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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.
No transcript available for this episode.

StarXiv: a podcast discussing the latest astronomy papers

StarXiv: a podcast discussing the latest astronomy papers

StarXiv: a podcast discussing the latest astronomy papers