Related papers: Cluster identification via Voronoi tessellation
Cluster analysis methods are used to identify homogeneous subgroups in a data set. In biomedical applications, one frequently applies cluster analysis in order to identify biologically interesting subgroups. In particular, one may wish to…
We explore the use of the tangential component of weak lensing shear to characterize the ellipticity of clusters of galaxies. We introduce an ellipticity estimator, and quantify its properties for isolated clusters from LCDM N-body…
Given the importance of clusters to the fields of cosmology and galaxy evolution, it is critical to understand how the cluster detection process affects (biases) ones scientific conclusions derived from a given cluster sample. I review the…
We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. The heart of the program is a neural network in form of Kohonen's self-organizing map. The resulting map is designed as an icon map…
Gravitational clustering broadens the count-in-cells distribution of galaxies for surveys along uncorrelated (well-separated) lines of sight beyond Poisson noise. A number of methods have proposed to measure this excess "cosmic" variance to…
This article explains an optimization-based approach for counting and localizing stars within a small cluster, based on photon counts in a focal plane array. The array need not be arranged in any particular way, and relatively small numbers…
We develop a neural network based pipeline to estimate masses of galaxy clusters with a known redshift directly from photon information in X-rays. Our neural networks are trained using supervised learning on simulations of eROSITA…
The Voronoi tessellation is the partition of space for a given seeds pattern and the result of the partition depends completely on the type of given pattern "random", Poisson-Voronoi tessellations (PVT), or "non-random", Non Poisson-Voronoi…
In data mining, density-based clustering, which entails classifying datapoints according to their distributions in some space, is an essential method to extract information from large datasets. With the advent of software-based radio,…
Face clustering is an essential tool for exploiting the unlabeled face data, and has a wide range of applications including face annotation and retrieval. Recent works show that supervised clustering can result in noticeable performance…
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…
We have developed a multiscale structure identification algorithm for the detection of overdensities in galaxy data that identifies structures having radii within a user-defined range. Our "multiscale probability mapping" technique combines…
Determining the masses of new physics particles appearing in decay chains is an important and longstanding problem in high energy phenomenology. Recently it has been shown that these mass measurements can be improved by utilizing the…
Current catalogues of open clusters are rather heterogeneous and incomplete lists of clusters than true catalogues. Before there has been no attempts of automatic search for open clusters in huge photometric catalogues using homogeneous…
The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means…
Observations of galaxy clusters (GC's) are a powerful tool to probe the evolution of the Universe at $z<2$. However, the determination of their real shape and structure is not completely understood and the assumption of asphericity is often…
This paper addresses the problem of unsupervised object localization in an image. Unlike previous supervised and weakly supervised algorithms that require bounding box or image level annotations for training classifiers in order to learn…
A direct approach to studying the galaxy-halo connection is to analyze groups and clusters of galaxies that trace the underlying dark matter halos, emphasizing the importance of identifying galaxy clusters and their associated brightest…
The mass measurement of galaxy clusters is an important tool for the determination of cosmological parameters describing the matter and energy content of the Universe. However, the standard methods rely on various assumptions about the…
Gravitational lensing in clusters of galaxies is an efficient tool to probe the mass distribution of galaxies and clusters, high redshift objects thanks to the gravitational amplification, and the geometry of the universe. We review some…