Related papers: A new approach to finding galaxy groups using Mark…
We present a large catalog of loose groups of galaxies in the Southern Galactic Hemisphere, selected from the Perseus-Pisces redshift Survey (PPS). Particular care is taken in order to obtain group samples as homogeneous as possible to…
We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point and the three-point clustering statistics. The reference catalogues are drawn from the BigMultiDark…
We present a very large high-resolution cosmological N-body simulation, the Millennium-XXL or MXXL, which uses 303 billion particles to represent the formation of dark matter structures throughout a 4.1Gpc box in a LambdaCDM cosmology. We…
We introduce GalWeight, a new technique for assigning galaxy cluster membership. This technique is specifically designed to simultaneously maximize the number of bona fide cluster members while minimizing the number of contaminating…
We present a graph-theoretical approach to data clustering, which combines the creation of a graph from the data with Markov Stability, a multiscale community detection framework. We show how the multiscale capabilities of the method allow…
This paper considers cluster detection in Block Markov Chains (BMCs). These Markov chains are characterized by a block structure in their transition matrix. More precisely, the $n$ possible states are divided into a finite number of $K$…
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…
A robust prediction of $\Lambda{\rm CDM}$ cosmology is the halo circular velocity function (CVF), a dynamical cousin of the halo mass function. The correspondence between theoretical and observed CVFs is uncertain, however: cluster galaxies…
We use the Updated Zwicky Catalog of galaxies (Falco et al. 1999) to generate a catalog of groups, by means of a friend-of-friend algorithm. The correlation length of the total sample is well fitted with a power law $ \xi(r)=(r/r_0)^\gamma…
We test the cosmological implications of studying galaxy clustering using a tomographic approach, by computing the galaxy two-point angular correlation function $\omega(\theta)$ in thin redshift shells using a spectroscopic-redshift galaxy…
We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies…
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…
The classification of galaxy morphology is a hot issue in astronomical research. Although significant progress has been made in the last decade in classifying galaxy morphology using deep learning technology, there are still some…
We have developed a new geometrical method for identifying and reconstructing a homogeneous and highly complete set of galaxy groups in the next generation of deep, flux-limited redshift surveys. Our method combines information from the…
In recent years, machine learning (ML) algorithms have been successfully employed in Astronomy for analyzing and interpreting the data collected from various surveys. The need for new robust and efficient data analysis tools in Astronomy is…
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…
The traditional method of morphological classification, by visual inspection of images of uniform quality and by reference to standards for each type, is critically examined. The rate of agreement among traditional morphologists on the…
We introduce a new method for the identification of galaxy systems in redshift surveys based on the halo model. This method is a modified version of the K-means identification algorithm developed by Yang et al (2005). We have calibrated and…
We propose a novel technique to refine the modelling of galaxy clusters mass distribution using gravitational lensing. The idea is to combine the strengths of both "parametric" and "non-parametric" methods to improve the quality of the fit.…
We describe a new method (Poisson Probability Method, PPM) to search for high redshift galaxy clusters and groups by using photometric redshift information and galaxy number counts. The method relies on Poisson statistics and is primarily…