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

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Hauptverfasser: Shen, Renjie, Ma, Yuehui, Wang, Hongchi, He, Suziye, Zhang, Miaomiao
Format: Preprint
Veröffentlicht: 2024
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author Shen, Renjie
Ma, Yuehui
Wang, Hongchi
He, Suziye
Zhang, Miaomiao
author_facet Shen, Renjie
Ma, Yuehui
Wang, Hongchi
He, Suziye
Zhang, Miaomiao
contents 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 (σv), virial parameter (αvir), and sonic Mach number of the substructures are presented. The radius and mass distributions and the σv-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 αvir 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 (αvir > 2), while most of the substructures in the star-forming regions are gravitationally bound (αvir < 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.
format Preprint
id arxiv_https___arxiv_org_abs_2405_19766
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hierarchical Structure and Self-gravity in the Maddalena Giant Molecular Cloud
Shen, Renjie
Ma, Yuehui
Wang, Hongchi
He, Suziye
Zhang, Miaomiao
Astrophysics of Galaxies
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 (σv), virial parameter (αvir), and sonic Mach number of the substructures are presented. The radius and mass distributions and the σv-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 αvir 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 (αvir > 2), while most of the substructures in the star-forming regions are gravitationally bound (αvir < 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.
title Hierarchical Structure and Self-gravity in the Maddalena Giant Molecular Cloud
topic Astrophysics of Galaxies
url https://arxiv.org/abs/2405.19766