The BU-FCRAO Milky Way Galactic Ring Survey: Principal Component and Delta-Variance Analysis of large scale spectral line images of clouds in the first Galactic quadrant

Details The BU-FCRAO Milky Way Galactic Ring Survey: Principal Component and Delta-Variance Analysis of large scale spectral line images of clouds in the first Galactic quadrant The BU-FCRAO Milky Way Galactic Ring Survey: Principal Component and Delta-Variance Analysis of large scale spectral line images of clouds in the first Galactic quadrant

Dec 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000aas...197.0510s&link_type=abstract

American Astronomical Society, 197th AAS Meeting, #05.10; Bulletin of the American Astronomical Society, Vol. 32, p.1395

Astronomy and Astrophysics

Astronomy

1

Scientific paper

We present results from a Principal Component (PCA) and Delta-Variance analysis applied to large scale spectral line images of molecular cloud complexes in the BU-FCRAO Milky Way Galactic Ring Survey (GRS), a high resolution survey of the first Galactic quadrant in the 13CO 1-0 molecular line. Our goal is to quantify the spatial and kinematic variablity of molecular line emission as these provide clues to the processes which regulate the evolution of the dense interstellar medium. Clouds with different star formation activity are used to investigate the relation between cloud structure and star formation. Both PCA and the Delta-variance prove to be valuable tools to quantify the structure in molecular cloud images. We determine the size-scales of spatial and velocity fluctuations and the effects of noise, finite resolution, and limited cloud coverage in the observations. The energy spectrum for several of the clouds is estimated from the decomposition of the data cubes using Principal Component Analysis. The power law slopes of the energy spectra are typically 2 and correspond to Burgers' turbulence in which kinetic energy is dissipated in shocks and replenished by internal and/or external sources. The Galactic Ring Survey acknowledges support by the NSF via grant AST--9800334.

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