Related papers: Super-resolving star clusters with sheaves
To reveal small galaxy groups in the Local Supercluster, a new approach is suggested which allows for individual properties of galaxies. The criterion is based on the assumption of closed motions of companions around the dominating group…
One important tool is the optimal clustering of data into useful categories. Dividing similar objects into a smaller number of clusters is of importance in many applications. These include search engines, monitoring of academic performance,…
We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses…
Clustering is a fundamental analysis tool aiming at classifying data points into groups based on their similarity or distance. It has found successful applications in all natural and social sciences, including biology, physics, economics,…
The detection of clusters of galaxies in large surveys plays an important part in extragalactic astronomy, and particularly in cosmology, since cluster counts can give strong constraints on cosmological parameters. X-ray imaging is in…
Galaxy clusters are the largest structures in Universe. They are very important as both cosmological probes and astrophysical laboratories. Several methods have been developed to detect galaxy clusters with different techniques (optical,…
The sample of known star clusters, the fundamental building blocks of galaxies, in the Milky Way is still extremely incomplete for objects beyond a distance of 1-2kpc. Many of the more distant and young clusters are compact and hidden…
Integrated spectrophotometric properties of stellar systems are intrinsically dispersed due to the stochastic nature of the small numbers of bright stars they contain. Among clusters, only the most massive ones can be used individually for…
Hypergraphs are a useful abstraction for modeling multiway relationships in data, and hypergraph clustering is the task of detecting groups of closely related nodes in such data. Graph clustering has been studied extensively, and there are…
The quantity of small scale solar photovoltaic (PV) arrays in the United States has grown rapidly in recent years. As a result, there is substantial interest in high quality information about the quantity, power capacity, and energy…
Velocity dispersions have been employed as a method to measure masses of clusters. To complement this conventional method, we explore the possibility of constraining cluster masses from the stacked phase space distribution of galaxies at…
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…
Local clustering aims at extracting a local structure inside a graph without the necessity of knowing the entire graph structure. As the local structure is usually small in size compared to the entire graph, one can think of it as a…
We present a uniform mid-infrared imaging and photometric survey of 36 young, nearby, star-forming clusters and groups using {\it Spitzer} IRAC and MIPS. We have confidently identified and classified 2548 young stellar objects using…
A most desirable feature of a standard candle to estimate astronomical distances is robustness against changes in metallicity and age. It is argued that the radii of main sequence stars with spectral types from solar to A0 show predictable…
The CAIRNS (Cluster And Infall Region Nearby Survey) project is a large spectroscopic survey of the infall regions surrounding nine nearby rich clusters of galaxies. I describe the survey and use the kinematics of galaxies in the infall…
Analysing the weak lensing distortions of the images of faint background galaxies provides a means to constrain the average mass distribution of cluster galaxies and potentially to test the extent of their dark matter haloes as a function…
The orientations of the red galaxies in a filament are aligned with the orientation of the filament. We thus develop a location-alignment-method (LAM) of detecting filaments around clusters of galaxies, which uses both the alignments of red…
We present a new cluster detection algorithm designed for the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) survey but with generic application to any multiband data. The method makes no prior assumptions about the…
Subspace clustering refers to the task of finding a multi-subspace representation that best fits a collection of points taken from a high-dimensional space. This paper introduces an algorithm inspired by sparse subspace clustering (SSC) [In…