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We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with…

Astrophysics · Physics 2009-11-13 Feng Dong , Elena Pierpaoli , James E. Gunn , Risa H. Wechsler

We present an improved version of FIT3D, a fitting tool for the analysis of the spectroscopic properties of the stellar populations and the ionized gas derived from moderate resolution spectra of galaxies. FIT3D is a tool developed to…

Galaxy clusters are powerful probes of astrophysics and cosmology through gravitational lensing: the clusters' mass, dominated by 85% dark matter, distorts background light. Yet, mass reconstruction lacks the scalability and large-scale…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Diego Royo , Brandon Zhao , Adolfo Muñoz , Diego Gutierrez , Katherine L. Bouman

We present a simple approach for obtaining robust values of astrophysical parameters from the observed colour-magnitude diagrams (CMDs) of star clusters. The basic inputs are the Hess diagram built with the photometric measurements of a…

Solar and Stellar Astrophysics · Physics 2015-05-20 C. Bonatto , F. Campos , S. O. Kepler , E. Bica

We develop a new density-based clustering algorithm named CRAD which is based on a new neighbor searching function with a robust data depth as the dissimilarity measure. Our experiments prove that the new CRAD is highly competitive at…

Computation · Statistics 2019-04-09 Xin Huang , Yulia R. Gel

Open clusters are key coeval structures that help us understand star formation, stellar evolution and trace the physical properties of our Galaxy. In the past years, the isolation of open clusters from the field has been heavily alleviated…

Young massive star clusters spanning $\sim 10^4 - 10^8 M_\odot$ in mass have been observed to have similar surface brightness profiles. Recent hydrodynamical simulations of star cluster formation have also produced star clusters with this…

We investigate how observations of strong lensing can be used to infer cosmological parameters, in particular the equation of state of dark energy. We focus on the growth of the critical lines of lensing clusters with the source redshift as…

Cosmology and Nongalactic Astrophysics · Physics 2012-04-03 Britta Zieser , Matthias Bartelmann

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…

Cosmology and Nongalactic Astrophysics · Physics 2012-03-08 Jeffrey A. Blackburne , Christopher S. Kochanek

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…

Machine Learning · Computer Science 2015-01-07 Teng Qiu , Yongjie Li

Dynamical state of galaxy clusters is closely related to their observational properties in X-ray, optical and radio wavelengths. We develop a method to diagnose the substructure and dynamical state of galaxy clusters by using photometric…

Cosmology and Nongalactic Astrophysics · Physics 2013-10-16 Z. L. Wen , J. L. Han

The Milky Way has accreted many ultra-faint dwarf galaxies (UFDs), and stars from these galaxies can be found throughout our Galaxy today. Studying these stars provides insight into galaxy formation and early chemical enrichment, but…

When it comes to clustering nonconvex shapes, two paradigms are used to find the most suitable clustering: minimum cut and maximum density. The most popular algorithms incorporating these paradigms are Spectral Clustering and DBSCAN. Both…

Machine Learning · Computer Science 2019-07-02 Sibylle Hess , Wouter Duivesteijn , Philipp Honysz , Katharina Morik

It is common practice in cosmology to model large-scale structure observables as lognormal random fields, and this approach has been successfully applied in the past to the matter density and weak lensing convergence fields separately. We…

Cosmology and Nongalactic Astrophysics · Physics 2017-07-18 Henrique S. Xavier , Filipe B. Abdalla , Benjamin Joachimi

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…

Machine Learning · Computer Science 2020-06-09 Xiang Li , Ben Kao , Caihua Shan , Dawei Yin , Martin Ester

Based on a recent photometric redshift galaxy catalogue, we have searched for galaxy clusters in the Stripe~82 region of the Sloan Digital Sky Survey by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to…

The Large-Scale Structure (LSS) of the Universe is a homogeneous network of galaxies separated in dense complexes, the superclusters of galaxies, and almost empty voids. The superclusters are young structures that did not have time to…

Astrophysics of Galaxies · Physics 2020-01-13 I. Santiago-Bautista , C. A. Caretta , H. Bravo-Alfaro , E. Pointecouteau , F. Madrigal

We present the first step toward deriving cosmological constraints through the abundances of galaxy clusters selected in a $510\,\mathrm{deg}^2$ weak-lensing aperture mass map, constructed with the Year-Three shear catalog from the Hyper…

Studies of galaxy protoclusters yield insights into galaxy cluster formation complementary to those obtained via `archaeological' studies of present-day galaxy clusters. Submillimetre-selected galaxies (SMGs) are one class of sources used…

Spatial clustering has been widely used for spatial data mining and knowledge discovery. An ideal multivariate spatial clustering should consider both spatial contiguity and aspatial attributes. Existing spatial clustering approaches may…

Machine Learning · Computer Science 2022-04-01 Yuhao Kang , Kunlin Wu , Song Gao , Ignavier Ng , Jinmeng Rao , Shan Ye , Fan Zhang , Teng Fei