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

Authors :
Shen, Renjie
Ma, Yuehui
Wang, Hongchi
He, Suziye
Zhang, Miaomiao
Publication Year :
2024

Abstract

In this work, we present the data from the Milky Way Imaging Scroll Painting (MWISP) 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 ({\sigma}v), virial parameter ({\alpha}vir), and sonic Mach number of the substructures are presented. The radius and mass distributions and the {\sigma}v-R scaling relationship of the substructures resemble those reported in previous studies that use non-hierarchical algorithms to identify the entities. We find that for the hierarchical substructures {\alpha}vir decreases as the radius or mass of the substructures increases. The majority of the substructures in the quiescent region of Maddalena GMC are not gravitationally bound ({\alpha}vir > 2), while most of the substructures in the star-forming regions are gravitationally bound ({\alpha}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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2405.19766
Document Type :
Working Paper