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Classifying galaxies according to their H I content
(Oxford University Press, 2020)
We use machine learning to classify galaxies according to their H I content, based on both their optical photometry and environmental properties. The data used for our analyses are the outputs in the range z = 0–1 from ...
Testing galaxy formation simulations with damped Lyman-α abundance and metallicity evolution
(Oxford University Press, 2020)
We examine the properties of damped Lyman-α absorbers (DLAs) emerging from a single set of cosmological initial conditions in two state-of-the-art cosmological hydrodynamic simulations: SIMBA and TECHNICOLOR DAWN. The ...
The impact of quenching on galaxy profiles in the SIMBA simulation
(Oxford University Press, 2020)
We study specific star formation rate (sSFR) and gas profiles of star-forming (SF) and green valley (GV) galaxies in the SIMBA cosmological hydrodynamic simulation. SF galaxy half-light radii (Rhalf) at z = 0 and their ...
Photometric properties of reionization-epoch galaxies in the SIMBA simulations
(Oxford University Press, 2020)
We study the photometric properties and sizes of the reionization-epoch galaxies in high-resolution SIMBA cosmological hydrodynamical simulations with box sizes of [25,50]h−1Mpc. Assuming various attenuation laws, we ...