Journal article
Dark-ages reionization and galaxy formation simulation - XIV. Gas accretion, cooling, and star formation in dwarf galaxies at high redshift
Y Qin, AR Duffy, SJ Mutch, GB Poole, PM Geil, A Mesinger, JSB Wyithe
Monthly Notices of the Royal Astronomical Society | OXFORD UNIV PRESS | Published : 2018
DOI: 10.1093/mnras/sty767
Abstract
We study dwarf galaxy formation at high redshift (z ≥ 5) using a suite of high-resolution, cosmological hydrodynamic simulations and a semi-analytic model (SAM). We focus on gas accretion, cooling, and star formation in this work by isolating the relevant process from reionization and supernova feedback, which will be further discussed in a companion paper. We apply the SAM to halo merger trees constructed from a collisionless N-body simulation sharing identical initial conditions to the hydrodynamic suite, and calibrate the free parameters against the stellar mass function predicted by the hydrodynamic simulations at z = 5. By making comparisons of the star formation history and gas compone..
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Grants
Awarded by National Computational Infrastructure
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), through project number 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. AM acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant No. 638809 - AIDA).