Related papers: Distant Cluster Search: Welcoming some Newcomers f…
In this paper, I will introduce a fast and novel clustering algorithm based on Gaussian distribution and it can guarantee the separation of each cluster centroid as a given parameter, $d_s$. The worst run time complexity of this algorithm…
Context. Clusters of galaxies are important for cosmology and astrophysics. They may be discovered through either the summed optical/IR radiation originating from their member galaxies or via X-ray emission originating from the hot…
k-medoids algorithm is a partitional, centroid-based clustering algorithm which uses pairwise distances of data points and tries to directly decompose the dataset with $n$ points into a set of $k$ disjoint clusters. However, k-medoids…
The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties, galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for…
Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have already noticed that this is not suitable for multi-scale…
In high-dimension, low-sample size (HDLSS) data, it is not always true that closeness of two objects reflects a hidden cluster structure. We point out the important fact that it is not the closeness, but the "values" of distance that…
Context. Since the first publication of the Gaia catalogue a new view of our Galaxy has arrived. Its astrometric and photometric information has improved the precision of the physical parameters of open star clusters obtained from them.…
We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities. Traditional spectral clustering techniques discover clusters by processing a similarity…
Fast radio transient search algorithms identify signals of interest by iterating and applying a threshold on a set of matched filters. These filters are defined by properties of the transient such as time and dispersion. A real transient…
We present the results of a search for galaxy clusters in the first 36 XMM-Newton pointings on the COSMOS field. We reach a depth for a total cluster flux in the 0.5-2 keV band of 3x10-15 ergs cm-2 s-1, having one of the widest XMM-Newton…
In [1], a clustering algorithm was given to find the centers of clusters quickly. However, the accuracy of this algorithm heavily depend on the threshold value of d-c. Furthermore, [1] has not provided any efficient way to select the…
We carried out a systematic search for new star clusters in a field of 5$^{\circ} \times5^{\circ}$ centred close to the Galactic Nucleus using the infrared JHK$_s$ 2MASS Survey archive. In addition we searched for embedded clusters in the…
This is the first in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here we present a new, automated method for identifying relaxed clusters based on their morphologies in X-ray…
Aims. We intend to compile a new galaxy group and cluster sample of the latest available SDSS data, adding several parameter for the purpose of studying the supercluster network, galaxy and group evolution, and their connection to the…
This paper proposes a simple, automatic and efficient clustering algorithm, namely, Automatic Merging for Optimal Clusters (AMOC) which aims to generate nearly optimal clusters for the given datasets automatically. The AMOC is an extension…
We present a comparison of X-ray and optical luminosities and luminosity functions of cluster candidates from a joint optical/X-ray survey, the ROSAT Optical X-Ray Survey. Completely independent X-ray and optical catalogs of 23 ROSAT fields…
We present results of an initial search for clusters of galaxies at z~1 and above, using data from 2.9 square degrees of XMM-Newton images. By selecting weak potentially extended X-ray sources with faint or no identifications in deep,…
This paper studies clustering algorithms for dynamically evolving graphs $\{G_t\}$, in which new edges (and potential new vertices) are added into a graph, and the underlying cluster structure of the graph can gradually change. The paper…
We present weak lensing mass reconstructions for the 20 high-redshift clusters i n the ESO Distant Cluster Survey. The weak lensing analysis was performed on deep, 3-color optical images taken with VLT/FORS2, using a composite galaxy…
Cluster analysis is the distribution of objects into different groups or more precisely the partitioning of a data set into subsets (clusters) so that the data in subsets share some common trait according to some distance measure. Unlike…