Hierarchical generative models for star clusters from hydrodynamical simulations

Stefano Torniamenti, Mario Pasquato, Pierfrancesco Di Cintio, Alessandro Ballone, Giuliano Iorio, M. Celeste Artale, Michela Mapelli

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Star formation in molecular clouds is clumpy, hierarchically subclustered. Fractal structure also emerges in hydrodynamical simulations of star-forming clouds. Simulating the formation of realistic star clusters with hydrodynamical simulations is a computational challenge, considering that only the statistically averaged results of large batches of simulations are reliable, due to the chaotic nature of the gravitational N-body problem. While large sets of initial conditions for N-body runs can be produced by hydrodynamical simulations of star formation, this is prohibitively expensive in terms of computational time. Here, we address this issue by introducing a new technique for generating many sets of new initial conditions from a given set of star masses, positions, and velocities from a hydrodynamical simulation. We use hierarchical clustering in phase space to inform a tree representation of the spatial and kinematic relations between stars. This constitutes the basis for the random generation of new sets of stars which share the clustering structure of the original ones but have individually different masses, positions, and velocities. We apply this method to the output of a number of hydrodynamical star-formation simulations, comparing the generated initial conditions to the original ones through a series of quantitative tests, including comparing mass and velocity distributions and fractal dimension. Finally, we evolve both the original and the generated star clusters using a direct N-body code, obtaining a qualitatively similar evolution.

Original languageEnglish
Pages (from-to)2097-2110
Number of pages14
JournalMonthly Notices of the Royal Astronomical Society
Issue number2
Publication statusPublished - Feb 2022
Externally publishedYes


  • ISM: clouds
  • ISM: kinematics and dynamics
  • methods: numerical
  • methods: statistical
  • open clusters and associations: general

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science


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