Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes

HIGHLIGHTS

• who: Moews Ben and collaborators from the Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh , HJ, UK have published the research: Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes, in the Journal: (JOURNAL)
• what: The authors explore the merging of an extended version of the equilibrium model an analytic formalism describing the evolution of the stellar than the analytic formalism alone can provide creating a high-speed hydrodynamic simulation emulator that populates galactic dark matter haloes in N-body simulations with baryonic properties. The authors demonstrate that this novel . . .
  

   

  

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