相关论文: Galaxy Morphology Without Classification: Self Org…

We develop a methodology to use the redshift dependence of the galaxy 2-point correlation function (2pCF) across the line-of-sight, $\xi(r_{\bot})$, as a probe of cosmological parameters. The positions of galaxies in comoving Cartesian…

We present the first nonparametric morphological analysis of a set of spiral galaxies from UV to submm wavelengths. Our study is based on high-quality multi-wavelength imaging for nine well-resolved spiral galaxies from the DustPedia…

With the development of a series of Galaxy sky surveys in recent years, the observations increased rapidly, which makes the research of machine learning methods for galaxy image recognition a hot topic. Available automatic galaxy image…

To study the distribution of star formation and dust emission within nearby galaxies, we measured five morphological parameters in the 3.6 and 24 micron wave bands for 65 galaxies in the Spitzer Infrared Nearby Galaxies Survey (SINGS) and 8…

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because…

We present a catalog of morphological and color data for galaxies with $I < 25$ mag in the {\em Hubble Deep Field} (Williams et al. 1996). Galaxies have been inspected and (when possible) independently visually classified on the MDS and DDO…

From a volume limited sample of 45,542 galaxies and 6,000 groups with $z \leq 0.213$ we use an adapted minimal spanning tree algorithm to identify and classify large scale structures within the Galaxy and Mass Assembly (GAMA) survey. Using…

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…

Studies of disordered heterogeneous media and galaxy cosmology share a common goal: analyzing the distribution of particles at `microscales' to predict physical properties at `macroscales', whether for a liquid, composite material, or…

We study the optical morphology of galaxies in a large-scale hydrodynamic cosmological simulation, the EAGLE simulation. Galaxy morphologies were characterized using non-parametric statistics (Gini, $M_{20}$, Concentration and Asymmetry)…

The Cosmic Evolution Survey (COSMOS) allows for the first time a highly significant census of environments and structures up to redshift one, as well as a full morphological description of the galaxy population. In this paper we present a…

We use high-resolution maps of the molecular interstellar medium (ISM) in the centres of eighty-six nearby galaxies from the millimetre-Wave Interferometric Survey of Dark Object Masses (WISDOM) and Physics at High Angular Resolution in…

We present a model-independent method of quantifying galaxy evolution in high-resolution images, which we apply to the Hubble Deep Field (HDF). Our procedure is to k-correct all pixels belonging to the images of a complete set of bright…

Self-Organizing Map (SOM) is a promising tool for exploring large multi-dimensional data sets. It is quick and convenient to train in an unsupervised fashion and, as an outcome, it produces natural clusters of data patterns. An example of…

The most massive and luminous galaxies in the Universe serve as powerful probes to study the formation of structure, the assembly of mass, and cosmology. However, their detailed formation and evolution is still barely understood. Here we…

The galaxy data provided by COSMOS survey for 1 by 1 degree field of sky are analysed by methods of complex networks. Three galaxy samples (slices) with redshifts ranging within intervals 0.88-0.91, 0.91-0.94 and 0.94-0.97 are studied as…

We present Johnson B surface photometry for the UCM Survey galaxies. One-dimensional bulge-disk decomposition is attempted, discussing on fitting functions and computational procedures. The results from this decomposition, jointly with…

We use deep r-band photometry and Halpha rotation curves for a sample of 290 late-type spirals to model their mass distribution within the optical radius. We examine luminosity profile decompositions into bulge and disk carefully and…

We describe an image analysis supervised learning algorithm that can automatically classify galaxy images. The algorithm is first trained using a manually classified images of elliptical, spiral, and edge-on galaxies. A large set of image…

With the advent of large scale surveys the manual analysis and classification of individual radio source morphologies is rendered impossible as existing approaches do not scale. The analysis of complex morphological features in the spatial…