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Published March 2022 | Accepted Version + Published
Journal Article Open

Black hole-galaxy scaling relations in FIRE: the importance of black hole location and mergers

Abstract

The concurrent growth of supermassive black holes (SMBHs) and their host galaxies remains to be fully explored, especially at high redshift. While often understood as a consequence of self-regulation via AGN feedback, it can also be explained by alternative SMBH accretion models. Here, we expand on previous work by studying the growth of SMBHs with the help of a large suite of cosmological zoom-in simulations (MassiveFIRE) that are part of the Feedback in Realistic Environments (FIRE) project. The growth of SMBHs is modelled in post-processing with different black hole accretion models, placements, and merger treatments, and validated by comparing to on-the-fly calculations. Scaling relations predicted by the gravitational torque-driven accretion (GTDA) model agree with observations at low redshift without the need for AGN feedback, in contrast to models in which the accretion rate depends strongly on SMBH mass. At high redshift, we find deviations from the local scaling relations in line with previous theoretical results. In particular, SMBHs are undermassive, presumably due to stellar feedback, but start to grow efficiently once their host galaxies reach M* ∼ 10¹⁰ M_⊙. We analyse and explain these findings in the context of a simple analytic model. Finally, we show that the predicted scaling relations depend sensitively on the SMBH location and the efficiency of SMBH merging, particularly in low-mass systems. These findings highlight the relevance of understanding the evolution of SMBH-galaxy scaling relations to predict the rate of gravitational wave signals from SMBH mergers across cosmic history.

Additional Information

© 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Accepted 2022 January 5. Received 2022 January 5; in original form 2020 July 24. OÇ thanks Pedro R. Capelo, Alexander P. Hobbs, and Mehmet Hakan Erkut for the discussion and their valuable feedback on the manuscript. OÇ also thanks his wife MÖÇ and three cats LÇ, KÇ and AÇ for their tireless efforts to create a motivating working environment during COVID-19 lockdown. RF acknowledges financial support from the Swiss National Science Foundation (grant no. 157591 and 194814). DAA acknowledges support by NSF grant AST-2009687 and by the Flatiron Institute, which is supported by the Simons Foundation. CAFG was supported by NSF through grants AST-1517491,AST-1715216, and CAREER award AST-1652522; by NASA through grant 17-ATP17-0067; and by a Cottrell Scholar Award and Scialog Award #26968 from the Research Corporation for Science Advancement. Simulations were run with resources provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research centre, proposal SMD-14-5492. Additional computing support was provided by HEC allocations SMD-14-5189, SMD-15-5950, by NSF XSEDE allocations AST120025, AST150045, AST160048, by allocations s697, s698 at the Swiss National Supercomputing Centre (CSCS), and by S3IT resources at the University of Zurich. Numerical calculations were run on the Quest computing cluster at Northwestern University; XSEDE allocation TG-AST140023; and NASA HEC allocation SMD-16-7561 and SMD-17-1204. DATA AVAILABILITY STATEMENT. Please contact the corresponding author if you have a sharing request for the data underlying this article.

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023