Related papers: Nearest neighbor vector analysis of sdss dr5 galax…
This is the first paper of a series in which we present new measurements of the observed rates of supernovae (SNe) in the local Universe, determined from the Lick Observatory Supernova Search (LOSS). We have obtained 2.3 million…
In order to determine the Galactic distribution of supernova remnants (SNRs) there are two main difficulties: (i) there are selection effects which mean that catalogues of SNRs are not complete, and (ii) distances are not available for most…
As a consequence of galaxy clustering, close galaxies observed on the plane of the sky should be spatially correlated with a probability that is inversely proportional to their angular separation. In principle, this information can be used…
Using the method of searching for arbitrary shaped voids in the distribution of volume-limited samples of galaxies from the DR5 SDSS survey, we have identified voids and investigated their characteristics and the change in these…
We analyse distribution, kinematics and star-formation (SF) properties of satellite galaxies in three different samples of nearby groups. We find that studied groups are generally well approximated by low-concentration NFW model, show a…
Recent large-scale galaxy spectroscopic surveys, such as the Sloan Digital Sky Survey (SDSS), enable us to execute a systematic, relatively-unbiased search for galaxy clusters. Such surveys make it possible to measure the 3-d distribution…
Consider a weighted or unweighted k-nearest neighbor graph that has been built on n data points drawn randomly according to some density p on R^d. We study the convergence of the shortest path distance in such graphs as the sample size…
Context. Convolutional neural networks (CNNs) are widely used for automated galaxy morphological classification in large surveys. However, projection effects, image artefacts, and intrinsic degeneracies limit reliable identification of…
The recent SDSS measured velocity distribution of satellite galaxies has been modelled in the context of MOND. We show that even when the extra constraint of adhering to the projected satellite number density profile is added, the two line…
The use of summary statistics beyond the two-point correlation function to analyze the non-Gaussian clustering on small scales is an active field of research in cosmology. In this paper, we explore a set of new summary statistics -- the…
We present the first analysis of three-dimensional genus statistics for the SDSS EDR galaxy sample. Due to the complicated survey volume and the selection function, analytic predictions of the genus statistics for this sample are not…
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…
The problem of nearest-neighbor (NN) condensation aims to reduce the size of a training set of a nearest-neighbor classifier while maintaining its classification accuracy. Although many condensation techniques have been proposed, few bounds…
We present a supervised neural network approach to the determination of photometric redshifts. The method was tuned to match the characteristics of the Sloan Digital Sky Survey and it exploits the spectroscopic redshifts provided by this…
We present a novel multimodal neural network (MNN) for classifying astronomical sources in multiband ground-based observations, from optical to near infrared, to separate sources in stars, galaxies and quasars. Our approach combines a…
This paper presents the results of simulated NGST observations. The goal of this work is to study the detectability of very high redshift galaxies and to try to characterize Wide Deep-Field observations. The main points made in this paper…
In this study, we investigate the morphology of galaxies in the TNG100 simulation by applying mock observation techniques and compare the results with the observational data from the Sloan Digital Sky Survey (SDSS). By employing a…
We develop an analytic halo model for the distribution of dust around galaxies. The model results are compared with the observed surface dust density profile measured through reddening of background quasars in the Sloan Digital Sky Survey…
It is not straightforward to determine the distribution of supernova remnants (SNRs) in the Galaxy. The two main difficulties are that there are observational selection effects that mean that catalogues of SNRs are incomplete, and distances…
In this paper, we present an overview of Nearest neighbor (NN) methods, which are frequently employed for solving classification problems using supervised learning. The article concisely introduces the theoretical background, algorithmic,…