Related papers: Comparison of Observed Galaxy Properties with Semi…
Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…
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…
Large photometric surveys will image billions of galaxies, but we currently lack quick, reliable automated ways to infer their physical properties like morphology, stellar mass, and star formation rates. Simulations provide galaxy images…
Supervised artificial neural networks are used to predict useful properties of galaxies in the Sloan Digital Sky Survey, in this instance morphological classifications, spectral types and redshifts. By giving the trained networks unseen…
We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…
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…
The matter environment of galaxies is connected to the physics of galaxy formation and evolution. Utilising galaxy-galaxy-galaxy lensing as a direct probe, we map out the distribution of correlated surface mass-density around galaxy pairs…
We study the consistency of the physical properties of galaxies retrieved from SED-fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection of physically motivated star formation histories, we set up a…
A significant fraction of high redshift star-forming disc galaxies are known to host giant clumps, whose nature and role in galaxy evolution are yet to be understood. In this work we first present a new method based on neural networks to…
Low surface brightness substructures around galaxies, known as tidal features, are a valuable tool in the detection of past or ongoing galaxy mergers, and their properties can answer questions about the progenitor galaxies involved in the…
Galaxy models predict a tight relation between the clustering of galaxies and dark matter on cosmological scales, but predictions differ notably in the details. We used this opportunity and tested two semi-analytic models by the Munich and…
We compare the stellar masses of central and satellite galaxies predicted by three independent semianalytical models with observational results obtained from a large galaxy group catalogue constructed from the Sloan Digital Sky Survey. In…
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…
The shear measurement from DECaLS (Dark Energy Camera Legacy Survey) provides an excellent opportunity for galaxy-galaxy lensing study with DESI (Dark Energy Spectroscopic Instrument) galaxies, given the large ($\sim 9000$ deg$^2$) sky…
We use the combined GALFORM semi-analytical model of galaxy formation and GRASIL spectrophotometric code to investigate the properties of galaxies selected via their sub-mm emission. Our fiducial model has previously been shown to fit the…
Shear estimation bias from galaxy detection and blending identification is now recognized as an issue for ongoing and future weak lensing surveys. Currently, the empirical approach to correcting for this bias involves numerically shearing…
We compare the properties of local spiral galaxies with the predictions of the Cole et al. semi-analytic model of hierarchical galaxy formation, in order to gain insight into the baryonic processes that were responsible for shaping these…
The results of morphological galaxy classifications performed by humans and by automated methods are compared. In particular, a comparison is made between the eyeball classifications of 454 galaxies in the Sloan Digital Sky Survey (SDSS)…
We use semi-analytic models of galaxy formation combined with high resolution N-body simulations to make predictions for galaxy-dark matter correlations and apply them to galaxy-galaxy lensing. We analyze cross-correlation spectra between…
Upcoming large galaxy surveys will subject the standard cosmological model, $\Lambda$CDM, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering…