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Convolutional Deep Denoising Autoencoders for Radio Astronomical Images
We apply a Machine Learning technique known as Convolutional Denoising Autoencoder to denoise synthetic images of state-of-the-art radio telescopes, with the goal of detecting the faint, diffused radio sources predicted to characterise the radio cosmic web.
On the alignment of haloes, filaments and magnetic fields in the simulated cosmic web
The continuous flow of gas and dark matter across scales in the cosmic web can generate correlated dynamical properties of haloes and filaments (and the magnetic fields they contain).
Cosmology and Nongalactic Astrophysics
A New View of Observed Galaxies through 3D Modelling and Visualisation
Observational astronomers survey the sky in great detail to gain a better understanding of many types of astronomical phenomena.
Instrumentation and Methods for Astrophysics Graphics
