Abstract
The masses of supermassive black holes are observed to increase with either the total mass or the mean (random) velocity of the stars in their host galaxies. The origin of these correlations remains elusive due to observational systematics and biases that severely limit our knowledge of the local demography of supermassive black holes. Here, we show that the large-scale spatial distribution of local active galactic nuclei (AGN) can constrain the shape and normalization of the black hole–stellar mass relation, thus bypassing resolution-related observational biases. In turn, our results can set more stringent constraints on the AGN radiative efficiency, ε. For currently accepted values of the AGN obscured fractions and bolometric corrections, our estimated local supermassive black hole mass density favours mean ε values of ~10–20%, suggesting that the vast majority of supermassive black holes are spinning moderately to rapidly. With large-scale AGN surveys coming online, our methodology will enable even tighter constraints on the fundamental parameters that regulate the growth of supermassive black holes.
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Data availability
The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. Source data for Fig. 3 are provided with the paper.
Code availability
The codes that support the findings of this study are available from the corresponding author upon reasonable request.
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Acknowledgements
F.S. thanks D. Weinberg, D. Baron, P. Behroozi, G. Calderone, B. Davis, F. Fiore, P. Gandhi, S. Hoenig, C. Knigge, C. Li, J. Miralda-Escudé, B. Moster, M. Powell, R. Vasudevan, C. Villforth and G. Yang for discussions and input, and acknowledges partial support from a Leverhulme Trust Research Fellowship and the European Union’s Horizon 2020 programme under the AHEAD project (grant agreement no. 654215). V.A. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 749348. M.B. acknowledges partial support from NSF grant AST-1816330. A.L. is supported by PRIN MIUR 2017 prot. 20173ML3WW_002 ‘Opening the ALMA window on the cosmic evolution of gas, stars and supermassive black holes’. M.K. acknowledges support from DLR grant 50OR1904. L.Z. and P.J.G. acknowledge funding from the Science and Technology Facilities Council (STFC).
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F.S. performed the full set up of the AGN mocks, analysis of the results and writing up of the manuscript. V.A. independently checked all of the results on AGN clustering and contributed to text revisions and to the referee reports. M.B. was one of the core authors in the Shankar et al.8 paper on the intrinsic black hole scaling relations and contributed to revision of the manuscript. C.M. devised accurate determinations of the correlation functions in the MultiDark simulation. A.L. calculated the accreted black hole mass functions following the models presented in Aversa et al.7. N.M. contributed to the AGN accretion models. P.J.G. and L.Z. contributed to the galaxy mocks, independently tested some of the key results and provided comments. J.M. performed preliminary large-scale bias estimates of AGN at different luminosities in low-redshift galaxies. M.K. made available a number of datasets on galaxy and AGN clustering inclusive of full covariance matrices. R.D.B. performed independent calculations of some of the AGN mocks. F.R. contributed to the characterization of the scaling relations in optically selected type I and type II AGN and to revision of the paper. F.L.F. provided key insights into the use of different AGN bolometric corrections. R.K.S. was one of the core authors in the Shankar et al.8 paper on the intrinsic black hole scaling relations and provided support on the theoretical side and revision of the paper.
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Extended data
Extended Data Fig. 1 Predicted local black hole mass functions of elliptical galaxies.
Same format as Figure 2 but only for elliptical, bulge-dominated galaxies. Panels a and b show the comparison between, respectively, the observed and intrinsic Mbh-Mstar and Mbh-σ relations of early-type galaxies, as labelled.
Extended Data Fig. 2 Comparing host halo auto-correlation functions.
Comparison between the linear matter correlation function multiplied by the square of the halo bias from Tinker et al. (2005, dotted line) and Tinker et al. (2010, solid line), and the autocorrelation function in the MultiDark simulation of all central and satellite haloes with virial mass at infall in the range 13.3<log Mvir/Msun<13.7. For this comparison we adopt the same cosmological parameters as in the MultiDark simulation.
Extended Data Fig. 3 Direct comparison with the cross-correlation function of active galaxies.
Comparison between the DR4 (panels a and b) and DR7 (panels c and d) projected AGN-galaxy cross-correlation function derived by Krumpe et al. (2015, filled squares with their 1σ uncertainties), with the linear matter projected correlation function multiplied by the product of the galaxy and black hole large-scale biases with Qbh=1 (panels a and c) and Qbh=2 (panels b and d). The solid red and long-dashed black lines refer to the large-scale bias derived, respectively, from the observed and intrinsic Mbh-Mstar relations. It is clear that the models derived from the intrinsic Mbh-Mstar relation (solid red lines) provide a better match to the data (see text for details).
Extended Data Fig. 4 Predicted bias as a function of black hole mass.
Similar format to Figure 2 but now showing the function b(Mbh) expected from the observed/biased (dashed) and intrinsic (solid) Mbh-σ scaling relations.
Extended Data Fig. 5 Table 1.
Black hole mass function retrieved from the intrinsic Mbh-Mstar relation.
Source data
Source Data for Fig. 3
Data on the local black hole mass functions. Columns are: logMbh [Msun], log(Phi_intrinsic) [Mpc-3 dex-1], 1sigma uncertainty in log(Phi_intrinsic), log(Phi_biased) [Mpc-3 dex-1], 1sigma uncertainty in log(Phi_biased)
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Shankar, F., Allevato, V., Bernardi, M. et al. Constraining black hole–galaxy scaling relations and radiative efficiency from galaxy clustering. Nat Astron 4, 282–291 (2020). https://doi.org/10.1038/s41550-019-0949-y
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DOI: https://doi.org/10.1038/s41550-019-0949-y
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