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The luminosity function and clustering of bright quasars in the FLAMINGO cosmological simulations

Published 28 Oct 2025 in astro-ph.GA and astro-ph.CO | (2510.24283v1)

Abstract: Cosmological hydrodynamical simulations are essential tools for studying the formation and evolution of galaxies and their central supermassive black holes. While they reproduce many key observed properties of galaxies, their limited volumes have hindered comprehensive studies of the AGN and quasar populations. In this work, we leverage the FLAMINGO simulation suite, focusing on its large $(2.8$ $\mathrm{Gpc})3$ volume, to investigate two key observables of quasar activity: the quasar luminosity function (QLF) and quasar clustering. FLAMINGO reproduces the observed QLF at low redshift ($z \lesssim 1$) and for faint quasars ($L_\mathrm{bol} \lesssim 10{45}$ $\mathrm{erg s{-1}}$), but significantly underpredicts the abundance of bright quasars at $z \approx 1$-$3$. Introducing a 0.75 dex log-normal luminosity scatter to represent unresolved small-scale variability boosts the number of bright quasars by upscattering lower-luminosity systems, thereby improving agreement with observations at the bright end. A decomposition of the QLF by black hole mass reveals that this boost is primarily driven by low-mass black holes radiating above the Eddington limit. Nevertheless, limitations remain in fully reproducing the rise and decline of the bright quasar population over cosmic time and in matching the black hole masses inferred from quasar spectra. Thanks to FLAMINGO's large volume, we can robustly sample rare, luminous quasars and measure their spatial clustering for $\log_{10} L_\mathrm{bol}/\mathrm{erg s{-1}} \gtrsim 45.5$. The simulation reproduces the observed clustering across $0 \lesssim z \lesssim 3$, and the reduced luminosity dependence introduced by scatter aligns with observational trends. However, it underpredicts the clustering strength at $z \approx 4$, consistent with other models and possibly reflecting high-redshift observational uncertainties.

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