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Hierarchical clustering is one of the most powerful solutions to the problem of clustering, on the grounds that it performs a multi scale organization of the data. In recent years, research on hierarchical clustering methods has attracted…

Machine Learning · Computer Science 2019-08-02 Antonia Korba

In large scale structure formation, massive systems assemble through the hierarchical merging of less massive ones. Galaxy clusters, being the most massive and thus the most recent collapsed structures, still grow by accreting smaller…

Cosmology and Nongalactic Astrophysics · Physics 2013-11-20 Rubens E. G. Machado , Gastão B. Lima Neto

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its…

Genomics · Quantitative Biology 2018-06-07 Gary K. Chen , Eric Chi , John Ranola , Kenneth Lange

We have compiled a sample of 67 nearby ($z$ < 0.15) clusters of galaxies, for which on average more than 150 spectroscopic members are available, and, by applying different methods to detect substructures in their galaxy distribution, we…

Hypergraphs provide a powerful framework for modeling complex systems and networks with higher-order interactions beyond simple pairwise relationships. However, graph-based clustering approaches, which focus primarily on pairwise relations,…

Social and Information Networks · Computer Science 2025-07-16 Giuseppe F. Italiano , Athanasios L. Konstantinidis , Anna Mpanti , Fariba Ranjbar

In the most prominent current scenario of galaxy formation, galaxies form hierarchically through the merger of smaller systems. Such mergers could leave behind dynamical signatures which may linger long after the event. In particular, the…

Astrophysics · Physics 2011-03-10 K. M. Perrett , D. A. Stiff , D. A. Hanes , T. J. Bridges

We describe and test a method to quantitatively classify clusters of galaxies according to their projected morphologies. This method will be subsequently used to place constraints on cosmological parameters ($\Omega$ and the power spectrum…

Astrophysics · Physics 2009-10-28 David A. Buote , John C. Tsai

The main goals of the present work are (i) to study the substructure content of a representative, X-ray selected sample of 31 galaxy clusters, as traced by the spatial distribution of their red-sequence galaxies, and (ii) to compare it to…

Astrophysics of Galaxies · Physics 2019-01-29 Gaël Foëx

This paper considers networks where relationships between nodes are represented by directed dissimilarities. The goal is to study methods that, based on the dissimilarity structure, output hierarchical clusters, i.e., a family of nested…

Machine Learning · Computer Science 2016-07-22 Gunnar Carlsson , Facundo Mémoli , Alejandro Ribeiro , Santiago Segarra

Gravitational flexion has recently been introduced as a technique by which one can map out and study substructure in clusters of galaxies. Previous analyses involving flexion have measured the individual galaxy-galaxy flexion signal, or…

Astrophysics · Physics 2009-11-13 Adrienne Leonard , Lindsay J. King , Stephen M. Wilkins

The analysis of the spatial distribution and kinematics of galaxies in clusters allows one to determine the cluster internal dynamics. In this paper, I review the state of the art of this topic. In particular, I summarize what we have…

Astrophysics · Physics 2007-05-23 Andrea Biviano

A homogeneous sample of galaxy redshifts in the core regions (R < 0.5 h$^{-1}$ Mpc) of 12 clusters is used to measure the frequency of substructure with different tests. In 50 % of the cases substructure is detected, a frequency which…

Astrophysics · Physics 2007-05-23 P. Stein

We present a general method to identify infalling substructure in discrete datasets with position and line-of-sight velocity data. We exploit the fact that galaxies falling onto a brightest cluster galaxy (BCG) in a virialised cluster, or…

Astrophysics of Galaxies · Physics 2016-07-13 L. J. Oldham , N. W. Evans

Aims: Develop a data-driven and statistically based method for finding such clumps in Integrals of Motion space for nearby halo stars and evaluating their significance robustly. Methods: We use data from Gaia EDR3 extended with radial…

Astrophysics of Galaxies · Physics 2022-09-14 S. Sofie Lövdal , Tomás Ruiz-Lara , Helmer H. Koppelman , Tadafumi Matsuno , Emma Dodd , Amina Helmi

This paper presents the detailed results obtained in the search of density- velocity inhomogeneities in a volume limited and absolute magnitude limited sample of A-F type dwarfs within 125 parsecs of the Sun. A 3-D wavelet analysis is used…

Astrophysics · Physics 2009-10-30 E. Chereul , M. Crézé , O. Bienaymé

The Blooming Tree (BT) algorithm, based on the hierarchical clustering method, is designed to identify clusters, groups, and substructures from galaxy redshift surveys. We apply the BT algorithm to a wide-field ($10\times 10$ deg$^2$)…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-01 Heng Yu , Antonaldo Diaferio

A cluster finding method was developed and applied in four Local Group Galaxies (SMC, M31, M33 and NGC 6822). The aim is to study the young stellar population of these galaxies by identifying stellar structures in small and large scales.…

Instrumentation and Methods for Astrophysics · Physics 2016-04-13 Petros Drazinos , A. Karampelas , E. Kontizas , M. Kontizas , A. Dapergolas , E. Livanou , I. Bellas-Velidis

We propose a new approach to study the dynamical implications of mass models of clusters for the velocity structure of galaxies in the core. Strong and weak lensing data are used to construct the total mass profile of the cluster, which is…

Astrophysics · Physics 2015-06-24 Priyamvada Natarajan , Jean-Paul Kneib

We build upon Ordering Points To Identify Clustering Structure (OPTICS), a hierarchical clustering algorithm well-known to be a robust data-miner, in order to produce Halo-OPTICS, an algorithm designed for the automatic detection and…

Astrophysics of Galaxies · Physics 2021-01-06 William H. Oliver , Pascal J. Elahi , Geraint F. Lewis , Chris Power

We face a need of discovering a pattern in locations of a great number of points in a high-dimensional space. Goal is to group the close points together. We are interested in a hierarchical structure, like a B-tree. B-Trees are…

Data Structures and Algorithms · Computer Science 2016-07-19 Victor Sadikov , Oliver Rutishauser