相关论文: Galaxies in the zone of avoidance: Misclassificati…

High-accuracy HI profiles and linewidths are presented for inclined ($(b/a)^o < 0.5$) spiral galaxies in the southern Zone of Avoidance (ZOA). These galaxies define a sample for use in the determinations of peculiar velocities using the…

We present a new method to classify galaxies from large surveys like the Sloan Digital Sky Survey using inclination-corrected concentration, inclination-corrected location on the color-magnitude diagram, and apparent axis ratio. Explicitly…

Context. The ZOA does not allow clear optical observations of extragalactic sources behind the Milky Way due to the meaningful extinction of the optical emission of these objects. The observations in NIR wavelengths represent a potential…

We use mid-infrared variability in galaxies to search for active galactic nuclei (AGN) in the local universe. We use a sample of 10,220 galaxies from the Mapping Nearby Galaxies at APO (MaNGA) survey, part of the Sloan Digital Sky Survey…

This study utilizes unsupervised machine learning, specifically the uniform manifold approximation and projection (UMAP) algorithm, to classify optical spectra originating from star-forming regions, Seyferts, and low-ionization (nuclear)…

The morphological classification of galaxies provides vital physical information about the orbital motions of stars in galaxies, and correlates in interesting ways with star formation history, and other physical properties. Galaxy…

Context. The accurate classification of hundreds of thousands of galaxies observed in modern deep surveys is imperative if we want to understand the universe and its evolution. Aims. Here, we report the use of machine learning techniques to…

Galaxy groups provide the means for a great diversity of studies that contribute to a better understanding of the structure of the universe on a large scale and allow the properties of galaxies to be linked to those of the host halos.…

Galaxy edges or truncations are low-surface-brightness (LSB) features located in the galaxy outskirts that delimit the distance up to where the gas density enables efficient star formation. As such, they could be interpreted as a…

Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…

We present a new analysis of the Sloan Digital Sky Survey data aimed at producing a detailed map of the nearby (z < 0.5) universe. Using neural networks trained on the available spectroscopic base of knowledge we derived distance estimates…

Extensive astronomical surveys, like those conducted with the {\em Chandra} X-ray Observatory, detect hundreds of thousands of unidentified cosmic sources. Machine learning (ML) methods offer an efficient, probabilistic approach to classify…

MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a SDSS-IV survey that will obtain spatially resolved spectroscopy from 3600 \AA\ to 10300 \AA\ for a representative sample of over 10000 nearby galaxies. In this paper we…

The HI Parkes Zone of Avoidance Survey is a 21 cm blind search with the multibeam receiver on the 64-m radiotelescope, looking for galaxies hidden behind the southern Milky Way. The first, shallow (15 mJy rms) phase of the survey has…

The Laniakea Supercluster is the closest large scale structure of galaxies. Is such a structure expected in the standard cold dark matter model of cosmology? This would be a relatively simple question to answer, were it not for the fact…

Increasingly large areas in cosmic shear surveys lead to a reduction of statistical errors, necessitating to control systematic errors increasingly better. One of these systematic effects was initially studied by Hartlap et al. in 2011,…

We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to train an optimised random forest classifier using photometry from the SDSS and the Widefield Infrared Survey Explorer (WISE). We applied this…

We investigate the extent to which supervised machine learning techniques can distinguish between neutron-star matter models using macroscopic and oscillation-related quantities derived from theoretical stellar configurations. Four…

We consider the problem of determining the host galaxies of radio sources by cross-identification. This has traditionally been done manually, which will be intractable for wide-area radio surveys like the Evolutionary Map of the Universe…

The purpose of this review is to discuss the advantages and problems of near-infrared surveys in observing pulsating stars in the Milky Way. One of the advantages of near-infrared surveys, when compared to optical counterparts, is that the…