AI and the World's Hard Problems · Astronomy & space · arXiv · 2026-10-23
A neural-network model to find correlations in astrochemical space
Detecting new interstellar molecules is central to astrochemistry. The authors built a machine-learning pipeline that links chemical strings of molecular structures to column densities in TMC-1, using a neural network to predict those densities for both known and out-of-distribution molecules. The learned latent vectors point to several promising candidates for future detection in the cloud.