Support vector machines trained on Renaissance simulation data identify atomic cooling halos as direct collapse black hole candidates using features including metallicity, Lyman-Werner radiation flux, and halo stellar mass.
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Identification of Candidate Halos Hosting Massive Black Hole Seeds in the $\textit{Renaissance}$ Simulations with Support Vector Machines
Support vector machines trained on Renaissance simulation data identify atomic cooling halos as direct collapse black hole candidates using features including metallicity, Lyman-Werner radiation flux, and halo stellar mass.