A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations

L Zanisi, M Huertas-Company… - Monthly Notices of …, 2021 - academic.oup.com
Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the
physics that shapes galaxies. The agreement between the morphology of simulated and real …

Deep generative models for galaxy image simulations

F Lanusse, R Mandelbaum… - Monthly Notices of …, 2021 - academic.oup.com
Image simulations are essential tools for preparing and validating the analysis of current and
future wide-field optical surveys. However, the galaxy models used as the basis for these …

What shapes a galaxy?–unraveling the role of mass, environment, and star formation in forming galactic structure

AFL Bluck, C Bottrell, H Teimoorinia… - Monthly Notices of …, 2019 - academic.oup.com
We investigate the dependence of galaxy structure on a variety of galactic and
environmental parameters for∼ 500 000 galaxies at z< 0.2, taken from the Sloan Digital Sky …

The Hubble Sequence at z ∼ 0 in the IllustrisTNG simulation with deep learning

M Huertas-Company… - Monthly Notices of …, 2019 - academic.oup.com
We analyse the optical morphologies of galaxies in the IllustrisTNG simulation at z∼ 0 with a
convolutional neural network trained on visual morphologies in the Sloan Digital Sky …

Galaxy morphology network: A convolutional neural network used to study morphology and quenching in∼ 100,000 sdss and∼ 20,000 candels galaxies

A Ghosh, CM Urry, Z Wang, K Schawinski… - The Astrophysical …, 2020 - iopscience.iop.org
We examine morphology-separated color–mass diagrams to study the quenching of star
formation in∼ 100,000 (z∼ 0) Sloan Digital Sky Survey (SDSS) and∼ 20,000 (z∼ 1) …

Galaxy formation in semi-analytic models and cosmological hydrodynamic zoom simulations

M Hirschmann, T Naab, RS Somerville… - Monthly Notices of …, 2012 - academic.oup.com
We present a detailed comparison between numerical cosmological hydrodynamic zoom
simulations and the semi-analytic model (SAM) of Somerville et al., run within merger trees …

The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations

H Li, M Vogelsberger, F Marinacci… - Monthly Notices of …, 2020 - academic.oup.com
Recent cosmological hydrodynamical simulations are able to reproduce numerous statistical
properties of galaxies that are consistent with observational data. Yet, the adopted subgrid …

Rotation-invariant convolutional neural networks for galaxy morphology prediction

S Dieleman, KW Willett, J Dambre - Monthly notices of the royal …, 2015 - academic.oup.com
Measuring the morphological parameters of galaxies is a key requirement for studying their
formation and evolution. Surveys such as the Sloan Digital Sky Survey have resulted in the …

The star formation main sequence and stellar mass assembly of galaxies in the Illustris simulation

M Sparre, CC Hayward, V Springel… - Monthly Notices of …, 2015 - academic.oup.com
Understanding the physical processes that drive star formation is a key challenge for galaxy
formation models. In this paper, we study the tight correlation between the star formation rate …

Physical models of galaxy formation in a cosmological framework

RS Somerville, R Davé - Annual Review of Astronomy and …, 2015 - annualreviews.org
Modeling galaxy formation in a cosmological context presents one of the greatest
challenges in astrophysics today due to the vast range of scales and numerous physical …