A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations
Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed across galaxy scaling relations are important probes of our k...
Main Authors: | Zanisi, Lorenzo, Huertas-Company, Marc, Lanusse, François, Bottrell, Connor, Pillepich, Annalisa, Nelson, Dylan, Rodriguez-Gomez, Vicente, Shankar, Francesco, Hernquist, Lars, Dekel, Avishai, Margalef-Bentabol, Berta, Vogelsberger, Mark, Primack, Joel |
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Other Authors: | Massachusetts Institute of Technology. Department of Physics |
Format: | Article |
Language: | English |
Published: |
Oxford University Press (OUP)
2022
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Online Access: | https://hdl.handle.net/1721.1/142553 |
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