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Sökning: WFRF:(Orkisz M.) > Henshaw J. D.

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1.
  • Riener, M., et al. (författare)
  • Autonomous Gaussian decomposition of the Galactic Ring Survey I. Global statistics and properties of the (CO)-C-13 emission data
  • 2020
  • Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 633
  • Tidskriftsartikel (refereegranskat)abstract
    • The analysis of large molecular line surveys of the Galactic plane is essential for our understanding of the gas kinematics on Galactic scales and, 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 the first results of a Gaussian decomposition of the entire Galactic Ring Survey (GRS) (CO)-C-13 (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. These decomposition results enable novel and unexplored ways to interpret and study the gas velocity structure. We discuss the statistics of the fit components and relations between the fitted intensities, velocity centroids, and velocity dispersions. We find that the magnitude of the velocity dispersion values increase towards the inner Galaxy and around the Galactic midplane, which we speculate is partly due to the influence of the Galactic bar and regions with higher non-thermal motions located in the midplane, respectively. We also used our decomposition results to infer global properties of the gas emission and find that the number of fit components used per spectrum is indicative of the amount of structure along the line of sight. We find that the emission lines from regions located on the far side of the Galaxy show increased velocity dispersion values, which are likely due to beam averaging effects. We demonstrate how this trend has the potential to aid in characterising Galactic structure by disentangling emission that belongs to the nearby Aquila Rift molecular cloud from emission that is more likely associated with the Perseus and Outer spiral arms. With this work, we also make our entire decomposition results available.
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2.
  • Riener, M., et al. (författare)
  • GAUSSPY+: A fully automated Gaussian decomposition package for emission line spectra
  • 2019
  • Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 628
  • Tidskriftsartikel (refereegranskat)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.
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