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The clusters of a distribution are often defined by the connected components of a density level set. However, this definition depends on the user-specified level. We address this issue by proposing a simple, generic algorithm, which uses an…

Methodology · Statistics 2015-10-29 Ingo Steinwart

By virtue of their high galaxy space densities and their large spatial separations, clusters are efficient and accurate tracers of the large-scale density and velocity fields. Substantial progress has been made over the past decade in the…

Astrophysics · Physics 2007-05-23 Marc Postman

Clusters of galaxies mass can be inferred by indirect observations, see X-ray band, Sunyaev-Zeldovich (SZ) effect signal or optical. Unfortunately, all of them are affected by some bias. Alternatively, we provide an independent estimation…

Cosmology and Nongalactic Astrophysics · Physics 2022-02-09 Daniel de Andres , Weiguang Cui , Florian Ruppin , Marco De Petris , Gustavo Yepes , Ichraf Lahouli , Gianmarco Aversano , Romain Dupuis , Mahmoud Jarraya

We investigate the formation of clusters of galaxies in an expanding universe using a new code that regrids at a region of high density. In particular we investigate two models for the initial conditions, both with the standard CDM power…

Astrophysics · Physics 2015-06-24 Suvendra N. Dutta

We present the first cosmological constraints from analyzing higher-order galaxy clustering on non-linear scales. We use ${\rm S{\scriptsize IM}BIG}$, a forward modeling framework for galaxy clustering analyses that employs simulation-based…

We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…

Cosmology and Nongalactic Astrophysics · Physics 2026-01-21 Ethan Tregidga , David Harvey , Luca Biggio , Felix Vecchi

We develop a method to identify cosmic voids from the matter density field by adopting a physically-motivated concept that voids are the counterpart of massive clusters. To prove the concept we use a pair of $\Lambda$CDM simulations, a…

Cosmology and Nongalactic Astrophysics · Physics 2021-03-16 Junsup Shim , Changbom Park , Juhan Kim , Ho Seong Hwang

Cosmological probes pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters which characterize the underlying physical system -- our Universe. Modern…

Instrumentation and Methods for Astrophysics · Physics 2019-05-21 Timur Takhtaganov , Zarija Lukic , Juliane Mueller , Dmitriy Morozov

Cosmological surveys aim to use the evolution of the abundance of galaxy clusters to accurately constrain the cosmological model. In the context of LCDM, we show that it is possible to achieve the required percent level accuracy in the halo…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-05 Darren S. Reed , Robert E. Smith , Doug Potter , Aurel Schneider , Joachim Stadel , Ben Moore

We present a new clustering method, Significance Mode Analysis (SigMA), to extract co-spatial and co-moving stellar populations from large-scale surveys such as ESA Gaia. The method studies the topological properties of the density field in…

Current catalogues of open clusters are rather heterogeneous and incomplete lists of clusters than true catalogues. Before there has been no attempts of automatic search for open clusters in huge photometric catalogues using homogeneous…

Astrophysics · Physics 2007-05-23 Ivan Zolotukhin , Sergey Koposov , Elena Glushkova

We investigate the extent to which the number of clusters of mass exceeding $10^{15}\,M_{\odot}\,h^{-1}$ within the local super-volume ($<135\mathrm{\,Mpc}h^{-1}$) is compatible with the standard $\Lambda$CDM cosmological model. Depending…

Cosmology and Nongalactic Astrophysics · Physics 2021-09-08 Stephen Stopyra , Hiranya V. Peiris , Andrew Pontzen , Jens Jasche , Priyamvada Natarajan

Classically, Bayesian clustering interprets each component of a mixture model as a cluster. The inferred clustering posterior is highly sensitive to any inaccuracies in the kernel within each component. As this kernel is made more flexible,…

Methodology · Statistics 2025-12-12 David Buch , Miheer Dewaskar , David B. Dunson

We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Francisco-Shu Kitaura

One of the major science goals over the coming decade is to test fundamental physics with probes of the cosmic large-scale structure out to high redshift. Here we present a fully Bayesian approach to infer the three-dimensional cosmic…

Cosmology and Nongalactic Astrophysics · Physics 2019-10-09 Natalia Porqueres , Jens Jasche , Guilhem Lavaux , Torsten Enßlin

Lensing by galaxy clusters is a versatile probe of cosmology and extragalactic astrophysics, but the accuracy of some of its predictions is limited by the simplified models adopted to reduce the (otherwise untractable) number of degrees of…

Cosmology and Nongalactic Astrophysics · Physics 2021-04-28 Pietro Bergamini , Adriano Agnello , Gabriel Bartosch Caminha

The X-ray regime, where the most massive visible component of galaxy clusters, the intra cluster medium (ICM), is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to…

Cosmology and Nongalactic Astrophysics · Physics 2017-06-28 G. Schellenberger , T. H. Reiprich

The void power spectrum is related to the clustering of low-density regions in the large-scale structure (LSS) of the Universe, and can be used as an effective cosmological probe to extract the information of the LSS. We generate the galaxy…

Cosmology and Nongalactic Astrophysics · Physics 2024-11-01 Yingxiao Song , Qi Xiong , Yan Gong , Furen Deng , Kwan Chuen Chan , Xuelei Chen , Qi Guo , Guoliang Li , Ming Li , Yun Liu , Yu Luo , Wenxiang Pei , Chengliang Wei

We propose a simple and efficient clustering method for high-dimensional data with a large number of clusters. Our algorithm achieves high-performance by evaluating distances of datapoints with a subset of the cluster centres. Our…

Machine Learning · Computer Science 2022-03-30 Georgios Exarchakis , Omar Oubari , Gregor Lenz