A Robust Study of High-redshift Galaxies: Unsupervised Machine Learning for Characterizing Morphology with JWST up to z ∼ 8

A Robust Study of High-redshift Galaxies: Unsupervised Machine Learning for Characterizing Morphology with JWST up to z ∼ 8

Galaxy morphologies provide valuable insights into their formation processes, tracing the spatial distribution of ongoing star formation and encoding signatures of dynamical interactions. While such information has been extensively investigated at low redshift, it is crucial to develop a robust syst...

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Bibliographic Details
Main Authors: C. Tohill, S. P. Bamford, C. J. Conselice, L. Ferreira, T. Harvey, N. Adams, D. Austin
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:The Astrophysical Journal
Subjects:
Galaxy evolution
Convolutional neural networks
High-redshift galaxies
Galaxy classification systems
Online Access:https://doi.org/10.3847/1538-4357/ad17b8

Internet

https://doi.org/10.3847/1538-4357/ad17b8

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