Related papers: Galaxy classification: A machine learning analysis…
Several semi-analytic models (SAMs) try to explain how galaxies form, evolve and interact inside the dark matter large-scale structure. These SAMs can be tested by comparing their predictions for galaxy-galaxy-galaxy-lensing (G3L), which is…
We constrain the distributions of projected radial alignment angles of satellite galaxy shapes within the Galaxy And Mass Assembly survey group catalogue. We identify the galaxy groups using spectroscopic redshifts and measure galaxy…
We investigate the contentious issue of the presence, or lack thereof, of satellites mass segregation in galaxy groups using the Galaxy And Mass Assembly (GAMA) survey, the GALFORM semi-analytic and the EAGLE cosmological hydrodynamical…
The Galaxy And Mass Assembly Survey (GAMA) has now been operating for almost 5 years gathering spectroscopic redshifts for five regions of sky spanning 300 sq degrees in total to a depth of r<19.8 mag. The survey has amassed over 225,000…
We investigate the relationship between colour and structure within galaxies using a large, volume-limited sample of bright, low-redshift galaxies with optical to near-infrared imaging from the GAMA survey. We fit single-component,…
The taxonomy of galaxy morphology is critical in astrophysics as the morphological properties are powerful tracers of galaxy evolution. With the upcoming Large-scale Imaging Surveys, billions of galaxy images challenge astronomers to…
The GAMA survey aims to deliver 250,000 optical spectra (3--7Ang resolution) over 250 sq. degrees to spectroscopic limits of r_{AB} <19.8 and K_{AB}<17.0 mag. Complementary imaging will be provided by GALEX, VST, UKIRT, VISTA, HERSCHEL and…
We report the morphological classification of 3727 galaxies from the Galaxy and Mass Assembly survey with M_r < -17.4 mag and in the redshift range 0.025 < z < 0.06 (2.1 x 10^5 Mpc^3 ) into E, S0-Sa, SB0-SBa, Sab-Scd, SBab-SBcd, Sd-Irr and…
We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural…
This paper presents machine learning experiments performed over results of galaxy classification into elliptical (E) and spiral (S) with morphological parameters: concetration (CN), assimetry metrics (A3), smoothness metrics (S3), entropy…
Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their…
We present a metric to quantify systematic labeling bias in galaxy morphology data sets stemming from the quality of the labeled data. This labeling bias is independent from labeling errors and requires knowledge about the intrinsic…
We study how the sizes and radial profiles of galaxies vary with wavelength, by fitting Sersic functions simultaneously to imaging in nine optical and near-infrared bands. To quantify the wavelength dependence of effective radius we use the…
In this paper we aim to (i) test the number of statistically distinct classes required to classify the local galaxy population, and, (ii) identify the differences in the physical and star formation properties of visually-distinct galaxies.…
Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any…
This paper describes the first catalogue of photometrically-derived stellar mass estimates for intermediate-redshift (z < 0.65) galaxies in the Galaxy And Mass Assembly (GAMA) spectroscopic redshift survey. These masses, as well as the full…
We present a maximum-likelihood weak lensing analysis of the mass distribution in optically selected spectroscopic Galaxy Groups (G$^3$Cv5) in the Galaxy And Mass Assembly (GAMA) survey, using background Sloan Digital Sky Survey (SDSS)…
In order to help facilitate the future study of ultra-diffuse galaxies (UDGs) we compile a catalogue of their spectroscopic properties. Using it, we investigate some of the biases inherent in the current UDG sample that have been targeted…
Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…
The GAMA survey has now completed its spectroscopic campaign of over 250,000 galaxies ($r<19.8$mag), and will shortly complete the assimilation of the complementary panchromatic imaging data from GALEX, VST, VISTA, WISE, and Herschel. In…