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arxiv: 2601.22213 · v2 · submitted 2026-01-29 · 🌌 astro-ph.GA

Little Red Dots on FIRE: The Ability of Bursty Galaxies to Host an Abundant Population of High-Redshift AGN

Pith reviewed 2026-05-16 09:24 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords little red dotshigh-redshift AGNFIRE-2 simulationsblack hole accretionbursty galaxiesJWST observationsgalaxy evolution at z greater than 4
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The pith

High-redshift bursty galaxies can produce enough AGN to explain the observed little red dots.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests whether galaxies in FIRE-2 simulations at z greater than or equal to 5 can sustain the abundant population of potential AGN known as little red dots. It applies a gravitational torque-driven accretion model and a free-fall accretion model to track black hole growth from central gas supplies and builds predicted bolometric luminosity functions. Both models yield AGN numbers that meet or exceed the latest observations, though the fiducial versions overproduce faint sources. The authors propose that the observed LRDs correspond to super-Eddington accreting black holes above roughly 200,000 solar masses inside galaxies above roughly 20 million solar masses. This framework shows that episodic gas supply in bursty systems is still adequate for the required black hole activity.

Core claim

Galaxies drawn from high-redshift FIRE-2 simulations host AGN abundances that are more than sufficient to account for the observed little red dots when black holes accrete according to the gravitational torque-driven accretion prescription or according to a free-fall model in which they consume at most one percent of their central gas reservoir per free-fall time. The same models overpredict the number of low-luminosity AGN, a tension that is eased if the little red dots are instead identified with super-Eddington accreting, Eddington-luminosity-limited black holes whose masses exceed 2 times 10 to the 5 solar masses and that sit inside galaxies whose stellar masses exceed 2 times 10 to the

What carries the argument

Gravitational torque-driven accretion (GTDA) model and free-fall accretion model applied to the central gas supply within 100 parsecs of simulated galaxies.

If this is right

  • The GTDA model produces AGN abundances well above those needed to match LRD counts at z=5-7.
  • The free-fall model with accretion capped at one percent of central gas per free-fall time likewise supplies more than enough AGN.
  • Mock images of the proposed super-Eddington sources reproduce the key photometric and color properties reported for LRDs.
  • The overprediction at low luminosities implies that either accretion is throttled or that current surveys miss a large fraction of faint AGN.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the proposed mass thresholds hold, the typical LRD host galaxy must already contain a black hole seed that grew rapidly before z=7.
  • The same accretion physics may set the minimum galaxy mass that can sustain observable AGN at still higher redshifts.
  • Future deep surveys that separate host-galaxy UV light from nuclear emission could directly test whether the stellar-mass cut at 2 times 10 to the 7 solar masses is required.

Load-bearing premise

The chosen accretion efficiency of at most one percent per free-fall time or the torques in the GTDA model correctly describe how black holes actually draw gas in these bursty galaxies.

What would settle it

A direct count of AGN at z equals 5 to 7 that falls well below the predicted luminosity function even after imposing the super-Eddington, Eddington-limited threshold on black holes more massive than 2 times 10 to the 5 solar masses.

Figures

Figures reproduced from arXiv: 2601.22213 by Andrew Marszewski, Claude-Andr\'e Faucher-Gigu\`ere, Daniel Angl\'es-Alc\'azar, Guochao Sun, Kung-Yi Su, Niranjan Chandra Roy, Robert Feldmann, Tim B. Miller.

Figure 1
Figure 1. Figure 1: Predicted black hole accretion rates using the gravitational torque-driven accretion (GTDA) model (solid lines) and the free-fall accretion model with εff = 0.001 (dashed lines) for three example host galaxies in our sample with M⋆(z = 5) ∼ 106 (purple), 108 (green), and 1010 (orange) M⊙ for z = 5 − 7. The horizontal axis shows cosmic time. Bursty stellar feedback in FIRE-2 (and in many other high-resoluti… view at source ↗
Figure 2
Figure 2. Figure 2: The AGN bolometric luminosity function predicted at z ∼ 6 using the GTDA model (blue with stars) and the simple free-fall accretion model (dark red with circles) with ε¯ff = 1 (solid), 0.1 (dashed), 0.01 (dot-dashed), and 0.001 (dotted). Curves show the median luminosity function predicted from our 1000 bootstrapped samples; shaded regions enclose the 16th–84th percentile range. Here, our fiducial aperture… view at source ↗
Figure 3
Figure 3. Figure 3: The predicted z ∼ 6 AGN bolometric luminosity function from FIRE-2 simulations using the GTDA model (left panel) and the simple free-fall accretion model (right panel). To model unresolved time variability, we apply log-normally distributed values of the normalization (ϵ¯T = 5) for the GTDA model and the accretion efficiency (ε¯ff=0.01) for the simple free-fall model with σlog(ϵ) = 0 (dark blue), 0.25 (blu… view at source ↗
Figure 4
Figure 4. Figure 4: The predicted z ∼ 6 AGN bolometric luminosity function (top) and UVLF for galaxies hosting an AGN in the LRD luminosity bins (LBol ∼ 1043−45 erg/s; bottom) using the GTDA model (left) and the simple free-fall accretion model (right). Galaxies only contribute to the UVLFs plotted in the bottom panels if they are predicted (by the model plotted) to host an AGN in the range LBol = 1042.5−45.5 erg/s. Since not… view at source ↗
Figure 5
Figure 5. Figure 5: The stellar mass distribution of FIRE-2 galaxies hosting AGN in luminosity bins centered at LBol ∼ 1043 (purple), 1044 (blue), 1045 (green), and 1046 (yellow) erg/s for our fiducial models (including unmodified LBol values for AGN in all galaxies; top) and our “Plausible LRD Scenario" (as in [PITH_FULL_IMAGE:figures/full_fig_p012_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: The predicted z ∼ 6 AGN bolometric luminosity function using the GTDA model (left panel) and the simple free-fall accretion model (right panel) calculated using different radial apertures of R = 20 (dark blue), 50 (purple), 100 (magenta), 200 (red), 500 (orange), and 1000 (yellow) pc. Shaded regions represent the range between the 16th and 84th percentile luminosity functions predicted from our bootstrappe… view at source ↗
Figure 7
Figure 7. Figure 7: The predicted z ∼ 6 AGN bolometric luminosity function assuming different MBH −M⋆ scaling relations for the cases where the luminosities of AGN are capped at their predicted LEdd (top) and where we only include super-Eddington accretors whose luminosities are still capped at LEdd (bottom) using the GTDA model (left) and the simple free-fall accretion model (right). We present the cases where galaxies of an… view at source ↗
Figure 8
Figure 8. Figure 8: The predicted z ∼ 6 UVLF for galaxies hosting an AGN in the LRD luminosity bins (LBol ∼ 1043−45 erg/s) using the GTDA model (left) and the simple free-fall accretion model (right) using our fiducial dust model from Donnan et al. (2025) (top) and a dust-free model (bottom). Galaxies only contribute to the UVLFs if they are predicted (by the model plotted) to host an AGN in the range LBol = 1042.5−45.5 erg/s… view at source ↗
read the original abstract

The James Webb Space Telescope has unveiled an abundant population of potential active galactic nuclei (AGN) at high redshift ($z\gtrsim4$) known as little red dots (LRDs), which are likely hosted in relatively low-mass galaxies. However, previous theoretical models have highlighted the difficulty in continuously feeding massive black holes in the central regions of bursty, high-redshift galaxies because of repeated gas evacuation by stellar feedback. We analyze galaxies in high-redshift FIRE-2 simulations to understand whether they are capable of hosting the observed abundant population of high-redshift AGN. We use a gravitational torque-driven accretion (GTDA) model and a simple free-fall accretion model to derive black hole accretion rates and construct predicted AGN bolometric luminosity functions for $z=5-7$. The GTDA model and the free-fall model with black holes accreting $\lesssim 1$ percent of their central gas supply ($<100 \rm \ pc$) per free-fall time predict AGN abundances that are more than sufficient to explain the most recent LRD observations. The fiducial models, in fact, overpredict the number of low-luminosity AGN as compared with observations. We explore possible resolutions of this tension. A plausible, though likely not unique, scenario for alleviating the AGN overpredictions and which also provides a good match to the host-galaxy UV luminosity distribution suggests that LRDs are super Eddington-accreting, Eddington luminosity-limited, $M_{\rm BH}\gtrsim 2\times10^5 \ \rm M_\odot$ black holes residing in $M_\star\gtrsim 2\times10^7 \ \rm M_\odot$ galaxies. We show that, under simple assumptions, mock observations of such sources can reproduce key observed LRD characteristics.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper analyzes high-redshift galaxies from FIRE-2 simulations to assess their ability to host abundant AGN populations observed as little red dots (LRDs) by JWST. Using gravitational torque-driven accretion (GTDA) and free-fall accretion models applied to central gas within <100 pc, it finds that these models predict AGN abundances sufficient to explain LRD observations at z=5-7, though fiducial models overpredict low-luminosity AGN. The authors propose that LRDs correspond to super-Eddington accreting but Eddington-luminosity-limited black holes with M_BH ≳ 2×10^5 M_⊙ in galaxies with M_* ≳ 2×10^7 M_⊙, which also matches host UV luminosities and reproduces key observed LRD characteristics under simple mock-observation assumptions.

Significance. If the post-processed accretion prescriptions hold, the work shows that bursty high-redshift galaxies in FIRE-2 can host the observed LRD population, providing a theoretical basis for abundant high-z AGN in low-mass hosts without requiring continuous gas feeding. The explicit comparison to recent LRD counts and the construction of mock observations that recover key LRD traits are concrete strengths.

major comments (3)
  1. [§3 (Accretion Models) and §4.1 (Predicted Luminosity Functions)] The GTDA and free-fall models are applied as post-processing to FIRE-2 runs that contain only stellar feedback and no black-hole particles or AGN energy injection. Consequently the central gas reservoirs within <100 pc are not self-regulated by the accretion events being modeled; AGN feedback would be expected to heat or expel gas on these scales and lower the instantaneous supply, reducing predicted bolometric luminosities. This directly affects the reported overprediction of faint AGN and the need for subsequent mass thresholds.
  2. [§4.3 (Resolving the Overprediction) and §5 (Discussion)] The favored scenario that alleviates the overprediction imposes M_BH ≳ 2×10^5 M_⊙, M_* ≳ 2×10^7 M_⊙, and an Eddington cap on super-Eddington accretion. These thresholds are selected because they produce a match to observed LRD number densities and host UV luminosities; the paper should demonstrate that they follow from independent physical arguments rather than being tuned parameters.
  3. [§3.2 (Free-fall Accretion Model)] The free-fall model adopts an accretion efficiency of ≲1 % of the central gas supply per free-fall time. The text does not show how this specific fraction is motivated by resolved simulations or analytic theory, nor whether it remains constant across the range of galaxy masses and redshifts examined.
minor comments (2)
  1. [Figure 3] Figure 3 (or equivalent luminosity-function panels) would benefit from explicit shading or error bands indicating the range of accretion efficiencies explored, to clarify how sensitive the overprediction is to the 1 % choice.
  2. [Abstract and §4.1] The abstract states that the models 'predict AGN abundances that are more than sufficient'; the main text should quantify this statement with the factor by which the fiducial models exceed the observed LRD counts before the mass cuts are applied.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their thoughtful and constructive comments on our manuscript. We address each major comment below and indicate the revisions made to the manuscript.

read point-by-point responses
  1. Referee: [§3 (Accretion Models) and §4.1 (Predicted Luminosity Functions)] The GTDA and free-fall models are applied as post-processing to FIRE-2 runs that contain only stellar feedback and no black-hole particles or AGN energy injection. Consequently the central gas reservoirs within <100 pc are not self-regulated by the accretion events being modeled; AGN feedback would be expected to heat or expel gas on these scales and lower the instantaneous supply, reducing predicted bolometric luminosities. This directly affects the reported overprediction of faint AGN and the need for subsequent mass thresholds.

    Authors: We agree that the post-processing approach omits self-regulation by AGN feedback, which is a genuine limitation of the current study. AGN feedback would be expected to reduce central gas densities and thus lower the predicted luminosities, especially at the faint end. In the revised manuscript we have expanded the discussion in Section 5 to explicitly note this caveat and to state that the fiducial predictions represent upper limits in the absence of AGN feedback. We retain the argument that stellar feedback already drives the bursty gas dynamics captured in FIRE-2, and that the proposed mass thresholds provide a practical resolution to the overprediction. A fully self-consistent simulation that includes AGN feedback lies beyond the scope of this work. revision: partial

  2. Referee: [§4.3 (Resolving the Overprediction) and §5 (Discussion)] The favored scenario that alleviates the overprediction imposes M_BH ≳ 2×10^5 M_⊙, M_* ≳ 2×10^7 M_⊙, and an Eddington cap on super-Eddington accretion. These thresholds are selected because they produce a match to observed LRD number densities and host UV luminosities; the paper should demonstrate that they follow from independent physical arguments rather than being tuned parameters.

    Authors: The referee correctly observes that the specific thresholds were chosen to reproduce the observed LRD abundances and host UV luminosities. While these values are informed by physical considerations such as the minimum black-hole mass at which AGN signatures become observable in low-mass galaxies and the stellar-mass range of JWST-detected LRD hosts, they are not derived from first-principles calculations internal to the simulation. In the revised manuscript we have strengthened the justification in Sections 4.3 and 5 by adding references to high-redshift black-hole–stellar-mass relations and by noting that lower-mass black holes are expected to fall below the luminosity threshold for LRD classification. We continue to present the scenario as plausible rather than uniquely determined. revision: yes

  3. Referee: [§3.2 (Free-fall Accretion Model)] The free-fall model adopts an accretion efficiency of ≲1 % of the central gas supply per free-fall time. The text does not show how this specific fraction is motivated by resolved simulations or analytic theory, nor whether it remains constant across the range of galaxy masses and redshifts examined.

    Authors: The ≲1 % efficiency was adopted to produce accretion rates broadly consistent with the GTDA model while remaining plausible given unresolved sub-parsec physics. In the revised manuscript we have added a paragraph in Section 3.2 that motivates this fraction with references to resolved hydrodynamic simulations of black-hole accretion and analytic estimates of angular-momentum barriers and local feedback. We also discuss the assumption of a constant efficiency and note that mass- or redshift-dependent variations could be explored in future work. revision: yes

Circularity Check

0 steps flagged

No significant circularity; forward modeling from simulation gas properties

full rationale

The paper applies GTDA and free-fall accretion prescriptions to central gas masses extracted from existing FIRE-2 simulation snapshots (which include only stellar feedback) to compute accretion rates, bolometric luminosities, and luminosity functions at z=5-7. These outputs are then compared to LRD observations. The 1% efficiency, mass thresholds, and Eddington cap are explicit model parameters explored to address overprediction, but the core derivation computes new quantities (accretion rates and LFs) from the simulated gas distributions rather than re-expressing the inputs or fitting in a self-referential loop. No load-bearing step reduces by construction to a prior self-citation or tautological redefinition; the chain remains a standard post-processing forward model.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The analysis rests on the FIRE-2 subgrid physics for stellar feedback and gas dynamics plus two simple analytic accretion prescriptions whose efficiency is adjusted to observations.

free parameters (2)
  • accretion fraction per free-fall time
    Set to ≲1% to produce sufficient AGN while exploring overprediction resolution.
  • minimum black hole and galaxy masses
    M_BH >= 2e5 Msun and M_star >= 2e7 Msun chosen to match LRD and UV distributions.
axioms (2)
  • domain assumption FIRE-2 simulation accurately captures bursty star formation and stellar feedback at high redshift
    Invoked throughout to justify gas evacuation and central gas supply estimates.
  • domain assumption Gravitational torque-driven accretion and free-fall prescriptions are valid for central gas dynamics
    Used to convert simulated gas properties into black hole accretion rates.

pith-pipeline@v0.9.0 · 5680 in / 1481 out tokens · 50014 ms · 2026-05-16T09:24:10.700071+00:00 · methodology

discussion (0)

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Forward citations

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Works this paper leans on

73 extracted references · 73 canonical work pages · cited by 1 Pith paper · 4 internal anchors

  1. [1]

    B., Casey, C

    Akins, H. B., Casey, C. M., Lambrides, E., et al. 2025, ApJ, 991, 37, doi: 10.3847/1538-4357/ade984

  2. [2]

    T., Bogd´ an,´A., Kov´ acs, O

    Ananna, T. T., Bogdán, Á., Kovács, O. E., Natarajan, P., & Hickox, R. C. 2024, ApJL, 969, L18, doi: 10.3847/2041-8213/ad5669 Anglés-Alcázar, D., Davé, R., Faucher-Giguère, C.-A., Özel, F., & Hopkins, P. F. 2017a, MNRAS, 464, 2840, doi: 10.1093/mnras/stw2565 Anglés-Alcázar, D., Faucher-Giguère, C.-A., Quataert, E., et al. 2017b, MNRAS, 472, L109, doi: 10.1...

  3. [3]

    Baggen, J. F. W., van Dokkum, P., Brammer, G., et al. 2024, ApJL, 977, L13, doi: 10.3847/2041-8213/ad90b8

  4. [4]

    G., Kocevski, D

    Barro, G., Pérez-González, P. G., Kocevski, D. D., et al. 2024, ApJ, 963, 128, doi: 10.3847/1538-4357/ad167e

  5. [5]

    The Average Star Formation Histories of Galaxies in Dark Matter Halos from z=0-8

    Behroozi, P. S., Wechsler, R. H., & Conroy, C. 2013, ApJ, 770, 57, doi: 10.1088/0004-637X/770/1/57

  6. [6]

    G., Schaye, J., Frenk, C

    Bower, R. G., Schaye, J., Frenk, C. S., et al. 2017, MNRAS, 465, 32, doi: 10.1093/mnras/stw2735

  7. [7]

    2023, MNRAS, 520, 722, doi: 10.1093/mnras/stad171

    Byrne, L., Faucher-Giguère, C.-A., Stern, J., et al. 2023, MNRAS, 520, 722, doi: 10.1093/mnras/stad171

  8. [8]

    2024, The Astrophysical Journal, 973, 149, doi: 10.3847/1538-4357/ad67ca

    Byrne, L., Faucher-Giguère, C.-A., Wellons, S., et al. 2024, ApJ, 973, 149, doi: 10.3847/1538-4357/ad67ca

  9. [9]

    M., Akins, H

    Casey, C. M., Akins, H. B., Finkelstein, S. L., et al. 2025, ApJL, 990, L61, doi: 10.3847/2041-8213/adfa91 Çatmabacak, O., Feldmann, R., Anglés-Alcázar, D., et al. 2022, MNRAS, 511, 506, doi: 10.1093/mnras/stac040

  10. [10]

    E., et al

    Dayal, P., Volonteri, M., Greene, J. E., et al. 2025, A&A, 697, A211, doi: 10.1051/0004-6361/202449331 de Graaff, A., Rix, H.-W., Naidu, R. P., et al. 2025, A&A, 701, A168, doi: 10.1051/0004-6361/202554681

  11. [11]

    T., Dunlop J

    Donnan, C. T., Dunlop, J. S., McLure, R. J., McLeod, D. J., & Cullen, F. 2025, MNRAS, 539, 2409, doi: 10.1093/mnras/staf641

  12. [12]

    2015, MNRAS, 452, 1502, doi: 10.1093/mnras/stv1416

    Dubois, Y., Volonteri, M., Silk, J., et al. 2015, MNRAS, 452, 1502, doi: 10.1093/mnras/stv1416

  13. [13]

    S., et al

    Feldmann, R., Boylan-Kolchin, M., Bullock, J. S., et al. 2025, MNRAS, 536, 988, doi: 10.1093/mnras/stae2633

  14. [14]

    J., Labb´ e, I., Zitrin, A., et al

    Furtak, L. J., Labbé, I., Zitrin, A., et al. 2024, Nature, 628, 57, doi: 10.1038/s41586-024-07184-8

  15. [15]

    J., Secunda, A

    Furtak, L. J., Secunda, A. R., Greene, J. E., et al. 2025, A&A, 698, A227, doi: 10.1051/0004-6361/202554110

  16. [16]

    , keywords =

    Greene, J. E., Labbe, I., Goulding, A. D., et al. 2024, ApJ, 964, 39, doi: 10.3847/1538-4357/ad1e5f

  17. [17]

    E., Setton, D

    Greene, J. E., Setton, D. J., Furtak, L. J., et al. 2025, arXiv e-prints, arXiv:2509.05434, doi: 10.48550/arXiv.2509.05434

  18. [18]

    2017, MNRAS, 468, 3935, doi: 10.1093/mnras/stx666

    Habouzit, M., Volonteri, M., & Dubois, Y. 2017, MNRAS, 468, 3935, doi: 10.1093/mnras/stx666

  19. [19]

    , keywords =

    Habouzit, M., Li, Y., Somerville, R. S., et al. 2021, MNRAS, 503, 1940, doi: 10.1093/mnras/stab496

  20. [20]

    2023, ApJ, 959, 39, doi: 10.3847/1538-4357/ad029e

    Harikane, Y., Zhang, Y., Nakajima, K., et al. 2023, ApJ, 959, 39, doi: 10.3847/1538-4357/ad029e

  21. [21]

    Hopkins, P. F. 2015, MNRAS, 450, 53, doi: 10.1093/mnras/stv195

  22. [22]

    F., Grudic, M

    Hopkins, P. F., Grudic, M. Y., Kremer, K., et al. 2024a, The Open Journal of Astrophysics, 7, 71, doi: 10.33232/001c.122857

  23. [23]
  24. [24]
  25. [25]

    F., Wetzel, A., Kereˇ s, D., et al

    Hopkins, P. F., Wetzel, A., Kereš, D., et al. 2018, MNRAS, 480, 800, doi: 10.1093/mnras/sty1690

  26. [26]

    F., Wetzel, A., Wheeler, C., et al

    Hopkins, P. F., Wetzel, A., Wheeler, C., et al. 2023, MNRAS, 519, 3154, doi: 10.1093/mnras/stac3489

  27. [27]

    The Open Journal of Astrophysics , keywords =

    Hopkins, P. F., Grudic, M. Y., Su, K.-Y., et al. 2024b, The Open Journal of Astrophysics, 7, 18, doi: 10.21105/astro.2309.13115

  28. [28]

    The Open Journal of Astrophysics , keywords =

    Hopkins, P. F., Squire, J., Su, K.-Y., et al. 2024c, The Open Journal of Astrophysics, 7, 19, doi: 10.21105/astro.2310.04506

  29. [29]

    E., de Graaff, A., Miller, T

    Hviding, R. E., de Graaff, A., Miller, T. B., et al. 2025, arXiv e-prints, arXiv:2506.05459, doi: 10.48550/arXiv.2506.05459

  30. [30]

    , keywords =

    Inayoshi, K., Kimura, S. S., & Noda, H. 2025a, PASJ, 77, 811, doi: 10.1093/pasj/psaf050 15

  31. [31]

    2025, ApJL, 980, L27, doi: 10.3847/2041-8213/adaebd

    Inayoshi, K., & Maiolino, R. 2025, ApJL, 980, L27, doi: 10.3847/2041-8213/adaebd

  32. [32]

    Spectral Uniformity of Little Red Dots: A Natural Outcome of Coevolving Seed Black Holes and Nascent Starbursts

    Inayoshi, K., Murase, K., & Kashiyama, K. 2025b, arXiv e-prints, arXiv:2509.19422, doi: 10.48550/arXiv.2509.19422

  33. [33]

    M., & Davis, S

    Jiang, Y.-F., Stone, J. M., & Davis, S. W. 2014, ApJ, 796, 106, doi: 10.1088/0004-637X/796/2/106

  34. [34]

    , keywords =

    Killi, M., Watson, D., Brammer, G., et al. 2024, A&A, 691, A52, doi: 10.1051/0004-6361/202348857

  35. [35]

    R., & Knebe, A

    Knollmann, S. R., & Knebe, A. 2009, ApJS, 182, 608, doi: 10.1088/0067-0049/182/2/608

  36. [36]

    , keywords =

    Kocevski, D. D., Finkelstein, S. L., Barro, G., et al. 2025, ApJ, 986, 126, doi: 10.3847/1538-4357/adbc7d

  37. [37]

    2023, ApJL, 957, L7, doi: 10.3847/2041-8213/ad037a

    Kokorev, V., Fujimoto, S., Labbe, I., et al. 2023, ApJL, 957, L7, doi: 10.3847/2041-8213/ad037a

  38. [38]

    I., Greene, J

    Kokorev, V., Caputi, K. I., Greene, J. E., et al. 2024, ApJ, 968, 38, doi: 10.3847/1538-4357/ad4265

  39. [39]

    arXiv e-prints , keywords =

    Kokorev, V., Chisholm, J., Naidu, R. P., et al. 2025, arXiv e-prints, arXiv:2511.07515, doi: 10.48550/arXiv.2511.07515 Labbé, I., van Dokkum, P., Nelson, E., et al. 2023, Nature, 616, 266, doi: 10.1038/s41586-023-05786-2

  40. [40]

    E., Bezanson, R., et al

    Labbe, I., Greene, J. E., Bezanson, R., et al. 2025, ApJ, 978, 92, doi: 10.3847/1538-4357/ad3551

  41. [41]

    2021, MNRAS, 505, 172, doi: 10.1093/mnras/stab1205

    Lapiner, S., Dekel, A., & Dubois, Y. 2021, MNRAS, 505, 172, doi: 10.1093/mnras/stab1205

  42. [42]

    2024, A&A, 689, A128, doi: 10.1051/0004-6361/202451249

    Mazzucchelli, C. 2024, A&A, 689, A128, doi: 10.1051/0004-6361/202451249

  43. [43]

    F., Ma, X., et al

    Ma, L., Hopkins, P. F., Ma, X., et al. 2021, MNRAS, 508, 1973, doi: 10.1093/mnras/stab2713

  44. [44]

    F., Boylan-Kolchin, M., et al

    Ma, X., Hopkins, P. F., Boylan-Kolchin, M., et al. 2018a, MNRAS, 477, 219, doi: 10.1093/mnras/sty684

  45. [45]

    F., Garrison-Kimmel, S., et al

    Ma, X., Hopkins, P. F., Garrison-Kimmel, S., et al. 2018b, MNRAS, 478, 1694, doi: 10.1093/mnras/sty1024

  46. [46]

    C., Casey, C

    Ma, X., Hayward, C. C., Casey, C. M., et al. 2019, MNRAS, 487, 1844, doi: 10.1093/mnras/stz1324

  47. [47]

    2025, arXiv e-prints, arXiv:2501.09854, doi: 10.48550/arXiv.2501.09854

    Madau, P. 2025, arXiv e-prints, arXiv:2501.09854, doi: 10.48550/arXiv.2501.09854

  48. [48]

    , keywords =

    Madau, P., & Haardt, F. 2024, ApJL, 976, L24, doi: 10.3847/2041-8213/ad90e1

  49. [49]

    , keywords =

    Maiolino, R., Risaliti, G., Signorini, M., et al. 2025, MNRAS, 538, 1921, doi: 10.1093/mnras/staf359

  50. [50]

    2025, arXiv e-prints, arXiv:2505.22712, doi: 10.48550/arXiv.2505.22712

    Sun, G. 2025, arXiv e-prints, arXiv:2505.22712, doi: 10.48550/arXiv.2505.22712

  51. [51]

    C., & Feldmann, R

    Marszewski, A., Sun, G., Faucher-Giguère, C.-A., Hayward, C. C., & Feldmann, R. 2024, ApJL, 967, L41, doi: 10.3847/2041-8213/ad4cee

  52. [52]

    P., Brammer, G., et al

    Matthee, J., Naidu, R. P., Brammer, G., et al. 2024, ApJ, 963, 129, doi: 10.3847/1538-4357/ad2345

  53. [53]

    P., Kotiwale, G., et al

    Matthee, J., Naidu, R. P., Kotiwale, G., et al. 2025, ApJ, 988, 246, doi: 10.3847/1538-4357/ade886

  54. [54]

    G., Power , C., & Robotham , A

    Murray, S. G., Power, C., & Robotham, A. S. G. 2013, Astronomy and Computing, 3, 23, doi: 10.1016/j.ascom.2013.11.001

  55. [55]

    A "Black Hole Star" Reveals the Remarkable Gas-Enshrouded Hearts of the Little Red Dots

    Naidu, R. P., Matthee, J., Katz, H., et al. 2025, arXiv e-prints, arXiv:2503.16596, doi: 10.48550/arXiv.2503.16596

  56. [56]

    D., & Thorne, K

    Novikov, I. D., & Thorne, K. S. 1973, in Black Holes (Les Astres Occlus), ed. C. DeWitt & B. S. DeWitt (New York: Gordon and Breach), 343–450

  57. [57]

    2002, ApJ, 574, 315, doi: 10.1086/340798

    Ohsuga, K., Mineshige, S., Mori, M., & Umemura, M. 2002, ApJ, 574, 315, doi: 10.1086/340798

  58. [58]

    N., & Thorne, K

    Page, D. N., & Thorne, K. S. 1974, Astrophysical Journal, 191, 499, doi: 10.1086/152990

  59. [59]

    Perger, K., Fogasy, J., Frey, S., & Gabányi, K. É. 2025, A&A, 693, L2, doi: 10.1051/0004-6361/202452422

  60. [60]

    F., Schaye, J., et al

    Pizzati, E., Hennawi, J. F., Schaye, J., et al. 2025, MNRAS, 539, 2910, doi: 10.1093/mnras/staf660

  61. [61]

    C., Anglés-Alcázar, D., Cochrane, R

    Roy, N. C., Anglés-Alcázar, D., Cochrane, R. K., et al. 2026, in prep

  62. [62]

    P., et al

    Rusakov, V., Watson, D., Nikopoulos, G. P., et al. 2026, Nature, 649, 574, doi: 10.1038/s41586-025-09900-4

  63. [63]

    J., Greene, J

    Setton, D. J., Greene, J. E., Spilker, J. S., et al. 2025, ApJL, 991, L10, doi: 10.3847/2041-8213/ade78b

  64. [64]

    F., Faucher-Gigu` ere, C.-A., et al

    Shen, X., Hopkins, P. F., Faucher-Giguère, C.-A., et al. 2020, MNRAS, 495, 3252, doi: 10.1093/mnras/staa1381 Sądowski, A., Narayan, R., McKinney, J. C., &

  65. [65]

    2014, MNRAS, 439, 503, doi: 10.1093/mnras/stt2479

    Tchekhovskoy, A. 2014, MNRAS, 439, 503, doi: 10.1093/mnras/stt2479

  66. [66]

    Sotan , title =

    Soltan, A. 1982, MNRAS, 200, 115, doi: 10.1093/mnras/200.1.115

  67. [67]

    R., & Eldridge, J

    Stanway, E. R., & Eldridge, J. J. 2018, MNRAS, 479, 75, doi: 10.1093/mnras/sty1353

  68. [68]

    C., et al

    Sun, G., Faucher-Giguère, C.-A., Hayward, C. C., et al. 2023, ApJL, 955, L35, doi: 10.3847/2041-8213/acf85a

  69. [69]

    2017, ApJ, 849, 155, doi: 10.3847/1538-4357/aa93f1

    Trebitsch, M. 2017, ApJ, 849, 155, doi: 10.3847/1538-4357/aa93f1

  70. [70]

    F., et al

    Wellons, S., Faucher-Giguère, C.-A., Hopkins, P. F., et al. 2023, MNRAS, 520, 5394, doi: 10.1093/mnras/stad511

  71. [71]

    and LeBlanc , F

    Yu, Q., & Tremaine, S. 2002, MNRAS, 335, 965, doi: 10.1046/j.1365-8711.2002.05532.x

  72. [72]

    , keywords =

    Yue, M., Eilers, A.-C., Ananna, T. T., et al. 2024, ApJL, 974, L26, doi: 10.3847/2041-8213/ad7eba

  73. [73]

    Global Fit A

    Zhang, L., Stone, J. M., Mullen, P. D., et al. 2025, ApJ, 995, 26, doi: 10.3847/1538-4357/ae0f91 16 ACKNOWLEDGMENTS AM was supported by a CIERA Board of Visitors Fellowship. CAFG was supported by NSF through grants AST- 2108230 and AST-2307327; by NASA through grants 80NSSC22K1124, 21-ATP21-0036 and 23-ATP23-0008; by STScI through grant JWST-AR-03252.001-...