Related papers: SDSS DR7 superclusters. Principal component analys…
We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at $z=3.1$. These protocluster 'complexes', designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of $z=3.1$…
In this work, we use the theory of spatial networks to analyze galaxy distributions. The aim is to develop new approaches to study the spatial galaxy environment properties by means of the network parameters. We investigate how each of the…
Open clusters are key coeval structures that help us understand star formation, stellar evolution and trace the physical properties of our Galaxy. In the past years, the isolation of open clusters from the field has been heavily alleviated…
We study the galaxy clustering dependence on the $\left[\mathrm{O\scriptsize{II}}\right]$ emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift $z\sim0.1$. We select volume-limited samples of galaxies with different…
In this paper we investigate, using high resolution N-body simulations, the density profiles and the morphologies of galaxy clusters in seven models of structure formation. We show that these properties of clusters are closely related to…
A review of the study of superclusters based on the 2dFGRS and SDSS is given. Real superclusters are compared with models using simulated galaxies of the Millennium Run. We show that the fraction of very luminous superclusters in real…
We apply scaling and the theory of the fundamental limits of the second-order molecular susceptibility to identify material classes with ultralarge nonlinear-optical response. Size effects are removed by normalizing all nonlinearities to…
I review the status of large-scale structure studies based on redshift surveys of galaxies and clusters of galaxies. In particular, I compare recent results on the power spectrum and two-point correlation correlation function from the 2dF…
We investigate the spectral correlations between different species used to observe molecular clouds. We use hydrodynamic simulations and a full chemical network to study the abundances of over 150 species in typical Milky Way molecular…
Principal Component Analysis (PCA) is an important tool of dimension reduction especially when the dimension (or the number of variables) is very high. Asymptotic studies where the sample size is fixed, and the dimension grows [i.e., High…
Complex networks are a powerful modeling tool, allowing the study of countless real-world systems. They have been used in very different domains such as computer science, biology, sociology, management, etc. Authors have been trying to…
We present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering 416 deg$^2$, and the SDSS DR11 spectroscopic…
Geometrical model of structure of the universe is examined to obtain analytical expression for the two points nonlinear correlation function. According to the model the objects (galaxies) are concentrated into two types of structure…
Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering has evolved from shallow models to deep and achieved promising results in many benchmark datasets. However,…
We created artificial color-magnitude diagrams of Monte Carlo dynamical models of globular clusters, and then used observational methods to determine the number of blue stragglers in those clusters. We compared these blue stragglers to…
We investigate the possibility of very early formation of primordial star clusters from high-\sigma perturbations in cold dark matter dominated structure formation scenarios. For this we have developed a powerful 2-level hierarchical…
In order to study the fragmentation of massive dense cores, which constitute the cluster cradles, we observed with the PdBI in the most extended configuration the continuum at 1.3 mm and the CO(2-1) emission of four massive cores. We detect…
High-dimensional clustering often relies on geometric or local-similarity structure, but the dominant separation between groups may not always be location-based. Differences in dispersion can create asymmetric local-neighborhood patterns:…
We aim at a direct measurement of the compactness of three galaxy-scale lenses in massive clusters, testing the accuracy of the scaling laws that describe the members in strong lensing (SL) models of galaxy clusters. We selected the…
Percolation, a paradigmatic geometric system in various branches of physical sciences, is known to possess logarithmic factors in its correlators. Starting from its definition, as the $Q\rightarrow1$ limit of the $Q$-state Potts model with…