Autonomous Gaussian decomposition of the Galactic Ring Survey. I. Global statistics and properties of the 13CO emission data
M. Riener, J. Kainulainen, H. Beuther, J. D. Henshaw, J. H. Orkisz, Y., Wang

TL;DR
This paper presents an automated Gaussian decomposition of the Galactic Ring Survey's 13CO data, revealing statistical properties of molecular gas and its relation to Galactic structure and dynamics.
Contribution
It introduces a fully automated Gaussian decomposition method for large molecular line surveys and analyzes the resulting component statistics to understand Galactic gas properties.
Findings
Velocity dispersion increases toward the inner Galaxy and midplane.
Number of Gaussian components correlates with the amount of line-of-sight structure.
Emission from the far side of the Galaxy shows higher velocity dispersions, aiding in Galactic structure analysis.
Abstract
The analysis of large molecular line surveys of the Galactic plane is essential for our understanding of the gas kinematics on Galactic scales, in particular its link with the formation and evolution of dense structures in the interstellar medium. An approximation of the emission peaks with Gaussian functions allows for an efficient and straightforward extraction of useful physical information contained in the shape and Doppler-shifted frequency of the emission lines contained in these enormous data sets. In this work we present an overview and first results of a Gaussian decomposition of the entire Galactic Ring Survey (GRS) 13CO (1-0) data that consists of about 2.3 million spectra. We performed the decomposition with the fully automated GaussPy+ algorithm and fitted about 4.6 million Gaussian components to the GRS spectra. We discuss the statistics of the fit components and relations…
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Taxonomy
TopicsAstrophysics and Star Formation Studies · Stellar, planetary, and galactic studies · Astronomy and Astrophysical Research
