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  Mocking faint black holes during reionization

Eide, M. B., Ciardi, B., Feng, Y., & Matteo, T. D. (2020). Mocking faint black holes during reionization. Monthly Notices of the Royal Astronomical Society, 499(4), 5978-5985. doi:10.1093/mnras/staa3253.

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Eide, Marius B.1, Author              
Ciardi, Benedetta1, Author              
Feng, Yu, Author
Matteo, Tiziana Di, Author
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1Computational Structure Formation, MPI for Astrophysics, Max Planck Society, ou_2205642              

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 Abstract: To investigate the potential abundance and impact of nuclear black holes (BHs) during reionization, we generate a neural network that estimates their masses and accretion rates by training it on 23 properties of galaxies harbouring them at z = 6 in the cosmological hydrodynamical simulation MassiveBlack-II. We then populate all galaxies in the simulation from z = 18 to 5 with BHs from this network. As the network allows to robustly extrapolate to BH masses below those of the BH seeds, we predict a population of faint BHs with a turnover-free luminosity function, while retaining the bright (and observed) BHs, and together they predict a Universe in which intergalactic hydrogen is 15 per cent ionized at z = 6 for a clumping factor of 5. Faint BHs may play a stronger role in H reionization without violating any observational constraints. This is expected to have an impact also on pre-heating and pre-ionization, which is relevant to observations of the 21-cm line from neutral H. We also find that BHs grow more efficiently at higher z, but mainly follow a redshift-independent galaxy–BH relation. We provide a power law parametrization of the hydrogen ionizing emissivity of BHs.

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 Dates: 2020-10-21
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1093/mnras/staa3253
Other: LOCALID: 3283783
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Title: Monthly Notices of the Royal Astronomical Society
  Other : Mon. Not. R. Astron. Soc.
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 499 (4) Sequence Number: - Start / End Page: 5978 - 5985 Identifier: ISSN: 1365-8711
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000024150