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We propose the DPSM method, a density-based node clustering approach that automatically determines the number of clusters and can be applied in both data space and graph space. Unlike traditional density-based clustering methods, which…
Photometric galaxy surveys constitute a powerful cosmological probe but rely on the accurate characterization of their redshift distributions using only broadband imaging, and can be very sensitive to incomplete or biased priors used for…
We present an automated method to detect populations of groups in galaxy redshift catalogs. This method uses both analysis of the redshift distribution along lines of sight in fixed cells to detect elementary structures and a…
We have developed a new geometrical method for identifying and reconstructing a homogeneous and highly complete set of galaxy groups in the next generation of deep, flux-limited redshift surveys. Our method combines information from the…
We present a new cluster-finding algorithm based on a combination of the Voronoi Tessellation and Friends-Of-Friends methods. The algorithm utilises probability distribution functions derived from a photometric redshift analysis and is…
Abridged] We present here new results on the space density of rich, optically-selected, clusters of galaxies at low redshift (z<0.15). These results are based on the application of the matched filter cluster-finding algorithm to 1067 deg2…
Young stellar clusters harbour complex spatial structures emerging from the star formation process. Identifying stellar over-densities is a key step to constrain better how these structures are formed. The high accuracy of distances derived…
The aim of this work is to propose a meta-algorithm for automatic classification in the presence of discrete binary classes. Classifier learning in the presence of overlapping class distributions is a challenging problem in machine…
In a previous paper, we described a new method for including detailed information about substructure in semi-analytic models of halo formation based on merger trees. In this paper, we compare the predictions of our model with results from…
The results of the analysis of the subclustering in a sample of ESO Nearby Abell Cluster Survey (ENACS) galaxy clusters, with data complemented from other studies, are presented. The analysis is performed by using the S-tree method enabling…
With the advent of several galaxy surveys targeting star-forming galaxies, it is important to have models capable of interpreting their spatial distribution in terms of astrophysical and cosmological parameters. To address this need, we…
In this article, we develop a clique-based method for social network clustering. We introduce a new index to evaluate the quality of clustering results, and propose an efficient algorithm based on recursive bipartition to maximize an…
The graph-theoretical S-tree technique developed for the study of the nonlinear N-body systems, is used for the study for the first time of the substructure of a high redshift cluster of galaxies, namely of MS 1054-03, z\simeq 0.8. Nearby…
We have performed fully self-consistent $N$-body simulations of star clusters near the Galactic center (GC). Such simulations have not been performed because it is difficult to perform fast and accurate simulations of such systems using…
Nowadays, data are generated massively and rapidly from scientific fields as bioinformatics, neuroscience and astronomy to business and engineering fields. Cluster analysis, as one of the major data analysis tools, is therefore more…
Clusters of galaxies are the most massive objects in the Universe and mapping their location is an important astronomical problem. This paper describes an algorithm (based on statistical signal processing methods), a software architecture…
We use a sample of galaxies from the Two Micron All Sky Survey (2MASS) Extended Source Catalog to refine a matched filter method of finding galaxy clusters that takes into account each galaxy's position, magnitude, and redshift if…
Community discovery in the social network is one of the tremendously expanding areas which earn interest among researchers for the past one decade. There are many already existing algorithms. However, new seed-based algorithms establish an…
A critical issue in studying the evolution of galaxy clusters is to find ways that enable meaningful comparisons of clusters observed at different redshifts, as well as in various stages of their growth. Studies in the past have typically…
Context. Understanding the formation and evolution of star clusters in the Milky Way requires precise identification of clusters that form binary or multiple systems. Such systems offer valuable insight into the dynamical processes and…