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A machine learning-based method for populating dark matter halos in N-body simulations with substructure
Dark matter N-body simulations that resolve halo substructure (subhalos) with high accuracy can be used for generating reliable catalogs of central and satellite galaxies via galaxy-halo connection models. However, such simulations are computationally expensive, especially when large numbers of real
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