Related papers: Unsupervised Classification of Galaxies. I. ICA fe…
Accurate measurement of galaxy structures is a prerequisite for quantitative investigation of galaxy properties or evolution. Yet, the impact of galaxy inclination and dust on commonly used metrics of galaxy structure is poorly quantified.…
We present a galaxy classification system for 238 (E1-Sdm) CALIFA (Calar Alto Legacy Integral Field Area) galaxies based on the shapes and amplitudes of their circular velocity curves (CVCs). We infer the CVCs from the de-projected surface…
In the independent component model, the multivariate data is assumed to be a mixture of mutually independent latent components, and in independent component analysis (ICA) the aim is to estimate these latent components. In this paper we…
We present the results of an isophotal shape analysis of three samples of galaxies in the Coma cluster. Quantitative morphology, together with structural and photometric parameters, is given for each galaxy. Special emphasis has been placed…
Using 8 telescopes in the northern and southern hemispheres, plus archival data from two on-line sky surveys, we performed a systematic optical spectroscopic study of 39 putative counterparts of unidentified or poorly studied INTEGRAL…
Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative…
With the aim of constructing accurate 2D maps of the stellar mass distribution in nearby galaxies from S4G 3.6 and 4.5 micron images, we report on the separation of the light from old stars from the emission contributed by contaminants…
Isolated galaxies have not been a hot topic over the past four decades. This is partly due to uncertainties about their existence. Are there galaxies isolated enough to be interesting? Do they exist in sufficient numbers to be statistically…
Galaxy intrinsic alignment (IA) is both a source of systematic contamination to cosmic shear measurement and its cosmological applications, and a source of valuable information on the large scale structure of the universe and galaxy…
Independent component analysis (ICA) is a fundamental data processing technique to decompose the captured signals into as independent as possible components. Computing the contrast function, which serves as a measure of independence of…
We have developed a web tool to perform Principal Component Analysis (PCA, Murtagh & Heck 1987; Kendall 1980) onto spectral data. The method is especially designed to perform spectral classification of galaxies from a sample of input…
During the last ten years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric datasets…
We present a systematical analysis of the Chandra observations of 53 nearby highly-inclined (i>60 degree) disk galaxies to study the coronae around them. This sample covers a broad range of galaxy properties: e.g., about three orders of…
The structural parameters of bulges, disks and bars of a sample of nearly 1000 nearby galaxies are being determined through sophisticated image decomposition in the g, r and i bands. The sample is carefully drawn from the Sloan Digital Sky…
Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. In this paper we construct a new nonlinear ICA model, called WICA, which obtains better and more stable results than…
This paper presents the first of two analyses about the influence of environment on the formation and evolution of galaxies observed in the nearby universe. For our study, we used three different samples representing different density…
The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means…
The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several million celestial sources. In the case of variable stars, supervised learning…
The distribution of global photometric, spectroscopic, structural and morphological parameters for a well defined sample of 350 nearby galaxies has been examined. The usual trends were recovered demonstrating that E/S0 galaxies are redder,…
The Carnegie-Irvine Galaxy Survey (CGS) is a comprehensive investigation of the physical properties of a complete, representative sample of 605 bright (B_T <= 12.9 mag) galaxies in the southern hemisphere. This contribution describes the…