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Abstract From the luminous quasars atz∼ 6 to the recentz∼ 9–11 active galactic nuclei (AGN) revealed by JWST, observations of the earliest black hole (BH) populations can provide unique constraints on BH evolution. We use theBRAHMAsimulations with constrained initial conditions to investigate BH assembly in extreme overdense regions. The simulations implement heavy ∼10⁴–10⁵M_⊙seeds forming in dense, metal-poor gas exposed to sufficient Lyman–Werner flux. With gas accretion modeled via the Bondi–Hoyle formalism and BH dynamics with a subgrid dynamical friction scheme, we isolate the impact of seeding, dynamics, accretion, and feedback on BH evolution. With fiducial stellar and AGN feedback inherited fromIllustrisTNG, accretion is suppressed atz≳ 9, leaving mergers as the dominant growth channel. Gas accretion dominates atz≲ 9, where permissive models (super-Eddington or low radiative efficiency) build ∼10⁹M_⊙BHs powering quasars byz∼ 6, while stricterIllustrisTNG-based prescriptions yield much smaller BHs (∼10⁶–10⁸M_⊙). Our seed models strongly affect mergers atz≳ 9: only the most lenient models (with ∼10⁵M_⊙seeds) produce enough BH mergers to reach ≳10⁶M_⊙byz∼ 10, consistent with current estimates for GN-z11. Our dynamical friction model gives low merger efficiencies. Therefore, even in such extreme regions, we are unable to produce ≳10⁷M_⊙BHs byz∼ 9–10, as currently inferred for GHZ9, UHZ1, and CAPERS-LRD-z9. If the BH-to-stellar mass ratios of these sources are indeed so extreme, they would require either very short BH merger timescales or reduced AGN thermal feedback. Weaker stellar feedback boosts both star formation and BH accretion and cannot raise these ratios. 

Abstract Recent pulsar timing array (PTA) observations detected nanohertz gravitational waves, likely originating from massive black hole binaries (MBHBs). The detected amplitude is unexpectedly higher than inferred from the electromagnetic measurements. We present new gravitational-wave background (GWB) results from the ASTRID simulation. Its large volume and on-the-fly dynamics for massive black holes (MBHs) provide new insights into the MBHB population, offering a more accurate assessment of its contribution to the observed GWB. ASTRID predicts a GWB from MBHBs ofh_c = 2.8 × 10⁻¹⁵, or ∼45% of the observed amplitude at ∼4 nHz with a slope consistent withf^−2/3, andh_c = 2.5 × 10⁻¹⁶withh_c ∝ f^−1.6at ∼30 nHz. These predictions remain below current PTA constraints but align with empirical models based on the observed MBH mass functions. By comparison, TNG300 with postprocessed MBH dynamics yields a range between 70% and 90% (20% and 30%) of the observed levels at low (high) frequencies. At low frequencies, ASTRID predicts that the bulk of the GWB originates from MBHBs with massesM_tot = 1–3 × 10⁹M_⊙peaking atz ≈ 0.3, consistent with TNG300. Notably, both simulations predict significant contributions from minor mergers (q < 0.2) by up to ∼40%. By tracing the full merger trees of local MBHs in ASTRID, we show that they generate gravitational waves at ∼10%–80% of the maximum signal assuming no accretion and recent equal-mass mergers. Finally, we demonstrate the importance of on-the-fly MBH dynamics, the lack of which leads to 3–5 times excessive mass growth by merger, and a boost to the GWB prediction from this overestimated mass function, especially at high frequencies. 

Abstract We analyze the dynamics of low-mass black hole (BH) seeds in the high-redshift (z ≳ 5) Universe using a suite of [4.5 Mpc]³and [9 Mpc]³BRAHMAcosmological hydrodynamic simulations. The simulations form seeds with massM_seed = 2.2 × 10³M_⊙in halos that exceed critical thresholds of dense and metal-poor gas mass (5–150M_seed) and the halo mass (1000–10,000M_seed). While the initialBRAHMAboxes pinned the BHs to the halo centers, here we implement a subgrid dynamical friction (DF) model. We also compare simulations where the BH is allowed to wander without the added DF. We investigate the spatial and velocity offsets of BHs in their host subhalos, as well as BH merger rates. We find that subgrid DF is crucial to ensure that a significant fraction of BHs effectively sink to halo centers byz ∼ 5, thereby enabling them to get gravitationally bound and merge with other BHs at separations close to the spatial resolution (∼0.2–0.4 kpc) of the simulation. For the BHs that merge, the associated merger timescales lag between ∼100 and 1000 Myr after their host halos merge. Compared to predictions using BH repositioning, the overallz ≳ 5 BH merger rates under subgrid DF decrease by a factor of ∼4–10. Under subgrid DF, the different seed models predict merger rates between ∼100 and 1000 events per year atz ≳ 5. These mergers dominate early BH growth, assembling BHs up to ∼10⁴–10⁵M_⊙byz ∼ 5, wherein ≲2% of their mass is assembled via gas accretion. Our results highlight the promise for constraining seeding mechanisms using gravitational waves from future facilities such as the Laser Interferometer Space Antenna. 

Abstract We study the coevolution of black holes (BHs) and their host galaxies in the ASTRIDandTNG300cosmological simulations and the DARKSAGEsemianalytic model (SAM), focusing on the evolution of the BH mass–stellar mass (M_BH–M_*) relation. Due to differences in the adopted subgrid modeling of BH seeding, dynamics, and feedback, the models differ in their predicted redshift evolution of theM_BH–M_*relation. We find that it is the interplay between the star formation rate (SFR) and the black hole accretion rate (BHAR) that drives the evolution of the mean relation. We define a quantity $\mathcal{R}$, the ratio between the specific BHAR and SFR (i.e., $\mathcal{R}\equiv$sBHAR/sSFR), and demonstrate that it is $\mathcal{R}$that governs the evolution of individual sources in theM_BH–M_*plane. The efficiency of BH growth versus stellar mass growth in the sSFR–sBHAR plane reflects the partitioning of gas between fueling star formation versus BH accretion. This partitioning depends on the implementation of BH dynamics and the nature of how black hole feedback quenches galaxies. In the cosmological simulations (ASTRIDandTNG300), the BHAR and SFR are intrinsically linked, resulting in a tightM_BH–M_*correlation, while the DARKSAGESAM produces a significantly larger scatter. We discuss these results in the context of recently discovered overmassive BHs and massive quenched galaxies at high redshift by the James Webb Space Telescope. 

Abstract We present an analysis searching for dual active galactic nuclei (AGN) among 62 high-redshift (2.5 <z< 3.5) X-ray sources selected from the X-UDS, AEGIS-XD, CDF-S, and COSMOS-Legacy Chandra surveys. We aim to quantify the frequency of dual AGN in the high-redshift Universe, which holds implications for black hole merger timescales and low-frequency gravitational wave detection rates. We analyze each X-ray source using BAYMAX, an analysis tool that calculates the Bayes factor for whether a given archival Chandra AGN is more likely a single or dual point source. We find no strong evidence for dual AGN in any individual source in our sample. We increase our sensitivity to search for dual AGN across the sample by comparing our measured distribution of Bayes factors to that expected from a sample composed entirely of single point sources and find no evidence for dual AGN in the sample distribution. Although our analysis utilizes one of the largest Chandra catalogs of high-zX-ray point sources available to study, the findings remain limited by the modest number of sources observed at the highest spatial resolution with Chandra and the typical count rates of the detected sources. Our nondetection allows us to place an upper limit on the X-ray dual AGN fraction at 2.5 <z< 3.5 of 4.8% at the 95% confidence level. Expanding substantially on these results at X-ray wavelengths will require future surveys spanning larger sky areas and extending to fainter fluxes than has been possible with Chandra. We illustrate the potential of the AXIS mission concept in this regard. 

Abstract We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2124 hydrodynamic simulation runs that vary three cosmological parameters (Ω_m,σ₈, Ω_b) and four parameters controlling stellar and active galactic nucleus (AGN) feedback. Compared to the existing TNG and SIMBA simulation suites in CAMELS, the fiducial model of ASTRID features the mildest AGN feedback and predicts the least baryonic effect on the matter power spectrum. The training set of ASTRID covers a broader variation in the galaxy populations and the baryonic impact on the matter power spectrum compared to its TNG and SIMBA counterparts, which can make machine-learning models trained on the ASTRID suite exhibit better extrapolation performance when tested on other hydrodynamic simulation sets. We also introduce extension simulation sets in CAMELS that widely explore 28 parameters in the TNG and SIMBA models, demonstrating the enormity of the overall galaxy formation model parameter space and the complex nonlinear interplay between cosmology and astrophysical processes. With the new simulation suites, we show that building robust machine-learning models favors training and testing on the largest possible diversity of galaxy formation models. We also demonstrate that it is possible to train accurate neural networks to infer cosmological parameters using the high-dimensional TNG-SB28 simulation set.