Bars formed in galaxy merging and their classification with deep learning

M. K. Cavanagh, K. Bekki

Astronomy and Astrophysics 2020 article cited by 29

importance 3/10 ai assisted Galaxies: Formation, Evolution, Phenomena astronomy research stage: research

Astronomers lacked understanding of how stellar bars form in galaxy merging and whether barred galaxies can be classified by their formation mechanism.

Understanding bar formation mechanisms sheds light on galaxy evolution and structure.

A convolutional neural network was trained on 29,400 images from N-body simulations to distinguish barred from non-barred galaxies and test classification of barred spirals by formation mechanism.

not stated in source

Deep learning was applied to simulated galaxy classification, but the abstract states no accuracy or findings.

Venue Astronomy and Astrophysics
Published 2020
Work type article
Authors M. K. Cavanagh, K. Bekki
Citations 29 (OpenAlex, at import time)
References 82
Model or method convolutional neural network (CNN)
Organization not stated in source
Primary source https://doi.org/10.1051/0004-6361/202037963
Open access bronze
Keywords deep learning, CNN, galaxy bars, galaxy merging, N-body simulations, classification
3 / 10

incremental / niche

Bar formation sheds light on galaxy evolution and structure; abstract frames it as an open astrophysics question, with no stated beneficiaries or scale.

Basis: inferred. Judged from the source text, which gives no explicit scale. Stated scale: not stated in source. Method and limits.

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