Journal article
Dark-ages reionization and galaxy formation simulation - XV. Stellar evolution and feedback in dwarf galaxies at high redshift
Y Qin, AR Duffy, SJ Mutch, GB Poole, A Mesinger, JSB Wyithe
Monthly Notices of the Royal Astronomical Society | OXFORD UNIV PRESS | Published : 2019
Abstract
We directly compare predictions of dwarf galaxy properties in a semi-analytic model (SAM) with those extracted from a high-resolution hydrodynamic simulation. We focus on galaxies with halo masses of 109 < Mvir/M⊙ ≲ 1011 at high redshift (z ≥ 5). We find that, with the modifications previously proposed in Qin et al. (2018), including to suppress the halo mass and baryon fraction, as well as to modulate gas cooling and star formation efficiencies, the SAM can reproduce the cosmic evolution of galaxy properties predicted by the hydrodynamic simulation. These include the galaxy stellar mass function, total baryonic mass, star-forming gas mass, and star formation rate at z ~ 5-11. However, this ..
View full abstractRelated Projects (1)
Grants
Awarded by State Government of Victoria
Funding Acknowledgements
This research was supported by the Victorian Life Sciences Computation Initiative, grant ref. 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 was conducted by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D, project #CE170100013). 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. YQ acknowledges support from the Albert Shimmins Fund. AMacknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant #638809-AIDA).