Journal article
Dark-ages reionization and galaxy formation simulation - X. The small contribution of quasars to reionization
Y Qin, SJ Mutch, GB Poole, C Liu, PW Angel, AR Duffy, PM Geil, A Mesinger, JSB Wyithe
Monthly Notices of the Royal Astronomical Society | OXFORD UNIV PRESS | Published : 2017
Abstract
Motivated by recent measurements of the number density of faint AGN at high redshift, we investigate the contribution of quasars to reionization by tracking the growth of central supermassive black holes in an update of the MERAXES semi-analytic model. The model is calibrated against the observed stellar mass function at z ~ 0.6-7, the black hole mass function at z≲0.5, the global ionizing emissivity at z ~ 2-5 and the Thomson scattering optical depth. The model reproduces a Magorrian relation in agreement with observations at z < 0.5 and predicts a decreasing black hole mass towards higher redshifts at fixed total stellar mass. With the implementation of an opening angle of 80 deg for quasa..
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Awarded by Australian Research Council
Funding Acknowledgements
We would like to thank the anonymous referees for providing helpful suggestions that improves the paper substantially. This research was supported by the Victorian Life Sciences Computation Initiative (VLSCI), grant no. UOM0005, on its Peak Computing Facility hosted at the University of Melbourne, an initiative of the Victorian Government, Australia. Part of this work was performed on the gSTAR national facility at Swinburne University of Technology. gSTAR is funded by Swinburne and the Australian Governments Education Investment Fund. This research programme is funded by the Australian Research Council through the ARC Laureate Fellowship FL110100072 awarded to JSBW. This work was supported by the Flagship Allocation Scheme of the NCI National Facility at the ANU, generous allocations of time through the iVEC Partner Share and Australian Supercomputer Time Allocation Committee. AM acknowledges support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant no. 638809 - AIDA).