The scatter in the galaxy-halo connection: a machine learning analysis
We apply machine learning (ML), a powerful method for uncovering complex correlations in high-dimensional data, to the galaxy-halo connection of cosmological hydrodynamical simulations. The mapping between galaxy and halo variables is stochastic in the absence of perfect information, but conventiona...
主要な著者: | Stiskalek, R, Bartlett, DJ, Desmond, H, Anbajagane, D |
---|---|
フォーマット: | Journal article |
言語: | English |
出版事項: |
Oxford University Press
2022
|
類似資料
-
Baryonic Imprints on DM Halos: the concentration-mass relation and its dependence on halo and galaxy properties
著者:: Mufan Shao, 等
出版事項: (2024-04-01) -
On the galaxy–halo connection in the EAGLE simulation
著者:: Desmond, H, 等
出版事項: (2017) -
Revealing the Galaxy–Halo Connection through Machine Learning
著者:: Ryan Hausen, 等
出版事項: (2023-01-01) -
Evaluating the reconstruction of individual haloes in constrained cosmological simulations
著者:: Stiskalek, R, 等
出版事項: (2023) -
Revealing the galaxy–halo connection in IllustrisTNG
著者:: Bose, Sownak, 等
出版事項: (2022)