Related papers: Dynamical Mass Measurements of Contaminated Galaxy…
This is the second paper in a series presenting the results from a 500 $h^{-1}$Mpc large constrained hydro-dynamical simulation of the local Universe (SLOW). The initial conditions are based on peculiar velocities derived from the…
Substructure in galaxy clusters can be quantified with the robust Delta statistics (Dressler and Shectman 1988) which uses velocity kinematics and sky projected positions. We test its sensitivity using dissipationless numerical simulations…
We introduce a new, non-parametric method to infer deprojected 3D mass profiles $M(r)$ of galaxy clusters from weak gravitational lensing observations. The method assumes spherical symmetry and a moderately small convergence, $\kappa…
Galaxy cluster masses help to constrain cosmological parameters through the halo mass function. To get rid of major biases in the mass measurement, we directly probe the cluster gravitational potentials by observing their gravitational…
We report weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known. This cluster sample, introduced earlier in this series of papers, spans redshifts 0.15 < z_cl < 0.7, and is well suited to calibrate mass proxies for…
We study the use of red sequence selected galaxy spectroscopy for unbiased estimation of galaxy cluster masses. We use the publicly available galaxy catalog produced using the semi-analytic model of De Lucia & Blaizot (2007) on the…
We present an improved determination of the total mass distribution of three CLASH/HFF massive clusters, MACS J1206.2-0847 (z=0.44), MACS J0416.1-2403 (z=0.40), Abell S1063 (z=0.35). We specifically reconstruct the sub-halo mass component…
I review our current knowledge of the mass distribution in clusters, as obtained from the analysis of the projected phase-space distribution of cluster galaxies. I discuss the methods of analysis, their relative advantages and…
Self-interacting dark matter is known as one of the most appropriate candidates for dark matter. Due to its excellent success in removing many astrophysical problems, particularly in small scale structure, studying this model has taken on…
We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature,…
The aim of this work is to perform a systematic study of the measures of the mass and concentration estimated by fitting the convergence profile of a large sample of mock galaxy cluster size lenses, created with the publicly available code…
In this work, we focus on the inverse medium scattering problem (IMSP), which aims to recover unknown scatterers based on measured scattered data. Motivated by the efficient direct sampling method (DSM) introduced in [23], we propose a…
This chapter reviews the application of Artificial Intelligence (AI) techniques to the study of galaxy clusters, covering both theoretical developments and their use as tools to infer cluster properties from a variety of observational…
We take advantage of a semi-analytic model with a state-of-art implementation of the formation of the intra-cluster light (ICL) to study the mass distribution of the ICL in galaxy groups and clusters, at different redshifts. We assume the…
We provide a new observational test for a key prediction of the \Lambda CDM cosmological model: the contributions of mergers with different halo-to-main-cluster mass ratios to cluster-sized halo growth. We perform this test by dynamically…
We present predictions for the two-point correlation function of galaxy clustering as a function of stellar mass, computed using two new versions of the GALFORM semi-analytic galaxy formation model. These models make use of a high…
We use deep learning to explore the nature of observed giant clumps in high-redshift disc galaxies, based on their identification and classification in cosmological simulations. Simulated clumps are detected using the 3D gas and stellar…
We study the classic $k$-means/median clustering, which are fundamental problems in unsupervised learning, in the setting where data are partitioned across multiple sites, and where we are allowed to discard a small portion of the data by…
Clusters of galaxies are powerful cosmological probes, particularly if their masses can be determined. One possibility for mass determination is to study the cosmic microwave background (CMB) on small angular scales and observe deviations…
In the era of Big Data, scalable and accurate clustering algorithms for high-dimensional data are essential. We present new Bayesian Distance Clustering (BDC) models and inference algorithms with improved scalability while maintaining the…