Related papers: Robust Quantification of Galaxy Cluster Morphology…
The mass accretion rate of galaxy clusters is a key factor in determining their structure, but a reliable observational tracer has yet to be established. We present a state-of-the-art machine learning model for constraining the mass…
Dwarf galaxies play an important role in studying the effects of the environment on galaxy formation and evolution. In this study, we aim to explore the relationship between the morphology, in particular the asymmetries of galaxies, and…
Multi-view clustering leverages consistent and complementary information across multiple views to provide more comprehensive insights than single-view analysis. However, the heterogeneity and redundancy of multi-view data pose significant…
This paper presents machine learning experiments performed over results of galaxy classification into elliptical (E) and spiral (S) with morphological parameters: concetration (CN), assimetry metrics (A3), smoothness metrics (S3), entropy…
We have assembled a sample of 115 galaxy clusters at 0.1<z<1.3 with archived Chandra ACIS-I observations. We present X-ray images of the clusters and make available region files containing contours of the smoothed X-ray emission. The…
We construct a sample of numerical models for clusters of galaxies and employ these to investigate their capability of imaging background sources into long arcs. Emphasis is laid on the statistics of these arcs. We study cross sections for…
One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational biology to social sciences to computer vision in part…
Results of a systematic study of substructure in X-ray surface brightness distributions of a combined sample of 470 REFLEX+BCS clusters of galaxies are presented. The fully automized morphology analysis is based on data of the 3rd…
The correlation function of galaxy clusters has often been used as a test of cosmological models. A number of assumptions are implicit in the comparison of theoretical expectations to data. Here we use an ensemble of ten large N-body…
In this work, we performed an analysis of the X-ray morphology of the 118 CHEX-MATE (Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation) galaxy clusters, with the aim to…
The properties of clusters of galaxies offer key insights into the assembly process of structure in the universe. Numerical simulations of cosmic structure formation in a hierarchical, dark matter dominated universe suggest that galaxy…
X-ray observations have played a key role in the study of substructure and merging in galaxy clusters. I review the evidence for cluster substructure and mergers obtained from X-ray observations with satellites that operated before Chandra…
[abridged] We present the analysis of the X-ray brightness and temperature profiles for six clusters belonging to both the Cool Core and Non Cool Core classes, in terms of the Supermodel (SM) developed by Cavaliere, Lapi & Fusco-Femiano…
Spectral clustering methods which are frequently used in clustering and community detection applications are sensitive to the specific graph constructions particularly when imbalanced clusters are present. We show that ratio cut (RCut) or…
We present a new cosmological probe for galaxy clusters, the halo sparsity. This characterises halos in terms of the ratio of halo masses measured at two different radii and carries cosmological information encoded in the halo mass profile.…
Morphological classification is a key piece of information to define samples of galaxies aiming to study the large-scale structure of the universe. In essence, the challenge is to build up a robust methodology to perform a reliable…
A computational theory for clustering and a semi-supervised clustering algorithm is presented. Clustering is defined to be the obtainment of groupings of data such that each group contains no anomalies with respect to a chosen grouping…
We introduce new methods for robust high-precision photometry from well-sampled images of a non-crowded field with a strongly varying point-spread function. For this work, we used archival imaging data of the open cluster M37 taken by MMT…
We propose a new clustering technique that can be regarded as a numerical method to compute the proximity gestalt. The method analyzes edge length statistics in the MST of the dataset and provides an a contrario cluster detection criterion.…
Encoded within the morphological structure of galaxies are clues related to their formation and evolutionary history. Recent advances pertaining to the statistics of galaxy morphology include sophisticated measures of concentration (C),…