method, the Cut & Enhance method (CE) for detecting clusters of galaxies in multi-color optical imaging surveys. This method uses simple color cuts, combined with a density enhancement algorithm, to up-weight pairs…
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 developed an algorithm to find and characterize gravitationally lensed galaxies (arcs) to perform a comparison of the observed and simulated arc abundance. Observations are from the Cluster Lensing And Supernova survey with Hubble…
We present an optimised galaxy cluster finder, 3D-Matched-Filter (3D-MF), which utilises galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys. This method is an…
The identification of star clusters holds significant importance in studying galaxy formation and evolution history. However, the task of swiftly and accurately identifying star clusters from vast amounts of photometric images presents an…