Abstract
Our understanding of the dynamics of the interstellar medium is informed by the study of the detailed velocity structure of emission line observations. One approach to study the velocity structure is to decompose the spectra into individual velocity components; this leads to a description of the data set that is significantly reduced in complexity. However, this decomposition requires full automation lest it become prohibitive for large data sets, such as Galactic plane surveys. We developed GAUSSPY+, a fully automated Gaussian decomposition package that can be applied to emission line data sets, especially large surveys of HI and isotopologues of CO. We built our package upon the existing GAUSSPY algorithm and significantly improved its performance for noisy data. New functionalities of GAUSSPY+ include: (i) automated preparatory steps, such as an accurate noise estimation, which can also be used as stand-alone applications; (ii) an improved fitting routine; (iii) an automated spatial refitting routine that can add spatial coherence to the decomposition results by refitting spectra based on neighbouring fit solutions. We thoroughly tested the performance of GAUSSPY+ on synthetic spectra and a test field from the Galactic Ring Survey. We found that GAUSSPY+ can deal with cases of complex emission and even low to moderate signal-to-noise values.
Highlights
Observations of emission lines are of fundamental importance in radio astronomy
We present GaussPy+, an automated decomposition package that is based on the existing GaussPy algorithm (Lindner et al 2015), but with physically-motivated developments designed for analysing the dynamics of the interstellar medium (ISM)
Even though in this paper we demonstrate the functionality of GaussPy+ only for a small Galactic Ring Survey (GRS) test field, we used the entire data set in testing and developing the algorithm
Summary
Observations of emission lines are of fundamental importance in radio astronomy. Our knowledge about the interstellar medium (ISM) is in large part shaped by observations of the emission of its gas molecules. Rathborne et al 2009; MivilleDeschênes et al 2017; Colombo et al 2019). Such studies are usually more focused on the average properties of the gas on Galactic scales or on the scales of molecular clouds or clumps
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