Related papers: A group finder algorithm optimised for the study o…
The Universe at the present epoch is found to be a network of matter over-dense and under-dense regions. To date, this picture of the Universe is best revealed through cosmological large-volume simulations and large-scale galaxy redshift…
Discovering cohesive groups is a fundamental primitive in graph-based recommender systems, underpinning tasks such as social recommendation, bundle discovery, and community-aware modeling. In interaction graphs, cohesion is often modeled as…
This paper presents a graph bundling algorithm that agglomerates edges taking into account both spatial proximity as well as user-defined criteria in order to reveal patterns that were not perceivable with previous bundling techniques. Each…
We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for…
In the theoretical framework of hierarchical structure formation, galaxy clusters evolve through continuous accretion and mergers of substructures. Cosmological simulations have revealed the best picture of the Universe as a 3-D filamentary…
Galaxy groups and clusters are the main tools used to test cosmological models and to study the environmental effect of galaxy formation. This work provides a catalogue of galaxy groups and clusters, as well as potentially merging systems…
We present a modified version of the friends-of-friends (FOF) structure finding algorithm, designed specifically to locate groups or clusters of galaxies in photometric redshift datasets. The main objective of this paper is to show that…
We use the halo occupation model to calibrate galaxy group finders in magnitude-limited redshift surveys. Since, according to the current scenario of structure formation, galaxy groups are associated with cold dark matter halos, we make use…
The main goal of this work is to investigate the influence of environment at different scales on the properties of galaxies in systems with a low number of members. To this end we used a catalogue of small galaxy systems comprising compact…
Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover…
Context. Friends-of-friends algorithms are a common tool to detect galaxy groups and clusters in large survey data. In order to be as precise as possible, they have to be carefully calibrated using mock catalogues. Aims. We create an…
Understanding the mechanisms that lead dense environments to host galaxies with redder colors, more spheroidal morphologies, and lower star formation rates than field populations remains an important problem. As most candidate processes…
We present a new sample of galaxy groups identified in the Sloan Digital Sky Survey Data Release 3. Following previous works we use the well tested friend-of-friend algorithm developed by Huchra & Geller which take into account the number…
We test the Friends-of-Friends (FoF) grouping algorithm, which depends on two linking lengths (LLs), plane-of-sky and line-of-sight (LOS), normalized to the mean nearest neighbor separation of field galaxies. We argue, on theoretical…
We present the first results of a serendipitous search for clusters of galaxies in deep ROSAT-PSPC pointed observations at high galactic latitude. The survey is being carried out using a Wavelet based Detection Algorithm which is not biased…
Identifying galaxy groups from redshift surveys of galaxies plays an important role in connecting galaxies with the underlying dark matter distribution. Current and future high-$z$ spectroscopic surveys, usually incomplete in redshift…
We construct a galaxy groups catalogue from the public 100K data release of the 2dF galaxy redshift survey. The group identification is carried out using a slightly modified version of the group finding algorithm developed by Huchra &…
We identify galaxy groups and clusters in volume-limited samples of the SDSS redshift survey, using a redshift-space friends-of-friends algorithm. We optimize the friends-of-friends linking lengths to recover galaxy systems that occupy the…
To reveal small galaxy groups in the Local Supercluster, a new approach is suggested which allows for individual properties of galaxies. The criterion is based on the assumption of closed motions of companions around the dominating group…
We create a new catalogue of groups and clusters for the 2dF GRS final release sample. We show that the variable linking length friends-of-friends (FoF) algorithms used so far yield groups with sizes that grow systematically with distance…