Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics
P. Houlahan, J. Scalo;
ApJ, 1992, 393, 172
ABSTRACT:A new method of image analysis is described, in which images partitioned into 'clouds' are
represented by simplified skeleton images, called structure trees, that preserve
the spatial relations of the component clouds while disregarding
information concerning their sizes and shapes.
The method can be used to
discriminate between images of projected hierarchical (multiply nested) and
random three-dimensional simulated collections of clouds constructed on
the basis of observed interstellar properties, and even intermediate
systems formed by combining random and hierarchical simulations.
For a given
structure type, the method can distinguish between different subclasses of
models with different parameters and reliably estimate their hierarchical
parameters: average number of children per parent, scale reduction factor per
level of hierarchy, density contrast, and number of resolved levels.
An
application to a column density image of the Taurus complex constructed from IRAS
data is given.
Moderately strong evidence for a hierarchical structural
component is found, and parameters of the hierarchy, as well as the average volume
filling factor and mass efficiency of fragmentation per level of hierarchy,
are estimated.
The existence of nested structure contradicts models in
which large molecular clouds are supposed to fragment, in a single stage,
into roughly stellar-mass cores.
KEYWORDS: astronomical models, infrared astronomy satellite, interstellar matter, trees (mathematics), molecular clouds, pixels, regression analysis, stellar mass, taurus constellation, three dimensional models
PERSOKEY:turbulence, ,
CODE: houlahan92