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Related papers: The statistical Analysis of Star Clusters

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We exhibit a characteristic structure of the class of all regular graphs of degree d that stems from the spectra of their adjacency matrices. The structure has a fractal threadlike appearance. Points with coordinates given by the mean and…

Combinatorics · Mathematics 2007-08-30 V. Ejov , J. A. Filar , S. K. Lucas , P. Zograf

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…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 Martina Falco , Steen H. Hansen , Radoslaw Wojtak , Thejs Brinckmann , Mikkel Lindholmer , Stefania Pandolfi

Subclustering is investigated in a set of 67 rich cluster galaxy samples extracted from the ESO Nearby Abell Cluster Survey (ENACS) catalog. We apply four well-known statistical techniques to evaluate the frequency with which substructure…

Astrophysics · Physics 2007-05-23 J. M. Solanes , E. Salvador-Sole , G. Gonzalez-Casado

We use a cluster ensemble to determine the number of clusters, k, in a group of data. A consensus similarity matrix is formed from the ensemble using multiple algorithms and several values for k. A random walk is induced on the graph…

Machine Learning · Statistics 2014-08-06 Shaina Race , Carl Meyer , Kevin Valakuzhy

We examine the line-of-sight clustering of QSO heavy-element absorption-line systems, using a new measure of clustering, called the reduced second moment measure, that directly measures the mean over-density of absorbers. While closely…

Astrophysics · Physics 2009-10-30 Jean M. Quashnock , Michael L. Stein

Density-based clustering methodology has been widely considered in the statistical literature for classifying Euclidean observations. However, this approach has not been contemplated for directional data yet. In this work, directional…

Methodology · Statistics 2023-03-07 Paula Saavedra-Nieves , Martín Fernández-Pérez

Star formation is mainly determined by the observation of H$\alpha$ radiation which is related to the presence of short lived massive stars. Disc galaxies show a strong cutoff in H$\alpha$ radiation at a certain galactocentric distance…

Astrophysics of Galaxies · Physics 2011-08-31 Jan Pflamm-Altenburg , Pavel Kroupa

I outline the connections between some of the most widely used statistical measures of galaxy clustering and the fundamental issues in the theory of structure formation. I devote particular attention to the problem of biasing, i.e. to a…

Astrophysics · Physics 2007-05-23 David H. Weinberg

Most star complexes are in fact complexes of stars, clusters and gas clouds; term "star complexes" was introduced as general one disregarding the preferential content of a complex. Generally the high rate of star formation in a complex is…

Astrophysics · Physics 2010-11-23 Yuri N. Efremov

The structure formation of the dense interstellar material and the fragmentation of clumps into cores is a fundamental step to understand how stars and stellar clusters form. We aim to establish a statistical view of clump fragmentation at…

Astrophysics of Galaxies · Physics 2019-10-30 Yuxin Lin , Timea Csengeri , Friedrich Wyrowski , James S. Urquhart , Frederic Schuller , Axel Weiss , Karl M. Menten

We present a statistical system that can be used in the study of cluster populations. The basis of our approach is the construction of synthetic cluster color-magnitude-radius diagrams (CMRDs), which we compare with the observed data using…

Astrophysics · Physics 2012-08-27 Andrew E. Dolphin , Robert C. Kennicutt,

The spectral statistics of low--lying states of $fp$ shell nuclei are studied by performing large shell--model calculations with a realistic nuclear interaction. For $Ca$ isotopes, we find deviations from the predictions of the…

Nuclear Theory · Physics 2007-05-23 J. M. G. Gomez , V. R. Manfredi , L. Salasnich

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

Traditional estimators of the mass of galaxy clusters assume that the cluster components (galaxies, intracluster medium, and dark matter) are in dynamical equilibrium. Two additional estimators, that do not require this assumption, were…

Cosmology and Nongalactic Astrophysics · Physics 2009-02-02 Antonaldo Diaferio

Mass determinations are difficult to obtain and still frequently characterised by deceptively large uncertainties. We review below the various mass estimators used for star clusters of all ages and luminosities. We highlight a few recent…

Astrophysics · Physics 2007-05-23 Georges Meylan

The clusters of young stars in massive star-forming regions show a wide range of sizes, morphologies, and numbers of stars. Their highly subclustered structures are revealed by the MYStIX project's sample of 31,754 young stars in nearby…

Although much of the focus of statistical works on networks has been on static networks, multiple networks are currently becoming more common among network data sets. Usually, a number of network data sets, which share some form of…

Methodology · Statistics 2018-05-29 Sharmodeep Bhattacharyya , Shirshendu Chatterjee

We describe a method for comparing the frequency spectra of oscillating stars. We focus on solar-like oscillations, in which mode frequencies generally follow a regular pattern. On the basis that oscillation frequencies of similar stars…

Solar and Stellar Astrophysics · Physics 2015-05-18 Timothy R. Bedding , Hans Kjeldsen

We apply the scale-length method to several three dimensional samples of the Two degree Field Galaxy Redshift Survey. This method allows us to map in a quantitative and powerful way large scale structures in the distribution of galaxies…

Astrophysics · Physics 2009-08-03 Francesco Sylos Labini , Nikolay L. Vasilyev , Yurij V. Baryshev

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…

Machine Learning · Computer Science 2024-11-05 Feiping Nie , Yitao Song , Jingjing Xue , Rong Wang , Xuelong Li
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