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Title: Trinity I: self-consistently modelling the dark matter halo–galaxy–supermassive black hole connection from z  = 0–10
ABSTRACT

We present Trinity, a flexible empirical model that self-consistently infers the statistical connection between dark matter haloes, galaxies, and supermassive black holes (SMBHs). Trinity is constrained by galaxy observables from 0 < z < 10 [galaxies’ stellar mass functions, specific and cosmic star formation rates (SFRs), quenched fractions, and UV luminosity functions] and SMBH observables from 0 < z < 6.5 (quasar luminosity functions, quasar probability distribution functions, active black hole mass functions, local SMBH mass–bulge mass relations, and the observed SMBH mass distributions of high-redshift bright quasars). The model includes full treatment of observational systematics [e.g. active galactic nucleus (AGN) obscuration and errors in stellar masses]. From these data, Trinity infers the average SMBH mass, SMBH accretion rate, merger rate, and Eddington ratio distribution as functions of halo mass, galaxy stellar mass, and redshift. Key findings include: (1) the normalization and the slope of the SMBH mass–bulge mass relation increases mildly from z = 0 to z = 10; (2) The best-fitting AGN radiative+kinetic efficiency is ∼0.05–0.06, but can be in the range ∼0.035–0.07 with alternative input assumptions; (3) AGNs show downsizing, i.e. the Eddington ratios of more massive SMBHs start to decrease earlier than those of lower mass objects; (4) The average ratio between average SMBH accretion rate and SFR is ∼10−3 for low-mass galaxies, which are primarily star-forming. This ratio increases to ∼10−1 for the most massive haloes below z ∼ 1, where star formation is quenched but SMBHs continue to accrete.

 
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Award ID(s):
1908284
NSF-PAR ID:
10492479
Author(s) / Creator(s):
 ; ; ; ; ; ;  ;
Publisher / Repository:
MNRAS
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
518
Issue:
2
ISSN:
0035-8711
Page Range / eLocation ID:
2123 to 2163
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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