Statistical link between the structure of molecular clouds and their density distribution

We introduce the concept of a class of equivalence of molecular clouds represented by an abstract spherically symmetric, isotropic object. This object is described by use of abstract scales in respect to a given mass-density distribution. Mass and average density are ascribed to each scale and thus...

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Hauptverfasser: Donkov, Sava (VerfasserIn) , Veltchev, Todor V. (VerfasserIn) , Klessen, Ralf S. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2017
In: Monthly notices of the Royal Astronomical Society
Year: 2016, Jahrgang: 466, Heft: 1, Pages: 914-920
ISSN:1365-2966
DOI:10.1093/mnras/stw3147
Online-Zugang:Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1093/mnras/stw3147
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Verfasserangaben:Sava Donkov, Todor V. Veltchev and Ralf S. Klessen
Beschreibung
Zusammenfassung:We introduce the concept of a class of equivalence of molecular clouds represented by an abstract spherically symmetric, isotropic object. This object is described by use of abstract scales in respect to a given mass-density distribution. Mass and average density are ascribed to each scale and thus are linked to the density distribution: a power-law type and an arbitrary continuous one. In the latter case, we derive a differential relationship between the mean density at a given scale and the structure parameter that defines the mass-density relationship. The two-dimensional (2D) projection of the cloud along the line of sight is also investigated. Scaling relations of mass and mean density are derived in the considered cases of power-law and arbitrary continuous distributions. We obtain relations between scaling exponents in the 2D and 3D cases. The proposed classes of equivalence are representative for the general structure of real clouds with various types of column-density distributions: power law, lognormal or combination of both.
Beschreibung:Publilshed: 10 December 2016
Gesehen am 03.08.2017
Beschreibung:Online Resource
ISSN:1365-2966
DOI:10.1093/mnras/stw3147