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!
Using a Random Forest to Classify ASAS-SN Variable Stars
ASAS-SN searches for supernova and finds variable stars too! They found so many (~90,000) that they decided to classify them all. How do you go about classifying 90,000 things? Machine learning, of course!
Never underestimate a droid: deep learning for turbulence
Can we teach a machine to reproduce the physics of turbulence? An exploration of using deep learning to simulate magnetohydrodynamic turbulence!
Galaxy collisions and star-formation: a surprising causal examination
The longstanding role of galaxy mergers as drivers of star-formation is brought into question
Ghosts of Spiral Arms Past
A study of star clusters in the Milky Way has uncovered a peculiar trend in the way they are arranged.
Is That a Supernova? Classifying Transients in Real-Time with Machine Learning
A neural network enables transient classification with ongoing observations, potentially providing astronomers with more time to study the transient while it is still occurring.