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Título: | A bayesian-like approach to derive chemical abundances in type-2 active galactic nuclei based on photoionization models |
Autor: | Pérez Montero, Enrique ; Dors, O. L.; Vílchez Medina, José Manuel CSIC ORCID; García-Benito, Rubén CSIC ORCID ; Cardaci, M. V.; Hägele, Guillermo F. | Palabras clave: | Methods: data analysis ISM: abundances Galaxies: abundances Galaxies: active Galaxies: Seyfert |
Fecha de publicación: | 2019 | Editor: | Oxford University Press | Citación: | Monthly Notices of the Royal Astronomical Society 489(2): 2652-2668 (2019) | Resumen: | We present a new methodology for the analysis of the emission lines of the interstellar medium in the narrow-line regions around type-2 active galactic nuclei. Our aim is to provide a recipe that can be used for large samples of objects in a consistent way using different sets of optical emission lines that takes into the account possible variations from the O/H-N/O relation to use [N II] lines. Our approach consists of a bayesian-like comparison between certain observed emission-line ratios sensitive to total oxygen abundance, nitrogen-to-oxygen ratio, and ionization parameter with the predictions from a large grid of photoionization models calculated under the most usual conditions in this environment. We applied our method to a sample of Seyfert 2 galaxies with optical emission-line fluxes and determinations of their chemical properties from detailed models in the literature. Our results agree within the errors with other results and confirm the high metallicity of the objects of the sample, with N/O values consistent with a large secondary production of N, but with a large dispersion. The obtained ionization parameters for this sample are much larger than those for star-forming object at the same metallicity. © 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society | Versión del editor: | http://dx.doi.org/10.1093/mnras/stz2278 | URI: | http://hdl.handle.net/10261/192083 | DOI: | 10.1093/mnras/stz2278 | ISSN: | 0035-8711 |
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