Classifying and modelling spiral structures in hydrodynamic simulations of astrophysical discs
Date
11/05/2018Funder
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Abstract
We demonstrate numerical techniques for automatic identification of individual spiral arms in hydrodynamic simulations of astrophysical discs. Building on our earlier work, which used tensor classification to identify regions that were 'spiral-like', we can now obtain fits to spirals for individual arm elements. We show this process can even detect spirals in relatively flocculent spiral patterns, but the resulting fits to logarithmic 'grand-design' spirals are less robust. Our methods not only permit the estimation of pitch angles, but also direct measurements of the spiral arm width and pattern speed. In principle, our techniques will allow the tracking of material as it passes through an arm. Our demonstration uses smoothed particle hydrodynamics simulations, but we stress that the method is suitable for any finite-element hydrodynamics system. We anticipate our techniques will be essential to studies of star formation in disc galaxies, and attempts to find the origin of recently observed spiral structure in protostellar discs.
Citation
Forgan , D H , Ramon-Fox , F G & Bonnell , I A 2018 , ' Classifying and modelling spiral structures in hydrodynamic simulations of astrophysical discs ' , Monthly Notices of the Royal Astronomical Society , vol. 476 , no. 2 , pp. 2384-2395 . https://doi.org/10.1093/mnras/sty331
Publication
Monthly Notices of the Royal Astronomical Society
Status
Peer reviewed
ISSN
0035-8711Type
Journal article
Rights
© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1093/mnras/sty331
Description
DHF, FGR-F and IAB gratefully acknowledge support from the ECOGAL project, grant agreement 291227, funded by the European Research Council under ERC-2011-ADG.Collections
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