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Galaxy and black hole co-evolution in dark matter haloes not captured by cosmological simulations

Nature Astronomy (2026)Cite this article

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Abstract

Star formation in galaxies is governed by internal and environmental processes, yet their relative roles are not well understood. In particular, uncertainties in measurements of active galactic nuclei (AGN) host galaxies, combined with modelling limitations, obfuscate the impact of supermassive black hole feedback across environments and over time. Here we address this with a comprehensive analysis of ~60,000 nearby AGNs (redshift z < 0.15) and new environment and halo mass measurements for ~500,000 AGN and non-AGN host galaxies. This benchmark enables unified comparisons with three prominent cosmological simulations—SIMBA, TNG and EAGLE—and reveals major, contrasting shortcomings. Simulations fail to reproduce observed trends linking star formation, quiescence, AGN luminosity, stellar mass and halo mass. While simulations qualitatively capture that AGNs are more common in low-mass halos than in rich groups or clusters, detailed host demographics diverge strongly from observations. Partial agreement exists in the stellar mass distribution within large-scale structures, yet all simulations overproduce quenched low-mass satellites in massive halos, while misrepresenting quenched fractions of massive central galaxies and those in low-density environments, which are sensitive to feedback implementation. Improved AGN physics and modelling of multi-phase gas cooling and flows are required to capture the observed interplay between black holes, galaxies and halos.

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Fig. 1: Galaxy SMFs.
Fig. 2: Comparison of stellar mass overdensity distributions across multiple scales.
Fig. 3: Trends of quiescent galaxy fractions with stellar mass and environment in SDSS and simulations.
Fig. 4: Quenched fractions of satellite galaxies as a function of stellar and halo mass.
Fig. 5: Demographics of AGN and their host galaxies in the SDSS and the simulations.
Fig. 6: Distributions of halo-scale stellar mass overdensity and halo mass for simulated and SDSS AGNs and galaxies.

Data availability

All observational and simulation data used in this study are publicly available via the links below. Our newly derived measurements will be made publicly accessible in the future to facilitate comparisons and reproducibility. Requests for early access to these data can be accommodated upon reasonable enquiry. SDSS AGN catalogue: ref. 73 and https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/243/21. SDSS galaxy catalogue: ref. 75 and https://salims.pages.iu.edu/gswlc/. SDSS group catalogue: ref. 21 and https://gax.sjtu.edu.cn/data/Group.html. Galaxy and Mass Assembly (GAMA): ref. 19 and https://www.gama-survey.org/dr4/. GAMA galaxy group catalogue: ref. 22 and https://www.gama-survey.org/dr4/schema/dmu.php?id=115. IRAS 60 micron data (median coadds): https://irsa.ipac.caltech.edu/applications/Scanpi/. Pan-STARRS: https://catalogs.mast.stsci.edu/panstarrs/. 2MASS: https://irsa.ipac.caltech.edu/Missions/2mass.html. UKIDSS: http://wsa.roe.ac.uk/. WISE: https://irsa.ipac.caltech.edu/Missions/wise.html. XMM-DR14 catalogue: ref. 29 and http://xmmssc.irap.omp.eu/Catalogue/4XMM-DR14/4XMM_DR14.html. EAGLE simulations: https://icc.dur.ac.uk/Eagle/database.php. IllustrisTNG simulations: https://www.tng-project.org/data/. SIMBA simulations: http://simba.roe.ac.uk. We note that herein we have analysed versions of SIMBA and EAGLE that were re-processed by ref. 115 to enable an apples-to-apples comparison with TNG, not the original versions.

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Acknowledgements

We deeply appreciate the valuable consultations and discussions on various aspects of the simulations with A. Ludlow, C. Power, D. Nelson, K. Harborne and M. R. Ayromlou. We are also grateful to L. Hao and her research group for their useful discussions and support, which greatly facilitated the progress and ease of this research. C.B. gratefully acknowledges support from the Forrest Research Foundation. H.M.Y. was partially supported by the Research Fund for International Young Scientists of NSFC (11950410492) and JSPS KAKENHI Grant Number JP22K14072. This work was supported by resources provided by the Pawsey Supercomputing Research Centre’s Setonix Supercomputer (https://doi.org/10.48569/18sb-8s43) and Acacia Object Storage (https://doi.org/10.48569/nfe9-a426), with funding from the Australian Government and the Government of Western Australia.

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Authors and Affiliations

  1. Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China

    Hassen M. Yesuf

  2. Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo, Kashiwa, Japan

    Hassen M. Yesuf

  3. Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing, China

    Hassen M. Yesuf

  4. International Centre for Radio Astronomy Research, University of Western Australia, Crawley, Western Australia, Australia

    Connor Bottrell

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  1. Hassen M. Yesuf
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  2. Connor Bottrell
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Contributions

H.M.Y. developed the idea for the project, performed all observational measurements, including environmental measurements, and conducted the data analysis. C.B. compiled the simulation data and conducted the environmental measurements for the simulations. Both authors contributed to the interpretation of the results and writing the text of the paper.

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Correspondence to Hassen M. Yesuf.

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Extended data

Extended Data Fig. 1 Stellar mass functions of the SIMBA, EAGLE, and TNG simulation variants compared with GAMA.

Panels are grouped by simulation (snapshots at z ≈ 0.1) and, for each simulation, show the stellar mass functions of the global, high-SFR, low-SFR, and quiescent populations, defined by ΔSFR relative to the star-forming main sequence (SFMS). In all panels, the violet curves show the median stellar mass function and the 16th–84th percentile uncertainty range derived from fits to GAMA galaxies at z < 0.12. Error bars on the simulation curves indicate standard deviations assuming Poisson statistics. SIMBA (a-d): Black, red, green, and blue curves correspond to SIMBA variants with X-ray feedback disabled; both jet-mode and X-ray AGN feedback disabled; all AGN feedback disabled; and all AGN and supernova feedback processes disabled, respectively. EAGLE (e-h): Red, teal, green, and blue curves correspond to the fiducial EAGLE-50 simulation; the EAGLE-50 variant with increased AGN heating temperature (TAGN = 109 K); the EAGLE-50 simulation with AGN feedback disabled; and the higher-resolution EAGLE-25 simulation, respectively. TNG (i-l): Blue, green, and red curves show the three volume variants of the TNG simulations.

Extended Data Fig. 2 Quiescent satellite fractions in SIMBA and EAGLE feedback variants.

Panels (a)-(d) show the SIMBA50 variants: full physics with all feedback enabled; both jet-mode and X-ray AGN feedback disabled; all AGN feedback disabled; and all AGN and supernova feedback disabled, respectively. Panels (e)-(h) show the EAGLE50 variants: full physics; increased AGN heating temperature (TAGN = 109 K); AGN feedback disabled; and the larger-volume EAGLE100 simulation, respectively.

Extended Data Fig. 3 Trends of star formation rates (SFRs) with stellar mass and environment in SDSS and simulations.

Only star-forming galaxies (SFGs) are considered. Panel (a) shows the mean SFR trends for SFGs in SDSS, illustrating the expected positive correlation with stellar mass. Panels (b)-(d) show the residuals of SFR between each simulation and SDSS. Green (brown) residuals indicate higher (lower) SFRs in the simulations for galaxies of the same stellar mass in the same environment. Insets show the ratio of the absolute difference to SDSS uncertainties, \(| \Delta {{\rm{f}}}_{{\rm{q}}}| /{\sigma }_{{{\rm{f}}}_{{\rm{q}}}}\), providing a measure of the tension (σ-level).

Extended Data Fig. 4 Comparison of simulated AGNs and their host galaxies with SDSS observations.

Panels (a)-(e) show the distributions of (a) AGN luminosity, (b) Eddington ratio, (c) black hole-to-stellar mass ratio, (d) stellar mass, and (e) specific star formation rate, while panel (f) shows stellar mass versus star formation rate. The sample is restricted to galaxies with LAGN > 1042erg s−1, M* > 109 M ⊙ and z < 0.15. SDSS distributions are weighted by 1/Vmax to correct for sample incompleteness.

Extended Data Fig. 5 Black hole mass functions (BHMFs) from simulations compared with SDSS observations.

Panel (a) shows the full fiducial subsample and includes BHMF fits for Swift-BAT AGNs (Ananna et al. 2022)118, plotted using their two fitting methods. The remaining panels divide the samples by stellar mass or AGN luminosity. Error bars denote standard deviations assuming Poisson statistics.

Extended Data Fig. 6 Relations between quiescence and galaxy stellar mass for satellites and centrals in SDSS and the three simulations.

Each row of panels compares the quiescent fractions of satellites (panels a,c) and centrals (panels b,d). The bottom panels (c,d) show the subpopulations of satellites and centrals in regions with overdensity greater than three. Error bars on the quiescent fractions represent the standard error of a proportion.

Extended Data Table 1 Comparison between simulation predictions and GAMA stellar mass functions for galaxy subpopulations
Full size table
Extended Data Table 2 Aggregate discrepancies in quenched fraction and star formation rate across mass-environment space
Full size table
Extended Data Table 3 Discrepancies between SDSS and simulations in AGN and host galaxy distributions
Full size table

Supplementary information

Supplementary Information

Supplementary Figs. 1–17 and Table 1, as well as sensitivity analyses assessing the robustness of the results and extended discussion of the figures and findings.

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Yesuf, H.M., Bottrell, C. Galaxy and black hole co-evolution in dark matter haloes not captured by cosmological simulations. Nat Astron (2026). https://doi.org/10.1038/s41550-026-02792-y

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