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Related papers: Weak Separation, Pure Domains and Cluster Distance

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We show the existence of generalized clusters of a finite or even infinite number of sets, with minimal total perimeter and given total masses, in metric measure spaces homogeneous with respect to a group acting by measure preserving…

Analysis of PDEs · Mathematics 2021-12-16 Matteo Novaga , Emanuele Paolini , Eugene Stepanov , Vincenzo Maria Tortorelli

We test the precision with which weak lensing data can provide characteristic cluster mass profiles within Cold Dark Matter scenarios. Using a parallel treecode to simulate volumes as large as 500h-1 Mpc with good resolution, we generate…

Astrophysics · Physics 2009-10-28 Mary Crone , Fabio Governato , Joachim Stadel , Thomas Quinn

Let $X$ be a finite collection of sets (or "clusters"). We consider the problem of counting the number of ways a cluster $A \in X$ can be partitioned into two disjoint clusters $A_1, A_2 \in X$, thus $A = A_1 \uplus A_2$ is the disjoint…

Combinatorics · Mathematics 2017-05-24 Daniel Kane , Terence Tao

Weak gravitational lensing provides a direct way to study the mass distribution of clusters of galaxies at large radii. Unfortunately, large scale structure along the line of sight also contributes to the lensing signal, and consequently…

Astrophysics · Physics 2009-11-07 Henk Hoekstra

Model-based clustering is widely-used in a variety of application areas. However, fundamental concerns remain about robustness. In particular, results can be sensitive to the choice of kernel representing the within-cluster data density.…

Machine Learning · Statistics 2019-06-27 Leo L Duan , David B Dunson

Homogeneity and isotropy of the universe at sufficiently large scales is a fundamental premise on which modern cosmology is based. Fractal dimensions of matter distribution is a parameter that can be used to test the hypothesis of…

Astrophysics · Physics 2009-09-10 J. S. Bagla , Jaswant Yadav , T. R. Seshadri

This is the third of a series of papers of low X-ray luminosity galaxy clusters. In this work we present the weak lensing analysis of eight clusters, based on observations obtained with the Gemini Multi-Object Spectrograph in the $g'$, $r'$…

We study the following distribution clustering problem: Given a hidden partition of $k$ distributions into two groups, such that the distributions within each group are the same, and the two distributions associated with the two clusters…

Data Structures and Algorithms · Computer Science 2025-12-10 Gunjan Kumar , Yash Pote , Jonathan Scarlett

The reliability of cluster lens reconstruction techniques based on weak lensing is studied in terms of the accuracy of their reproduction of the total cluster mass as a function of distance from the cluster center. To do so, a variety of…

Astrophysics · Physics 2011-05-23 Matthias Bartelmann

The sensitivity and wide area reached by ongoing and future wide-field optical surveys allows for the detection of an increasing number of galaxy clusters uniquely through their weak lensing (WL) signal. This motivates the development of…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-18 G. Leroy , S. Pires , G. W. Pratt , C. Giocoli

We examine the class of weakly porous sets in Euclidean spaces. As our first main result we show that the distance weight $w(x)=\operatorname{dist}(x,E)^{-\alpha}$ belongs to the Muckenhoupt class $A_1$, for some $\alpha>0$, if and only if…

Classical Analysis and ODEs · Mathematics 2024-07-19 Theresa C. Anderson , Juha Lehrbäck , Carlos Mudarra , Antti V. Vähäkangas

Finding "true" clusters in a data set is a challenging problem. Clustering solutions obtained using different models and algorithms do not necessarily provide compact and well-separated clusters or the optimal number of clusters. Cluster…

Machine Learning · Computer Science 2026-03-12 Adil M. Bagirov , Ramiz M. Aliguliyev , Nargiz Sultanova , Sona Taheri

We study the notion of weak amalgamation in the context of diagonal conjugacy classes. Generalizing results of Kechris and Rosendal, we prove that for every countable structure $M$, Polish group $G$ of permutations of $M$, and $n \geq 1$,…

Logic · Mathematics 2022-03-11 Maciej Malicki

We study constrained clustering, where constraints guide the clustering process. In existing works, two categories of constraints have been widely explored, namely pairwise and cardinality constraints. Pairwise constraints enforce the…

Machine Learning · Computer Science 2023-01-30 Adel Bibi , Ali Alqahtani , Bernard Ghanem

We use the galaxy cluster X-ray temperature distribution function to constrain the amplitude of the power spectrum of density inhomogeneities on the scale corresponding to clusters. We carry out the analysis for critical density universes,…

Astrophysics · Physics 2015-06-24 Pedro T P Viana , Andrew R Liddle

We derive cosmological constraints using a galaxy cluster sample selected from the 2500~deg$^2$ SPT-SZ survey. The sample spans the redshift range $0.25< z<1.75$ and contains 343 clusters with SZ detection significance $\xi>5$. The sample…

Galaxy clusters are important targets for peculiar velocity studies as a direct comparison of the various distance indicators can be made. The potential problem of an environmental effect biasing the distances to clusters of different…

We report on the XMM-Newton (XMM) observation of RXJ1053.7+5735, one of the most distant X-ray selected clusters of galaxies, which also shows an unusual double-lobed X-ray morphology, indicative of a possible equal-mass cluster merger. The…

The statistical properties of galaxy clusters can only be used for cosmological purposes if observational effects related to cluster detection are accurately characterized. These effects include the selection function associated to cluster…

Cosmology and Nongalactic Astrophysics · Physics 2019-03-18 Michel Aguena , Marcos Lima

We consider the problem of metric learning subject to a set of constraints on relative-distance comparisons between the data items. Such constraints are meant to reflect side-information that is not expressed directly in the feature vectors…

Machine Learning · Computer Science 2016-12-06 Ehsan Amid , Aristides Gionis , Antti Ukkonen