Related papers: Galaxy classification: A machine learning analysis…

We address the problem of morphological classification of galaxies from the Galaxy Zoo DECaLS dataset using classical machine learning techniques. Our approach employs a dimensionality reduction method followed by a classical classifier to…

Morphological classification is a key piece of information to define samples of galaxies aiming to study the large-scale structure of the universe. In essence, the challenge is to build up a robust methodology to perform a reliable…

We report on a search for new low-surface-brightness galaxies (LSBGs) using Sloan Digital Sky Survey (SDSS) data within the GAMA equatorial fields. The search method consisted of masking objects detected with SDSS photo, combining gri…

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…

The classification of galaxies as spirals or ellipticals is a crucial task in understanding their formation and evolution. With the arrival of large-scale astronomical surveys, such as the Sloan Digital Sky Survey (SDSS), astronomers now…

The Galaxy And Mass Assembly (GAMA) survey has been operating since February 2008 on the 3.9-m Anglo-Australian Telescope using the AAOmega fibre-fed spectrograph facility to acquire spectra with a resolution of R~1300 for 120,862 SDSS…

We conduct a comparison of the merging galaxy populations detected by a sample of visual identification of tidal features around galaxies as well as spectroscopically-detected close pairs of galaxies to determine whether our method of…

Here, we present a machine vision approach, combining a VAE framework with PCA, to decipher galaxy images. Using mock gri-band images from the EAGLE simulation, the VAE finds that around 35 features are needed to describe the images. Adding…

In this work, decision tree learning algorithms and fuzzy inferencing systems are applied for galaxy morphology classification. In particular, the CART, the C4.5, the Random Forest and fuzzy logic algorithms are studied and reliable…

The Galaxy And Mass Assembly (GAMA) project is the latest in a tradition of large galaxy redshift surveys, and is now underway on the 3.9m Anglo-Australian Telescope at Siding Spring Observatory. GAMA is designed to map extragalactic…

We use 80922 galaxies in the Galaxy And Mass Assembly (GAMA) survey to measure the galaxy luminosity function (LF) in different environments over the redshift range 0.04<z<0.26. The depth and size of GAMA allows us to define samples split…

Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…

We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community: star/galaxy separation, and photometric redshift…

Using single-component fits to SDSS/UKIDSS images of galaxies in the G09 region of the GAMA survey we study radial colour gradients across the galaxy population. We use the multiwavelength information provided by MegaMorph analysis of…

We use data from the Galaxy And Mass Assembly (GAMA) survey in the redshift range 0.01$<$z$<$0.1 (8399 galaxies in $g$ to $K_s$ bands) to derive the stellar mass $-$ half-light radius relations for various divisions of 'early' and…

Galaxy Zoo is an online project to classify morphological features in extra-galactic imaging surveys with public voting. In this paper, we compare the classifications made for two different surveys, the Dark Energy Spectroscopic Instrument…

Using a sample of 472 local Universe (z<0.06) galaxies in the stellar mass range 10.25 < log M*/M_sun < 10.75, we explore the variation in galaxy structure as a function of morphology and galaxy colour. Our sample of galaxies is sub-divided…

Galaxy and Mass Assembly (GAMA) is a project to study galaxy formation and evolution, combining imaging data from ultraviolet to radio with spectroscopic data from the AAOmega spectrograph on the Anglo-Australian Telescope. Using data from…

The Galaxy And Mass Assembly (GAMA) survey is a multiwavelength photometric and spectroscopic survey, using the AAOmega spectrograph on the Anglo-Australian Telescope to obtain spectra for up to ~300000 galaxies over 280 square degrees, to…

The galaxy pairwise velocity dispersion (PVD) can provide important tests of non-standard gravity and galaxy formation models. We describe measurements of the PVD of galaxies in the Galaxy and Mass Assembly (GAMA) survey as a function of…