Adversarial Networks, Collaborative Cosmology
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.
Real (cosmological) information from simulated maps
Today’s paper proposes a machine learning method to recover fundamental cosmological parameters directly from sky maps. Will gastrophysics get in the way?
Emulating Galaxy Clusters
How a new machine learning approach to generate synthetic Sunyaev-Zeldovich maps can help constrain cosmological physics.
UR: Use of Machine Learning Techniques to Analyze Radial Velocity Data to Find Exoplanets
In the latest of our #UndergradResearch series, check out high school student Rohan Nagavardhan’s research on using computational techniques to find planets beyond our solar system!
Astrobites at AAS 238: Day 2
We report on Day 2 of the virtual summer AAS meeting.
A Peculiar Use of AI: Predicting Cosmic Velocities with Neural Networks
When studying the Universe becomes too complicated for human brains, we turn to artificial intelligence! Check out how today’s authors used a neural network to predict motions on the Universe’s largest scales