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

Author:

Shen RenjieORCID,Ma YuehuiORCID,Wang HongchiORCID,He SuziyeORCID,Zhang MiaomiaoORCID

Abstract

Abstract In this work, we present data from the Milky Way Imaging Scroll Painting project for the Maddalena giant molecular cloud (GMC). We decompose the 13CO 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.

Funder

National Key R&D Program of China

CAS Key Research Program of Frontier Sciences

National Natural Science Foundation of China

Publisher

American Astronomical Society

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