Related papers: Rotation Invariant Descriptors for Galaxy Morpholo…

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…

Based on the recent advancements in the numerical simulations of galaxy formation, we anticipate the achievement of realistic models of galaxies in the near future. Morphology is the most basic and fundamental property of galaxies, yet…

This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute…

It has recently been demonstrated that one can accurately derive galaxy morphology from particular primary and secondary isophotal shape estimates in the Sloan Digital Sky Survey imaging catalog. This was accomplished by applying Machine…

Deep neural networks (DNNs) with a step-by-step introduction of inputs, which is constructed by imitating the somatosensory system in human body, known as SpinalNet have been implemented in this work on a Galaxy Zoo dataset. The input…

Variations in the photometric parameters of stellar systems as a function of their evolution and the stellar populations comprising them are investigated. A set of seven evolutionary models with an exponential decrease in the star-formation…

We applied the image-based approach with a convolutional neural network model to the sample of low-redshifts galaxies with $-24^{m}<M_{r}<-19.4^{m}$ from the SDSS DR9. We divided it into two subsamples, SDSS DR9 galaxy dataset and Galaxy…

This paper analyzes the robustness of recent 3D shape descriptors to SO(3) rotations, something that is fundamental to shape modeling. Specifically, we formulate the task of rotated 3D object instance detection. To do so, we consider a…

Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in…

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…

The abundance of galaxy clusters as a function of mass is determined using the 2dFGRS Percolation-Inferred Galaxy Group (2PIGG) catalogue. This is used to estimate the amplitude of the matter fluctuation spectrum, parametrised by the linear…

We are carrying out a programme to measure the evolution of the stellar and dynamical masses and M/L ratios for a sizeable sample of morphologically-classified disk galaxies in rich galaxy clusters at 0.2<z<0.9. Using FORS2 at the VLT we…

Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual…

The rotation curves of 20 spiral galaxies are examined in the light of a toy model (Soares 1992) which has as the main feature the assignment of a high M/L ratio (=30; Ho=50 km/s/Mpc) to the visible matter. The observed rotation of all…

We present a study of galaxies in the Abell 901/902 Supercluster at z~0.165, based on HST ACS F606W, COMBO-17, Spitzer 24um, XMM-Newton X-ray, and gravitational lensing maps, as part of the STAGES survey. We characterize galaxies with…

In this paper, we develop a new gravitational lensing inversion technique. While traditional approaches assume that the lensing field varies little across a galaxy image, we note that this variation in the field can give rise to a…

Successful point cloud registration relies on accurate correspondences established upon powerful descriptors. However, existing neural descriptors either leverage a rotation-variant backbone whose performance declines under large rotations,…

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited…

Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as…

The studies of the evolution of galaxies in Galaxy Clusters have as a traditional complication the difficulty in establishing cluster membership of those sources detected in the field of view. The determination of spectroscopic redshifts…