Episode 30 - Direct collapse black holes, nuclear stellar discs, and machine learning merger histories

In this episode, Payel and Nicole delve into more JWST discoveries and the frontier of machine learning in astronomy - an ultra-deep view of the cosmic web, machine-learning deep images to look for mergers, a direct collapse black hole explanation to Little Red Dots, machine-learning the Milky Way to reveal complex star formation histories of accreted systems, and the earliest nuclear stellar disc observed to date. Check out the papers below.

An ultra-high-resolution map of (dark) matter - Diana Scognamiglio et al.

Convolutional Neural Networks for classifying galaxy mergers: Can faint tidal features aid in classifying mergers? - Yeonkyung Lee et al.

The Little Red Dots Are Direct Collapse Black Holes - Fabio Pacucci et al.

Two faces of Gaia-Sausage-Enceladus: Mining the chemical abundance space with graph attention networks - Milan Quandt-Rodriguez et al.

A nuclear disc at Cosmic Noon: evidence of early bar-driven galaxy evolution - Zoe A. Le Conte et al.