Structural Analysis of Molecular Clouds: Dendrograms

By Erik Rosolowsky, J. Pineda, Jens Kauffmann, A. Goodman. 2008

405 citations recorded by the source corpus.

We demonstrate the utility of dendrograms at representing the essential features of the hierarchical structure of the isosurfaces for molecular line data cubes. The dendrogram of a data cube is an abstraction of the changing topology of the isosurfaces as a function of contour level. The ability to track hierarchical structure over a range of scales makes this analysis philosophically different from local segmentation algorithms like CLUMPFIND. Points in the dendrogram structure correspond to specific volumes in data cubes defined by their bounding isosurfaces. We further refine the technique by measuring the properties associated with each isosurface in the analysis allowing for a multiscale calculation of molecular gas properties. Using COMPLETE13CO (J = 1→ 0) data from the L1448 region in Perseus and mock observations of a simulated data cube, we identify regions that have a significant contribution by self-gravity to their energetics on a range of scales. We find evidence for self-gravitation on all spatial scales in L1448, although not in all regions. In the simulated observations, nearly all of the emission is found in objects that would be self-gravitating if gravity were included in the simulation. We reconstruct the size-line-width relationship within the data cube using the dendrogram-derived properties and find it follows the standard relation: σv ∝ R0.58. Finally, we show that constructing the dendrogram of CO (J = 1→ 0) emission from the Orion-Monoceros region allows for the identification of giant molecular clouds in a blended molecular line data set using only a physically motivated definition (self-gravitating clouds with masses >5 × 104 M☉).

Subfields: Applied Mathematics, Astronomy and Astrophysics, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/55c47444addf3736d74490d3da52523c365668f3

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Citations in the corpus

SDC13 infrared dark clouds: longitudinally collapsing filaments? (2013, methodology): “It is calculated by taking the average of the clipping and the bijection schemes of the flux estimates (Rosolowsky et al. 2008).”
Molecular gas kinematics within the central 250 pc of the Milky Way (2016, background): “The quantitative effects of this truncation are discussed in Rosolowsky & Blitz (2005) and Rosolowsky et al. (2008).”
Dense gas in the Galactic central molecular zone is warm and heated by turbulence (2015, methodology): “…to extract higher signal-to-noise measurements on selected regions, we broke the data down into subsets using both a by-eye region selection drawing regions using ds9 and a more systematic approach using a dendrogram-based clump finding algorithm (Rosolowsky et al. 2008, http:// dendrograms.org/).”
PHYSICAL PROPERTIES OF MOLECULAR CLOUDS FOR THE ENTIRE MILKY WAY DISK (2016, methodology): “One way to improve on this is to look for hierarchical coherence within structures identified with different threshold levels, e.g., clumpfind (Williams et al. 1994) or the dendrogram technique (Rosolowsky et al. 2008).”
THE MAGELLANIC MOPRA ASSESSMENT (MAGMA). I. THE MOLECULAR CLOUD POPULATION OF THE LARGE MAGELLANIC CLOUD (2011, methodology): “In addition, the use of hierarchical decomposition methods (e.g. Rosolowsky et al. 2008; Kauffmann et al. 2010) will help to characterize the observed structures more robustly.”
ESTIMATING THE STAR FORMATION RATE AT 1 kpc SCALES IN NEARBY GALAXIES (2012, background): “Not much is known about the behavior of the DGR on kpc scales, but changes in metallicity do tend to be weak over such scales (e.g., Rosolowsky et al. 2008; Moustakas et al. 2010).”
Molecular Clouds in the Milky Way (2015, background): “With increasing angular resolution and sensitivity, hierarchical structure becomes more evident as localized, high-density peaks are found within larger clump structures, which themselves reside within the larger molecular cloud complex (Scalo 1985, Rosolowsky et al. 2008).”
FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45-m telescope (FUGIN) I: Project Overview and Initial Results (2017, methodology): “…clouds, clumps and filaments in the Galactic plane by using cloud/clump finding tools, e.g., Clumpfind (Williams et al. 1994) and Dedrograms (Rosolowsky et al. 2008), filament finding tool (DisPerSE: Sousbie 2011), and also catalogs of shell and arc structures that correspond to Spitzer…”
HOW MANY INFRARED DARK CLOUDS CAN FORM MASSIVE STARS AND CLUSTERS? (2010, methodology): “Using a dendogram method introduced by Rosolowsky et al. (2008), starting from a set of local column density maxima, a given column density map is contoured with infinitesimal level spacing.”
The Resolved Properties of Extragalactic Giant Molecular Clouds (2008, background): “Equation 1 is known as the size-line width relation, and it has been shown to hold even within GMCs down to very small scales (Heyer & Brunt 2004; Rosolowsky et al. 2008).”
A multi-scale, multi-wavelength source extraction method: getsources (2012, methodology): “Unlike such techniques as the dendrogram analysis (Rosolowsky et al. 2008), however, getsources is not explicitly designed to characterize the hierarchy of structures; our main focus is on the “compact” sources, at the end of the hierarchy.”
The big problems in star formation: The star formation rate, stellar clustering, and the initial mass function (2014, methodology): “Both dense cores (André et al. 2007; Kirk et al. 2007; Rosolowsky et al. 2008a) and stars (Fűrész et al. 2008; Tobin et al. 2009) show systematically smaller velocity dispersions than the diffuse gas in the same region.”