Shape analysis of H ii regions – II. Synthetic observations

Author:

Campbell-White Justyn12ORCID,Ali Ahmad A3ORCID,Froebrich Dirk2,Kume Alfred4

Affiliation:

1. SUPA, School of Science and Engineering, University of Dundee, Nethergate, Dundee DD1 4HN, UK

2. Centre for Astrophysics and Planetary Science, The University of Kent, Canterbury CT2 7NH, UK

3. Department of Physics and Astronomy, University of Exeter, Stocker Road, Exeter EX4 4QL, UK

4. School of Mathematics, Statistics and Actuarial Sciences, The University of Kent, Canterbury CT2 7FS, UK

Abstract

ABSTRACT The statistical shape analysis method developed for probing the link between physical parameters and morphologies of Galactic H ii regions is applied here to a set of synthetic observations (SOs) of a numerically modelled H ii region. The systematic extraction of H ii region shape, presented in the first paper of this series, allows for a quantifiable confirmation of the accuracy of the numerical simulation, with respect to the real observational counterparts of the resulting SOs. A further aim of this investigation is to determine whether such SOs can be used for direct interpretation of the observational data, in a future supervised classification scheme based upon H ii region shape. The numerical H ii region data were the result of photoionization and radiation pressure feedback of a 34  M⊙ star, in a 1000  M⊙ cloud. The SOs analysed herein comprised four evolutionary snapshots (0.1, 0.2, 0.4, and 0.6 Myr), and multiple viewing projection angles. The shape analysis results provided conclusive evidence of the efficacy of the numerical simulations. When comparing the shapes of the synthetic regions to their observational counterparts, the SOs were grouped in amongst the Galactic H ii regions by the hierarchical clustering procedure. There was also an association between the evolutionary distribution of regions and the respective groups. This suggested that the shape analysis method could be further developed for morphological classification of H ii regions by using a synthetic data training set, with differing initial conditions of well-defined parameters.

Funder

European Research Council

Horizon 2020

Science and Technology Facilities Council

BIS

BEIS

Durham University

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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