From the 1 of 3 linked papers with an AI index.
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Identifying backsplash galaxies using machine learning
Roan Haggar, Elizaveta Sazonova, Cameron R. Morgan +5
The paper presents a machine‑learning model trained on The Three Hundred cluster simulations that can identify backsplash galaxies in observations, achieving about 70% purity/compl…
Comparison and verification methods to trace interaction-driven disturbances in galaxies
Haotian Lyu, Sarah Brough, Aman Khalid +2
Low surface brightness tidal debris around galaxies, such as tails, streams, and shells, together with other interaction-driven morphological disturbances, serve as valuable indica…
The Hubble sequence in JWST CEERS from unbiased galaxy morphologies
Elizaveta Sazonova, Cameron R. Morgan, Michael Balogh
Whether the "Hubble sequence" of galaxy morphologies exists up to z~4 is still disputed, and one of the challenges is characterizing galaxy structure consistently across a wide ran…