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Details

Autor(en) / Beteiligte
Titel
Dark-ages reionization and galaxy formation simulation V: morphology and statistical signatures of reionization
Ist Teil von
  • Monthly notices of the Royal Astronomical Society, 2016-10, Vol.462 (1), p.804-817
Ort / Verlag
London: Oxford University Press
Erscheinungsjahr
2016
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • We use the Dark-ages, Reionization And Galaxy formation Observables from Numerical Simulations (DRAGONS) framework to investigate the effect of galaxy formation physics on the morphology and statistics of ionized hydrogen (H ii) regions during the Epoch of Reioinization (EoR). DRAGONS self-consistently couples a semi-analytic galaxy formation model with the inhomogeneous ionizing UV background, and can therefore be used to study the dependence of morphology and statistics of reionization on feedback phenomena of the ionizing source galaxy population. Changes in galaxy formation physics modify the sizes of H ii regions and the amplitude and shape of 21-cm power spectra. Of the galaxy physics investigated, we find that supernova feedback plays the most important role in reionization, with H ii regions up to ≈20 per cent smaller and a fractional difference in the amplitude of power spectra of up to ≈17 per cent at fixed ionized fraction in the absence of this feedback. We compare our galaxy formation-based reionization models with past calculations that assume constant stellar-to-halo mass ratios and find that with the correct choice of minimum halo mass, such models can mimic the predicted reionization morphology. Reionization morphology at fixed neutral fraction is therefore not uniquely determined by the details of galaxy formation, but is sensitive to the mass of the haloes hosting the bulk of the ionizing sources. Simple EoR parametrizations are therefore accurate predictors of reionization statistics. However, a complete understanding of reionization using future 21-cm observations will require interpretation with realistic galaxy formation models, in combination with other observations.
Sprache
Englisch
Identifikatoren
ISSN: 0035-8711
eISSN: 1365-2966
DOI: 10.1093/mnras/stw1718
Titel-ID: cdi_proquest_miscellaneous_1845832775

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