Cosmoboffins use neural networks to build dark matter maps the easy way
https://www.theregister.co.uk/2019/05/20/neural_networks_dark_matter/
Spinning up dark matter simulations is computationally expensive so a team of cosmologists are turning to AI models instead.
Generative adversarial networks or GANs are good at learning patterns from data and reproducing them in new samples. In this case, the team led by researchers from the Lawrence Berkeley National Laboratory used weak gravitational lensing maps as input to simulate more of the same images as output.
