3 papers
astro-ph.GA2026
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…
astro-ph.GA2026
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…
astro-ph.GA2026
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…