Related papers: Generating Galaxy Clusters Mass Density Maps from …
We present a new method by which the total masses of galaxies including dark matter can be estimated from the kinematics of their globular cluster systems (GCSs). In the proposed method, we apply the convolutional neural networks (CNNs) to…
We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate around 73,000 mock images along various lines of sight…
Various differences in galaxy cluster properties derived from X-ray and weak lensing observations have been highlighted in the literature. One such difference is the observation of mass concentrations in lensing maps which have no X-ray…
The spatial distribution of compact dark matter in our Galaxy can be determined in a few years of monitoring Galactic globular clusters for microlensing. Globular clusters are the only dense fields of stars distributed throughout the…
Clusters of galaxies are studied from a theoretical point of view, comparing with observational results whenever possible. The problem is approached both analytically as well as by means of high-resoultion numerical simulations. The dark…
Analysing the weak lensing distortions of the images of faint background galaxies provides a means to constrain the average mass distribution of cluster galaxies and potentially to test the extent of their dark matter haloes as a function…
We present a novel approach to identify galaxy clusters that are undergoing a merger using a deep learning approach. This paper uses massive galaxy clusters spanning $0 \leq z \leq 2$ from \textsc{The Three Hundred} project, a suite of…
We present a new application of deep learning to reconstruct the cosmic microwave background (CMB) temperature maps from the images of microwave sky, and to use these reconstructed maps to estimate the masses of galaxy clusters. We use a…
Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated halos. In this work, we propose a widely applicable method for…
Cosmological N-body simulations predict that dark matter halos should have a universal shape characterized by a steep, cuspy inner profile. Here we report on a spectroscopic study of six clusters each containing a dominant brightest cluster…
Galaxies, diffuse gas, and dark matter make up the cosmic web that defines the large-scale structure of the Universe. We constrained the joint distribution of these constituents by cross-correlating galaxy samples binned by stellar mass…
All galaxies are thought to reside within large halos of dark matter, whose properties can only be determined from indirect observations. The formation and assembly of galaxies is determined from the interplay between these dark matter…
Galaxy clusters are the most massive gravitationally bound structures in the Universe and key probes of cosmic evolution. The large data volume expected from upcoming surveys requires efficient automated analysis methods for tens of…
The determination of galaxy cluster mass is of great importance since it is directly linked to the well- known problem of dark matter in the Universe and to the cluster baryon content. X-ray observations from satellites have enabled a…
We present an optical analysis of a sample of 11 clusters built from the EXCPRES sample of X-ray selected clusters at intermediate redshift (z ~ 0.5). With a careful selection of the background galaxies we provide the mass maps…
Clusters of galaxies are self-gravitating systems of mass ~10^14-10^15 Msun. They consist of dark matter (~80 %), hot diffuse intracluster plasma (< 20 %) and a small fraction of stars, dust, and cold gas, mostly locked in galaxies. In most…
Knowledge of the structure of galaxy clusters is essential for an understanding of large scale structure in the universe, and may provide important clues to the nature of dark matter. Moreover, the shape of the dark matter distribution in…
The determination of the mass of galaxy clusters from observations is subject to systematic uncertainties. Beyond the errors due to instrumental and observational systematic effects, in this work we investigate the bias introduced by…
Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS}…
The mass of a cluster of galaxies can be estimated from its lens magnification, which can be determined from the variation in number counts of background galaxies. In order to derive the mass one needs to make assumptions for the lens…