Related papers: Morphology-assisted galaxy mass-to-light predictio…
We present a machine learning (ML) approach for the prediction of galaxies' dark matter halo masses that achieves an improved performance over conventional methods. We train three ML algorithms (\texttt{XGBoost}, Random Forests, and neural…
We study the influence of the environment on the evolution of galaxies by investigating the luminosity function (LF) of galaxies of different morphological types and colours at different environmental density levels. We construct the LFs…
In this paper we explore a quantitative and efficient method to constrain the halo properties of distant galaxy populations through ``galaxy--galaxy" lensing and show that the mean masses and sizes of halos can be estimated accurately,…
Our goal is to morphologically classify the sources identified in the images of the J-PLUS early data release (EDR) into compact (stars) or extended (galaxies) using a suited Bayesian classifier. J-PLUS sources exhibit two distinct…
The classification of galaxy morphology plays a crucial role in understanding galaxy formation and evolution. Traditionally, this process is done manually. The emergence of deep learning techniques has given room for the automation of this…
We discuss the state of the assembly of the Hubble Sequence in the mix of bright galaxies at redshift 1.4< z \le 2.5 with a large sample of 1,671 galaxies down to H_{AB}~26, selected from the HST/ACS and WFC3 images of the GOODS--South…
We present a new non-parametric method to quantify morphologies of galaxies based on a particular family of learning machines called support vector machines. The method, that can be seen as a generalization of the classical CAS…
This paper demonstrates that the stellar masses of galaxies in the Galaxy and Mass Assembly (GAMA) survey, originally derived via stellar population synthesis modelling, can be accurately predicted using only their absolute magnitudes and…
Bulge-disc decomposition is a valuable tool for understanding galaxies. However, achieving robust measurements of component properties is difficult, even with high quality imaging, and it becomes even more so with the imaging typical of…
Estimating physical properties of galaxies from wide-field surveys remains a central challenge in astrophysics. While spectroscopy provides precise measurements, it is observationally expensive, and photometry discards morphological…
Using the galaxy data of the Sloan Digital Sky Survey Data Release 8 (SDSS DR8), I explore whether the concentration index is a good morphological classification tool and find that a reasonably pure late-type galaxy sample can be…
Galaxy morphologies play an essential role in the study of the evolution of galaxies. The determination of morphologies is laborious for a large amount of data giving rise to machine learning-based approaches. Unfortunately, most of these…
Recent work has suggested that mid-IR wavelengths are optimal for estimating the mass-to-light ratios of stellar populations and hence the stellar masses of galaxies. We compare stellar masses deduced from spectral energy distribution (SED)…
We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal…
We introduce a new technique based on artificial neural networks which allows us to make accurate predictions for the spectral energy distributions (SEDs) of large samples of galaxies, at wavelengths ranging from the far-ultra-violet to the…
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…
We investigate colors and mass-to-light ratios ($M/L$s) of the bulges and disks for 28 nearby spiral galaxies with various morphological types of Sab to Scd, using images in optical and near-infrared ($V$, $I$, and $J$) bands and published…
The pace at which galaxies grew into their current stellar masses and how this growth is regulated is still not fully understood, nor is the role that morphology plays in this process. We applied full spectral fitting techniques with…
Automating classification of galaxy components is important for understanding the formation and evolution of galaxies. Traditionally, only the larger galaxy structures such as the spiral arms, bulge, and disc are classified. Here we use…
(Abridged) We compared the quantified morphological properties of 37 intermediate redshift MgII absorption selected galaxies to the properties of the absorbing halo gas, observed in the spectra of background quasars. The galaxy morphologies…