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Predicting the neutral hydrogen content of galaxies from optical data using machine learning
(Oxford University Press, 2018)
We develop a machine learning-based framework to predict the Hi content of galaxies using
more straightforwardly observable quantities such as optical photometry and environmental
parameters. We train the algorithm on z ...
Aligned metal absorbers and the ultraviolet background at the end of reionization
(Oxford University Press, 2018)
We use observations of spatially-aligned C ii, C iv, Si ii, Si iv, and O i absorbers to probe the
slope and intensity of the ultraviolet background (UVB) at z ∼ 6. We accom- plish this by comparing
observations with ...