Move over neural networks! – A new method for cosmological inference
Should neural networks give up trying to model cosmology and stick to sorting cat photos? Find out in todays post!
Should neural networks give up trying to model cosmology and stick to sorting cat photos? Find out in todays post!
If dark matter did not exist, the visible matter in the universe should be able to explain all gravitational phenomena. But can it?
In which cosmologists come up with yet another way to ignore pesky systematics – aka astrophysics!
Tide goes in, dark matter halos come out, today’s authors can simulate that! With separate universe simulations!
Galaxy clusters act like cosmic telescopes, magnifying our view of the universe. These exceptionally massive structures allow astronomers to gaze deep into the cosmos and study galaxies during early ages of the universe in fantastic detail. With the completion of the Frontier Fields survey, we can now study a population of magnified, distant galaxies like never before.
Gravitational waves have been used to measure the Hubble constant before, but the uncertainties were too large to provide competitive constraints. However, using lensed gravitational wave events could be a game-changer.