Can fake data help to make real computational gains? In today’s paper, the authors describe using machine learning to boost the resolution of cosmological simulations.
Today’s paper proposes a machine learning method to recover fundamental cosmological parameters directly from sky maps. Will gastrophysics get in the way?
In the latest of our #UndergradResearch series, discover how Lucia Volkova has been working with PICO to improve bubble chambers, one possible way to detect dark matter.
Cosmic magnetic fields are everywhere, but we don’t know where they came from. Today’s paper looks at simulations of the earliest fields in the Universe to try to solve this magnetic mystery.
Today’s classic paper predicts the formation of “cosmic pancakes” on the largest scales.
Studying gravity on cosmological scales is HARD. Today’s papers build a framework to extend the standard cosmology toolbox, which means we can keep more of our data and learn more about gravity in the process.