Statistics – Computation
Scientific paper
Dec 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005aas...20711903g&link_type=abstract
American Astronomical Society Meeting 207, #119.03; Bulletin of the American Astronomical Society, Vol. 37, p.1358
Statistics
Computation
Scientific paper
An analysis method to evaluate the degree and angle of velocity anisotropy using spectroscopic imaging data of interstellar molecular clouds is presented. Such anisotropies are predicted by analytical descriptions and computational simulations of interstellar MHD turbulence (Goldreich & Sridhar 1995; Cho, Lazarian, & Vishniac 2002; Vestuto, Ostriker, & Stone 2003). Recognizing velocity anisotropy in observational data is challenging owing to limited views of the velocity field by projection, line excitation, and noise. Using 3 dimensional velocity and density fields from the set of numerical simulations by Ostriker, Stone, & Gammie (2001) that span a range of magnetic field strengths, we construct molecular line spectroscopic data cubes accounting for optical depth and non-LTE line excitation. Velocity structure functions along the cardinal axes are derived using Principal Component Analysis (Brunt & Heyer 2002). For weak and intermediate magnetic field strengths, the derived structure functions are statistically identical and indicative of isotropic velocity fields. However, for strong magnetic fields, the measured structure functions are anisotropic with respect to the magnetic field direction as predicted by the models. Instrumental noise and finite resolution do not significantly modify these results. This method is a powerful diagnostic tool to evaluate MHD turbulence in interstellar clouds from observational data.
Brunt Christopher
Gong Haifeng
Heyer Mark
Ostriker Eve
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