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Published December 20, 2019 | Accepted Version + Published
Journal Article Open

High-redshift Galaxy Formation with Self-consistently Modeled Stars and Massive Black Holes: Stellar Feedback and Quasar Growth

Abstract

As computational resolution of modern cosmological simulations come closer to resolving individual star-forming clumps in a galaxy, the need for "resolution-appropriate" physics for a galaxy-scale simulation has never been greater. To this end, we introduce a self-consistent numerical framework that includes explicit treatments of feedback from star-forming molecular clouds (SFMCs) and massive black holes (MBHs). In addition to the thermal supernovae feedback from SFMC particles, photoionizing radiation from both SFMCs and MBHs is tracked through full three-dimensional ray tracing. A mechanical feedback channel from MBHs is also considered. Using our framework, we perform a state-of-the-art cosmological simulation of a quasar-host galaxy at z ~ 7.5 for ~25 Myr with all relevant galactic components, such as dark matter, gas, SFMCs, and an embedded MBH seed of ≳10⁶ M⊙. We find that feedback from SFMCs and an accreting MBH suppresses runaway star formation locally in the galactic core region. Newly included radiation feedback from SFMCs, combined with feedback from the MBH, helps the MBH grow faster by retaining gas that eventually accretes on to the MBH. Our experiment demonstrates that previously undiscussed types of interplay between gas, SFMCs, and a MBH may hold important clues about the growth and feedback of quasars and their host galaxies in the high-redshift universe.

Additional Information

© 2019 The American Astronomical Society. Received 2019 August 9; revised 2019 October 21; accepted 2019 October 23; published 2019 December 16. The authors thank Heon-Young Chang, Mark Krumholz, Myeong-Gu Park, and Hao-Yi Wu for insightful discussions during the progress of this study. We also thank the anonymous referee who helped significantly improve the draft of this paper. J.K. acknowledges support by Samsung Science and Technology Foundation under Project Number SSTF-BA1802-04, and by Research Start-up Fund for the new faculty of Seoul National University. J.W. is supported by National Science Foundation grants AST-1614333 and OAC-1835213 and NASA grant NNX17AG23G. The computing time used for the presented simulation was in part provided by Extreme Science and Engineering Discovery Environment (XSEDE) allocations TG-AST140023 and TG-AST140064. XSEDE is supported by the National Science Foundation (NSF) grant ACI-1053575. Resources supporting this work were also provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. This work was also supported by the National Institute of Supercomputing and Network/Korea Institute of Science and Technology Information with supercomputing resources including technical support, grants KSC-2018-S1-0016 and KSC-2018-CRE-0052. The publicly available Enzo and yt codes that we have used in this work are the products of collaborative efforts by many independent scientists from numerous institutions around the world. Their commitment to open science has helped to make this work possible.

Attached Files

Published - Kim_2019_ApJ_887_120.pdf

Accepted Version - 1910.12888.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 18, 2023