Modelling the structure of molecular clouds – I. A multiscale energy equipartition

Veltchev, Todor V.; Donkov, Sava; Klessen, Ralf S.

doi:10.1093/mnras/stw781

Cited by 14 publications

(12 citation statements)

References 62 publications

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“…A similar range of values is obtained from observations of molecular clouds. Hennebelle & Falgarone (2012) showed that, when compiled, the observational results are compatible with a variation of the exponent with R, i.e., non-power-law behavior, a feature that was also noticed in numerical simulations (Veltchev et al 2016).…”

Section: Mass-size Relationsupporting

confidence: 64%

Physical Properties of Molecular Clouds for the Entire Milky Way Disk

Miville-Deschênes¹,

Murray²,

Lee³

2017

ApJ

360

303

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This study presents a catalog of 8107 molecular clouds that covers the entire Galactic plane and includes 98% of the 12 CO emission observed within b ± 5• . The catalog was produced using a hierarchical cluster identification method applied to the result of a Gaussian decomposition of the Dame et al. data. The total H 2 mass in the catalog is 1.2 × 10 9 M , in agreement with previous estimates. We find that 30% of the sight lines intersect only a single cloud, with another 25% intersecting only two clouds. The most probable cloud size is R ∼ 30 pc. We find that M ∝ R 2.2±0.2 , with no correlation between the cloud surface density, Σ, and R. In contrast with the general idea, we find a rather large range of values of Σ, from 2 to 300 M pc −2 , and a systematic decrease with increasing Galactic radius, R gal . The cloud velocity dispersion and the normalization σ 0 = σ v /R 1/2 both decrease systematically with R gal . When studied over the whole Galactic disk, there is a large dispersion in the line width-size relation, and a significantly better correlation between σ v and Σ R. The normalization of this correlation is constant to better than a factor of two for R gal < 20 kpc. This relation is used to disentangle the ambiguity between near and far kinematic distances. We report a strong variation of the turbulent energy injection rate. In the outer Galaxy it may be maintained by accretion through the disk and/or onto the clouds, but neither source can drive the 100 times higher cloud-averaged injection rate in the inner Galaxy.

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Section: Mass-size Relationsupporting

confidence: 64%

Physical Properties of Molecular Clouds for the Entire Milky Way Disk

Miville-Deschênes¹,

Murray²,

Lee³

2017

ApJ

360

303

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“…Traditionally, the apperent near-virialization exhibited by clouds and their substructures (clumps and dense cores) been interpreted as a manifestation that all the structures in this hierarchy are supported against their selfgravity by strongly supersonic turbulence, and that, when this turbulence dissipates at the smallest scales, the cores can then proceed to collapse (see, e.g., the reviews by Larson 1981;Vázquez-Semadeni et al 2000;Mac Low & Klessen 2004;Ballesteros-Paredes et al 2007;McKee & Ostriker 2007;Bergin & Tafalla 2007;Hennebelle & Falgarone 2012;Dobbs et al 2014;Donkov et al 2011Donkov et al , 2012Veltchev et al 2016). However, it is difficult to understand how the many energy-injection mechanisms could adjust themselves to provide just the right amount of energy to the turbulence to keep the structures nearly virialized at all scales.…”

Section: Discussionmentioning

confidence: 99%

Gravity or turbulence? IV. Collapsing cores in out-of-virial disguise

Ballesteros-Paredes

Vázquez‐Semadeni

Palau

et al. 2018

Monthly Notices of the Royal Astronomical Society

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We study the dynamical state of cores by using a simple analytical model, a sample of observational massive cores, and numerical simulations of collapsing massive cores. From the analytical model, we find that, if cores are formed from turbulent compressions, they evolve from small to large column densities, increasing their velocity dispersion as they collapse. This results in a time evolution path in the Larson velocity dispersion-size diagram from large sizes and small velocity dispersions to small sizes and large velocity dispersions, while they tend to equipartition between gravity and kinetic energy.From the observational sample, we find that: (a) cores with substantially different column densities in the sample do not follow a Larson-like linewidth-size relation. Instead, cores with higher column densities tend to be located in the upper-left corner of the Larson velocity dispersion σ v,3D -size R diagram, a result predicted previously (Ballesteros-Paredes et al. 2011a). (b) The data exhibit cores with overvirial values.Finally, in the simulations of collapsing cores we reproduce the behavior predicted by the analytical model and depicted in the observational sample: cores evolve towards larger velocity dispersions and smaller sizes as they collapse and increase their column density. More importantly, however, is that collapsing cores appear to approach overvirial states within a free-fall time. We find that the cause of this apparent excess of kinetic energy is an underestimation of the actual gravitational energy, due to the assumption that the gravitational energy is given by the energy of an isolated sphere of constant column density. We find that this apparent excess disappears when the gravitational energy is correctly calculated from the actual spatial mass distribution, where inhomogeneities, as well as the potential due to the mass outside of the core, also contribute to the gravitational energy. We conclude that the observed energy budget of cores in recent surveys is consistent with their non-thermal motions being driven by their self-gravity and in the process of dynamical collapse.

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“…Therefore, the study of star formation requires an understanding of the morphological and kinematical evolution of MCs. This evolution could be traced, e.g., through the physical parameters of cloud fragments (clumps, cores, filaments) and their scaling relations (Heyer et al 2009; Larson 1981; Solomon et al 1987; Veltchev et al 2018) or by investigation of the general cloud structure in terms of abstract scales (Dib et al 2020; Donkov et al 2017; Heyer & Brunt 2004; Stutzki et al 1998; Veltchev et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Extraction of a second power‐law tail of the density distribution in simulated clouds

et al. 2021

Self Cite

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The emergence and development of a power-law tail (PLT) at the high-density end of the observed column-density distribution are thought to be indicative for advanced evolution of star-forming molecular clouds. As shown from many numerical simulations, it corresponds to a morphologically analogous evolution of the mass-density distribution ( -PDF). The latter may display also a second, shallower PLT at the stage of collapse of the first formed protostellar cores. It is difficult to estimate the parameters of a possible second PLT due to resolution constraints. To address the issue, we extend the method for the extraction of single PLTs from arbitrary density distributions suggested by Veltchev et al. (MNRAS, 489, 788, 2019) to detect a second PLT. The technique is elaborated through tests on an analytic ρ-PDF and applied to a set of hydrodynamical high-resolution simulations of isothermal self-gravitating clouds. In all but one case two PLTs were detected-the first slope is always steeper and the second one is typically ln V∕ ln ∼ −1. These results are in a good agreement with numerical and theoretical works and do suggest that the technique extracts correctly double PLTs from smooth PDFs.

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Modelling the structure of molecular clouds – I. A multiscale energy equipartition

Cited by 14 publications

References 62 publications

Physical Properties of Molecular Clouds for the Entire Milky Way Disk

Physical Properties of Molecular Clouds for the Entire Milky Way Disk

Gravity or turbulence? IV. Collapsing cores in out-of-virial disguise

Extraction of a second power‐law tail of the density distribution in simulated clouds

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