Related papers: Cluster identification via Voronoi tessellation
We propose a novel method to select satellite galaxies in outer regions of galaxy groups or clusters using weak gravitational lensing. The method is based on the theoretical expectation that the tangential shear pattern around satellite…
We present an end-to-end system for detecting and clustering faces by identity in full-length movies. Unlike works that start with a predefined set of detected faces, we consider the end-to-end problem of detection and clustering together.…
Galaxy clusters are one of the important cosmological probes to test the consistency of the observable structure and evolution of our Universe with the predictions of specific cosmological models. We use results from our analysis of the…
We present new automatic methods of search for star clusters using the data available in new huge stellar catalogues. Using 2MASS catalogue we have discovered over ten new open clusters in the region of Galaxy anticenter and determined…
We introduce a dynamical system based on the vertices of Voronoi tessellations. This dynamical system acts on finite or discrete point sets in the plane, taking a point set to the vertex set of its Voronoi tessellation. We explore the…
Galaxy clusters are usually detected in blind optical surveys via suitable filtering methods. We present an optimal matched filter which maximizes their signal-to-noise ratio by taking advantage of the knowledge we have of their intrinsic…
Weak gravitational lensing and the Sunyaev-Zel'dovich effect provide complementary information on the composition of clusters of galaxies. Preliminary results from cluster SZ observations with the Very Small Array are presented. A Bayesian…
We discuss a method to constrain the intrinsic three-dimensionale shapes of galaxy clusters by combining X-Ray and Sunyaev-Zeldovich observations. The method is applied to a sample of 25 X-Ray selected clusters, with measured…
A new method for a simultaneous search for clusters of galaxies in X-ray photon maps and optical galaxy maps is described. The merging of X-ray and optical data improves the source identification so that a large amount of telescope time for…
In this paper, we present the tools used to search for galaxy clusters in the Kilo Degree Survey (KiDS), and our first results. The cluster detection is based on an implementation of the optimal filtering technique that enables us to…
Star cluster studies hold the key to understanding star formation, stellar evolution, and origin of galaxies. The detection and characterization of clusters depend on the underlying background density and the cluster richness. We examine…
Clusters of galaxies are used in a variety of ways to do cosmology. Some of them are presented here. Their X-ray emitting gas allows us to determine the baryon fraction, dark matter distribution and the matter density $\Omega_{m}$ of the…
A methodology is developed to identify clusters in a bulk phase which are topologically equivalent to certain reference clusters. The selected reference clusters are the Morse clusters with 13 or less atoms and the 13 atom clusters found in…
Dark sirens are a powerful way to infer cosmological and astrophysical parameters from the combination of gravitational wave sirens and galaxy catalogues. Importantly, the method relies on the completeness of the galaxy catalogues being…
The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M200>=1E14 Msun/h extracted from a…
The Cluster Lensing And Supernova survey with Hubble (CLASH) is a 524-orbit multi-cycle treasury program to use the gravitational lensing properties of 25 galaxy clusters to accurately constrain their mass distributions. The survey,…
Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…
Probabilistic circuits (PCs) enable exact and tractable inference but employ data independent mixture weights that limit their ability to capture local geometry of the data manifold. We propose Voronoi tessellations (VT) as a natural way to…
We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantised variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that…
We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities). The problem is formulated as the matching of a graph to a template with smaller dimension, hence…