Related papers: Using X-Ray Morphological Parameters to Strengthen…
The possibility to constrain cosmological parameters from galaxy surveys using field-level machine learning methods that bypass traditional summary statistics analyses, depends crucially on our ability to generate simulated training sets.…
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…
Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify…
We describe and test a method to quantitatively classify clusters of galaxies according to their projected morphologies. This method will be subsequently used to place constraints on cosmological parameters ($\Omega$ and the power spectrum…
We use cosmological gas dynamic simulations to investigate the accuracy of galaxy cluster mass estimates based on X-ray observations. The experiments follow the formation of clusters in different cosmological models and include the effects…
Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory's Legacy Survey of Space and Time are expected to…
Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled…
We discuss the measurements of the galaxy cluster mass functions at z=~0.05 and z=~0.5 using high-quality Chandra observations of samples derived from the ROSAT PSPC All-Sky and 400deg^2 surveys. We provide a full reference for the data…
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using…
X-ray observations of galaxy clusters potentially provide powerful cosmological probes if systematics due to our incomplete knowledge of the intracluster medium (ICM) physics are understood and controlled. In this paper, we present mock…
Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters…
X-ray selected surveys of clusters of galaxies have been reported to contain more regular cool core clusters compared to samples selected using the Sunyaev-Zel'dovich (SZ) effect. Morphology population studies on X-ray selected clusters…
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed…
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the…
We present the results of a simple but robust morphological classification of a statis- tically complete sample of 108 of the most X-ray luminous clusters at 0.15 < z < 0.7 observed with Chandra. Our aims are to (a) identify the most…
We present a theoretical model which aims at predicting the clustering properties of X-ray clusters in flux-limited surveys for different cosmological scenarios. The model uses the theoretical and empirical relations between mass,…
We investigate the importances of various dynamical features in predicting the dynamical state (DS) of galaxy clusters, based on the Random Forest (RF) machine learning approach. We use a large sample of galaxy clusters from the Three…
We forecast the potential of the forthcoming X-ray galaxy-cluster survey with eROSITA to constrain dark-energy models. We focus on spatially-flat cosmological scenarios with either constant or time-dependent dark-energy equation-of-state…
Morphology is often used to infer the state of relaxation of galaxy clusters. The regularity, symmetry, and degree to which a cluster is centrally concentrated inform quantitative measures of cluster morphology. The Cluster Lensing and…
X-ray images of galaxy clusters often show disturbed structures that are indication of cluster mergers. As a complementary to our previous work on dynamical state of 964 clusters observed by the Chandra, we process the X-ray images for 1308…