The Astrophysical Journal (Jan 2024)

Hierarchical Structure and Self-gravity in the Maddalena Giant Molecular Cloud

  • Renjie Shen,
  • Yuehui Ma,
  • Hongchi Wang,
  • Suziye He,
  • Miaomiao Zhang

DOI
https://doi.org/10.3847/1538-4357/ad5347
Journal volume & issue
Vol. 971, no. 1
p. 14

Abstract

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In this work, we present data from the Milky Way Imaging Scroll Painting project for the Maddalena giant molecular cloud (GMC). We decompose the ^13 CO emission datacube of the observed region into hierarchical substructures using a modified dendrogram algorithm. We investigate the statistical properties of these substructures and examine the role that self-gravity plays on various spatial scales. The statistics of the mass ( M ), radius ( R ), velocity dispersion ( σ _v ), virial parameter ( α _vir ), and sonic Mach number of the substructures are presented. The radius and mass distributions and the σ _v –R scaling relationship of the substructures resemble those reported in previous studies that use nonhierarchical algorithms to identify the entities. We find that for the hierarchical substructures α _vir decreases as the radius or mass of the substructures increases. The majority of the substructures in the quiescent region of the Maddalena GMC are not gravitationally bound ( α _vir > 2), while most of the substructures in the star-forming regions are gravitationally bound ( α _vir < 2). Furthermore, we find that self-gravity plays an important role on scales of 0.8–4 pc in the IRAS 06453 star-forming region, while it is not an important factor on scales below 5 pc in the non-star-forming region.

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