Pith. sign in

REVIEW 2 major objections 4 minor 65 references

Stalled dust-poor gas hides early black holes from X-rays

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

Low-metallicity, dust-poor gas stalls under weak radiation pressure and blocks X-rays, explaining the X-ray weakness of early JWST-detected AGN.

T0 review reviewed 2026-08-05 challenge →

load-bearing objection A credible, mostly hypothesis-generating application of the dusty Eddington framework to JWST X-ray weak AGN; the central claim hinges on one empirical scaling that may not hold in these environments. the 2 major comments →

arxiv 2509.05423 v1 pith:DETNZHSH submitted 2025-09-05 astro-ph.GA astro-ph.HE

Another view into JWST-discovered X-ray weak AGNs via radiative dusty feedback

classification astro-ph.GA astro-ph.HE
keywords active galactic nucleiX-ray weak AGNJWST-AGNlittle red dotsradiative dusty feedbackeffective Eddington limitX-ray obscurationmetallicity
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The reading

The paper argues that the missing X-rays from JWST-discovered active galactic nuclei in the early universe are not proof that those black holes are intrinsically X-ray faint. Instead, it claims, low-metallicity gas with very little dust resists radiation pressure and lingers near the black hole, where it absorbs and scatters the X-rays. The authors trace this behaviour in the N_H–lambda plane, the boundary between gas that radiation pressure can eject and gas that stays as long-lived obscuration: lower metallicity and larger dust grains move that boundary to the right, enlarging the region where clouds survive. A separate blowout-versus-stalling calculation shows that the more massive the gas column, the higher the metallicity required to push it away, so heavy columns stall in metal-poor environments. If correct, the same stalled clouds would also account for Balmer absorption, weak radio emission, and the absence of ionised outflows in these sources.

Core claim

Within the radiative dusty feedback scenario, the effective Eddington limit for dust sets a critical curve in the column-density–Eddington-ratio (N_H–lambda) plane. To the left of this curve radiation pressure cannot expel the dusty gas, producing long-lived obscuration; to the right lies a 'forbidden' region where gas should be blown away. The paper's central claim is that the location of this curve depends sensitively on the dusty gas parameters, especially metallicity: because the dust-to-gas ratio scales with metallicity, low-metallicity gas has much weaker UV and IR dust opacities, shifting the boundary to the right. Consequently, dust-poor gas in the low-metallicity nuclear environment

What carries the argument

The central object is the effective Eddington ratio for dusty gas, Lambda = L(tau_IR + 1 - exp(-tau_UV))/(4 pi G c m_p M_BH N), balancing radiation pressure on dust against the black hole's gravity. Setting Lambda = 1 gives the critical column N_E = (tau_IR + 1 - exp(-tau_UV)) sigma_T / lambda, the boundary of the N_H–lambda plane that separates gas which is ejected (the forbidden region) from gas which survives as long-lived obscuration. The UV and IR dust opacities entering tau_UV and tau_IR depend on dust-to-gas ratio, grain size, grain density, and radiation temperature, and through the empirical dust-to-gas–metallicity relation they make the boundary a function of metallicity. For clump

Load-bearing premise

The argument depends on the empirical scaling between dust-to-gas ratio and metallicity, log f_dg = 1.30 [12+log(O/H)] - 13.72, holding in the high-redshift nuclear environments of JWST-AGN; if dust there is set by shock destruction, grain growth, or coagulation rather than by galaxy-wide metallicity, the boundary shifts and the stalling conclusion no longer follows.

What would settle it

If deep X-ray stacking of low-metallicity JWST-AGN at Eddington ratios above 0.1 shows transmitted 2–10 keV emission with column densities below 10^23 cm^-2, the stalled-gas explanation is contradicted; observing an Fe K-alpha fluorescence line consistent with cold, Compton-thick neutral gas at N_H greater than or equal to 10^24 cm^-2 would support the scenario.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • X-ray-weak JWST-AGN need not be powered by exotic super-Eddington accretion: long-lived dust-poor gas offers a physical absorption explanation consistent with the observed non-detections, even in stacked X-ray data.
  • Low metallicity makes radiative feedback self-limiting: the less dust there is, the harder it is for radiation pressure to clear the gas, so absorbing material accumulates and high covering fractions of Compton-thick clouds arise naturally.
  • Heavy gas columns stall preferentially in metal-poor environments, implying that the most heavily obscured early AGN should be found among the lowest-metallicity hosts.
  • The same stalled clouds can account for the co-occurrence of X-ray weakness, Balmer absorption (high-density gas), radio weakness (free-free absorption), and weak ionised outflows, tying several apparently unrelated JWST-AGN properties to one mechanism.
  • Locally, metal-poor dwarf galaxies hosting AGN may be useful analogs of early JWST-AGN, because low metallicity reproduces the same combination of X-ray and radio weakness and Balmer absorption.

Where Pith is reading between the lines

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

  • Inference: the scenario predicts a metallicity dependence of X-ray detection rates—if correct, the fraction of X-ray-detected JWST-AGN should rise with measured gas-phase metallicity, a testable trend in existing samples.
  • Inference: because the dust-to-gas–metallicity relation may break down locally, the model could be sharpened by measuring extinction-curve slopes and dust masses directly in these nuclei; a grey extinction curve with little small-grain content would support the large-grain assumption.
  • Inference: the same stalled gas reservoir would act as a persistent screen, perhaps suppressing optical/UV variability, and could keep feeding the black hole, connecting X-ray silence to a growth phase of early black holes.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 4 minor

Summary. The paper interprets the X-ray weakness of JWST-discovered AGN within the dusty radiative feedback scenario. It derives the effective Eddington limit for dusty gas and maps the critical boundary in the N_H−λ plane as a function of metallicity, grain size, grain composition, and radiation temperature (Sec. 2). It applies this to low-metallicity, large-grain circumnuclear gas, arguing that such dust-poor gas is hard to clear, accumulates, and produces long-lived heavy obscuration (Sec. 3). It analyzes the blowout/stalling condition for individual clouds (Sec. 4.1) and presents Monte-Carlo X-ray spectral simulations for Compton-thick, low-metallicity absorbers (Sec. 4.2). The discussion links the picture to Balmer absorption, radio weakness, and the absence of ionized outflows.

Significance. If the proposed scenario holds, it offers a single, physically motivated explanation for several peculiar JWST-AGN properties (X-ray weakness, Balmer absorption, radio weakness, weak [O III] outflows) in terms of low metallicity suppressing dust-radiation coupling. The analytical derivation is transparent and, apart from the adopted dust opacity model and the f_dg−Z calibration, contains no free parameters. The X-ray spectral simulations usefully show that even at Z=0.1−0.2 Z_sun, columns of 10^24−10^25 cm^-2 absorb most 2−20 keV flux. The authors are appropriately cautious in framing the proposal as suggestive rather than definitive. The main risk, which the paper itself partially acknowledges, is that the central conclusion is tied to the extrapolation of the local, galaxy-wide dust-to-gas vs metallicity relation to high-redshift nuclear gas.

major comments (2)
  1. [Section 2.1, Eq. (7)] Equation (7) as printed is inverted. Substituting λ = L/L_E into Eq. (3) gives N_E = λ(τ_IR + 1 − e^{−τ_UV})/σ_T, not σ_T(τ_IR + 1 − e^{−τ_UV})/λ. The text in §2.2 and all subsequent figures use the correct form, so this appears to be a typographical error, but it is a serious one: the printed formula would place the boundary on the wrong side of the N_H−λ plane. Please correct Eq. (7) and verify the derivation statement.
  2. [Section 3.1/Eq. (10)] The central claim that low-metallicity gas is dust-poor and therefore stalls follows directly from the assumed f_dg−Z power law calibrated on local, galaxy-wide samples. The paper lists processes (reverse-shock destruction, grain growth, coagulation) that can decouple f_dg from Z in high-z nuclear gas, but it does not quantify how the boundary in Figs. 1−6 changes under plausible local variations of f_dg at fixed Z. Because the direction of uncertainty matters (grain growth would shrink the long-lived-obscuration region, destruction would enlarge it), please add a robustness test varying f_dg by ±0.5−1 dex at fixed Z, or adopt an alternative high-z scaling, and show the resulting N_H−λ boundaries. If the stalling conclusion is not robust to such variations, the abstract and Sec. 5.1 should be correspondingly softened.
minor comments (4)
  1. [Section 2.1, Eqs. (8)−(9)] Please specify the units of κ_UV, κ_IR, and T_r. The coefficients in Eq. (9) appear to assume cgs units (K for T_r), but this is never stated.
  2. [Section 4.1/Fig. 6] The sentence 'the effective Eddington ratio decreases with increasing clump column density' is not generally true: in the IR-dominated limit Eq. (12) gives Λ_c → λ κ_IR m_p/σ_T, independent of N_c. The curves in Fig. 6 indeed flatten at high column density. Please qualify this statement.
  3. [Section 4.2/Table 1] The Monte-Carlo spectral simulations are the only new numerical result, but there is no comparison with a solar-metallicity case or a description of code validation. A sentence on the code and its earlier use would help.
  4. [Data availability] Although no observational data were generated, the Monte-Carlo simulations in §4.2 are new; please state whether the code is publicly available or provide a reference.

Circularity Check

0 steps flagged

No significant circularity: the central derivation is self-contained and uses an external empirical dust-to-gas ratio relation as input, not fitted to the target JWST X-ray data.

full rationale

The paper's derivation chain is: (i) adopt the standard radiation-pressure-on-dust force balance (Eqs. 1–6), (ii) introduce analytic dust opacities (Eqs. 8–9) with fixed fiducial parameters, (iii) set the dust-to-gas ratio via the empirical relation log f_dg = 1.30 [12+log(O/H)] − 13.72 (Eq. 10) taken from external local-universe galaxy samples (De Vis et al. 2019; Popping & Péroux 2022), and (iv) compute the effective Eddington boundary in the NH–λ plane (Eq. 7). The conclusion that low metallicity shifts the boundary rightward and expands the region where Λ < 1 is a direct algebraic consequence of κ ∝ f_dg ∝ Z. This is a logical implication, not a circularity: the input scaling is independent of the JWST X-ray weakness phenomenon, and no model parameter is fitted to the target observations. The blowout/stalling analysis (Sec 4.1) uses the same opacity inputs and likewise derives, rather than assumes, the result that higher metallicities are needed to eject heavier columns. The paper explicitly acknowledges uncertainties in applying Eq. 10 to high-redshift nuclear environments (Sec 3.1), but that is a robustness limitation, not a circular step. Self-citations to previous work (e.g., Ishibashi & Fabian 2016; Ishibashi et al. 2018) serve to reference the framework, whose assumptions are stated explicitly and are also supported by external references (e.g., Thompson & Heckman 2024; Mathis et al. 1977). No fitted parameter is renamed as a prediction, and no uniqueness theorem from the authors is invoked to forbid alternatives. Therefore the analysis is self-contained given its stated inputs, and no circular step can be exhibited.

Axiom & Free-Parameter Ledger

6 free parameters · 8 axioms · 0 invented entities

The central claim rests on the assumed scaling between dust opacity, dust-to-gas ratio, and metallicity, and on the dominance of radiation pressure over other forces. The model parameters (Z, a_min, a_max, rho_d, T_r) are varied by hand over plausible ranges; none is fitted to the JWST-AGN data. No new physical entities are introduced.

free parameters (6)
  • Metallicity Z = fiducial 1 Z_sun; varied 0.01-1 Z_sun
    Sets the dust-to-gas ratio through Eq 10 and is the central variable of the paper. Chosen to represent solar and sub-solar environments, not fitted to data here.
  • Minimum grain size a_min = 0.005 micron fiducial; varied 0.001-0.01 micron
    MRN distribution lower cutoff; controls the UV opacity in Eq 8. Varied to represent large-grain dust expected in the early universe.
  • Maximum grain size a_max = 0.25 micron fiducial; varied 0.1-10 micron
    MRN distribution upper cutoff; controls the UV opacity. Varied to represent supernova dust with a dominance of large grains.
  • Grain density rho_d = 3 g/cm3 fiducial; graphite 2.26, silicate 3.3
    Dust composition parameter; affects the UV opacity through Eq 8. The resulting boundary shift is minor.
  • Radiation temperature T_r = 200 K fiducial; varied 100-300 K
    Sets the IR Rosseland opacity in Eq 9; controls the high-column-density IR regime of the boundary.
  • Dust-to-gas ratio normalization (slope and intercept in Eq 10) = slope 1.30, intercept -13.72
    Empirical f_dg-Z relation from De Vis et al. 2019 and Popping and Peroux 2022; converts metallicity to dust content. Not fitted in this paper, but essential to the central claim.
axioms (8)
  • domain assumption Cold neutral dusty gas; electron scattering is negligible relative to dust absorption
    Invoked in Sec 2.1 to set F_rad = (L/c)(tau_IR + 1 - exp(-tau_UV)); if the gas were ionized, electron scattering would add a dust-independent force.
  • domain assumption Dust opacity parameterization from Thompson and Heckman 2024: kappa_UV = (3/4) f_dg / (rho_d sqrt(a_min a_max)) and kappa_IR = 0.0125 f_dg T_r^2
    Adopted as Eqs 8-9; the metallicity dependence of the boundary rests entirely on this scaling.
  • domain assumption Dust-to-gas ratio scales linearly with metallicity via log f_dg = 1.30 [12+log(O/H)] - 13.72
    Load-bearing premise for the X-ray weakness explanation; taken from De Vis et al. 2019 and Popping and Peroux 2022. Section 3.1 flags uncertainties in dust production and destruction at high z.
  • domain assumption Radiation pressure on dust is the only force opposing gravity; winds, magnetic fields, and X-ray heating are ignored
    The N_H-lambda boundary (Sec 2) and the blowout/stalling criterion (Sec 4.1) use only these two forces.
  • domain assumption The central black hole mass dominates the gravitational potential (F_grav = 4 pi G m_p M_BH N)
    Eq 1; Sec 2.2.5 acknowledges that a nuclear star cluster would shift the boundary to the right.
  • domain assumption The absorbing gas is a uniform, cold, neutral spherical cloud with solar abundance ratios scaled by metallicity Z
    Used for the Monte Carlo spectra in Sec 4.2; the cloud radius is stated not to affect the results.
  • domain assumption The cloud blowout condition is instantaneous force balance Lambda_c > 1; no time-dependent dynamics or cloud survival physics is modeled
    Sec 4.1 equates radiative and gravitational forces directly without integrating the equation of motion (Eq 11).
  • domain assumption MRN grain size distribution dn/da proportional to a^-3.5 with the adopted limits
    Used in the UV opacity formula; the paper varies a_min and a_max but keeps the power-law shape.

reviewed 2026-08-05 · how reviews work

0 comments
Cite this review

Pith. "Pith review of Another view into JWST-discovered X-ray weak AGNs via radiative dusty feedback." pith.science (2026). https://pith.science/paper/DETNZHSH

@misc{pith2026250905423,
  author       = {Pith},
  title        = {Pith review of: Another view into JWST-discovered X-ray weak AGNs via radiative dusty feedback},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/DETNZHSH}},
  note         = {Machine review of arXiv:2509.05423}
}
Share X Bluesky LinkedIn Reddit HN
abstract

JWST has revealed a previously unknown population of low-luminosity active galactic nuclei (AGN) in the early Universe. These JWST-AGN at high redshifts are characterised by a set of peculiar properties, including unusually weak X-ray emission. Here we investigate the apparent lack of X-ray emission in the framework of the ``AGN radiative dusty feedback'' scenario based on the effective Eddington limit for dust. We analyse how the boundary in the $N_\mathrm{H} - \lambda$ plane, defined by the column density versus the Eddington ratio, is modified as a function of the dusty gas parameters (metallicity, dust grain size and composition). Low metallicity gas with little dust content tends to survive against radiation pressure, and likely accumulates in the nuclear region. We suggest that such dust-poor gas can provide long-lived absorption and may lead to heavy X-ray obscuration, as observed in early JWST-AGN. The blowout vs. stalling condition of the obscuring clouds indicates that higher metallicities are required to eject heavier column densities, while large columns of gas can stall in low metallicity environments. Therefore the metallicity may play a key role in the AGN radiative dusty feedback scenario. We discuss how other peculiar properties of JWST-AGN -- such as Balmer absorption features and weak radio emission -- may be naturally interpreted within the same physical framework.

Figures

Figures reproduced from arXiv: 2509.05423 by A. C. Fabian, C. S. Reynolds, R. Maiolino, W. Ishibashi, Y. Gursahani.

Figure 1
Figure 1. Figure 1: NH − λ plane for fiducial parameters and variations in metallicity: Z = 1Z⊙ (red solid), Z = 0.5Z⊙ (blue dashed), Z = 0.3Z⊙ (green dash-dot), Z = 0.2Z⊙ (violet dash-dot-dot), Z = 0.1Z⊙ (orange dotted). The horizontal line (yellow fine line) marks the N = 1022cm−2 limit, below which absorption by outer dust lanes becomes important (Fabian et al. 2008, 2009). region decreases, and at the same time the region… view at source ↗
Figure 2
Figure 2. Figure 2: NH − λ plane with two metallicity cases: high-metallicity case (Z = 1Z⊙, red curves) and low-metallicity case (Z = 0.1Z⊙, green curves). Variations in minimum grain size (left-hand panel): amin = 0.001µm (dashed), amin = 0.005µm (solid), amin = 0.01µm (dotted). Variations in maximum grain size (right-hand panel): amax = 0.1µm (dashed), amax = 0.25µm (solid), amax = 1µm (dotted) [PITH_FULL_IMAGE:figures/fu… view at source ↗
Figure 3
Figure 3. Figure 3: NH − λ plane with two metallicity cases: high-metallicity case (Z = 1Z⊙, red curves) and low-metallicity case (Z = 0.1Z⊙, green curves). Variations in dust grain composition (left-hand panel): graphite grains ρd = 2.26 gcm−3 (dashed), and silicate grains ρd = 3.3 gcm−3 (dotted). Variations in radiation temperature (right-hand panel): T = 300 K (dashed), T = 200 K (solid), T = 100 K (dotted). ward shift of … view at source ↗
Figure 4
Figure 4. Figure 4: NH −λ plane for the solar metallicity case with fiducial parameters (red dotted) and JWST-AGN-like cases with lower metallicity (Z = 0.2Z⊙) and larger grains (amin = 0.01µm). Variations in maximum grain size: amax = 0.1µm (violet dashed), amax = 1.0µm (blue dash-dot), amax = 10µm (green dash-dot￾dot). 3.2 Dust extinction and the AV − λ plane The NH − λ plane may be converted into a correspond￾ing AV − λ pl… view at source ↗
Figure 5
Figure 5. Figure 5: AV − λ plane with RV = 5.0 and EB−V/NH = 0.1 (EB−V/NH)Gal. Solar metallicity case with fiducial param￾eters (cyan dashed) and JWST-AGN-like case with lower metal￾licity (Z = 0.2Z⊙) and larger dust grains (amin = 0.01µm, amax = 10µm) (magenta dotted). The horizontal line (yellow fine line) corresponds to the N = 1022cm−2 limit. Rectangular shade (green hatched): AV ∼ (0.5 − 5) mag and λ ∼ (0.01 − 1). large … view at source ↗
Figure 6
Figure 6. Figure 6: Left-hand panel: effective Eddington ratio (Λc) as a function of clump column density (Nc) for λ = 0.5 and different metallicities: Z = 1Z⊙ (red solid), Z = 0.3Z⊙ (blue dashed), Z = 0.1Z⊙ (green dotted), Z = 0.02Z⊙ (violet dash-dot), Z = 0.01Z⊙ (orange dash-dot-dot). Right-hand panel: effective Eddington ratio (Λc) as a function of metallicity (Z) for λ = 0.5 and different clump column densities: Nc = 1023… view at source ↗
Figure 7
Figure 7. Figure 7: Simulated X-ray spectra for a spherical cloud with Z = 0.1Z⊙ (left-hand panel) and Z = 0.2Z⊙ (right-hand panel), with NH = 1024cm−2 (blue curve) and NH = 1025cm−2 (orange curve). The black dashed line is the input power-law. covering factors may be expected when dense gas lingers in the nuclear region, due to weak AGN radiative feedback. A common picture emerging from the latest JWST observa￾tions is that … view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

65 extracted references · 50 canonical work pages · 1 internal anchor

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    @esa (Ref

    \@ifclassloaded agu2001 natbib The agu2001 class already includes natbib coding, so you should not add it explicitly Type <Return> for now, but then later remove the command natbib from the document \@ifclassloaded aguplus natbib The aguplus class already includes natbib coding, so you should not add it explicitly Type <Return> for now, but then later rem...

  3. [3]

    @stdbsttrue NAT@ctr \@lbibitem[ NAT@ctr ] \@lbibitem[#1]#2 \@extra@b@citeb \@ifundefined br@#2\@extra@b@citeb \@namedef br@#2 \@nameuse br@#2\@extra@b@citeb \@ifundefined b@#2\@extra@b@citeb @num @parse #2 [ @natanchorstart #2\@extra@b@citeb \@biblabel @num @natanchorend] @ifcmd#1(@)(@)\@nil #2 @lbibitem\@undefined @lbibitem\@lbibitem \@lbibitem[#1]#2 @lb...

  4. [4]

    @open @close @open @close and [1] URL: #1 \@ifundefined chapter * \@mkboth \@ifundefined NAT@sectionbib * \@mkboth * \@mkboth\@gobbletwo \@ifclassloaded amsart * \@ifclassloaded amsbook * \@ifundefined bib@heading @heading NAT@ctr thebibliography [1] @ \@biblabel NAT@ctr \@bibsetup #1 NAT@ctr 0 @openbib .11em \@plus.33em \@minus.07em 4000 4000 `\.=1000 \@...

  5. [5]

    T., Bogd \'a n \'A ., Kov \'a cs O

    Ananna T. T., Bogd \'a n \'A ., Kov \'a cs O. E., Natarajan P., Hickox R. C., 2024, , 969, L18

  6. [6]

    C., Ferland G

    Arakawa N., Fabian A. C., Ferland G. J., Ishibashi W., 2022, , 517, 5069

  7. [7]

    J., Scott P., 2009, , 47, 481

    Asplund M., Grevesse N., Sauval A. J., Scott P., 2009, , 47, 481

  8. [8]

    C., Savage B

    Bohlin R. C., Savage B. D., Drake J. F., 1978, , 224, 132

  9. [9]

    J., Liu X., Chen Y.-C., Shen Y., Guo H., 2021, , 504, 543

    Burke C. J., Liu X., Chen Y.-C., Shen Y., Guo H., 2021, , 504, 543

  10. [10]

    I., Graci \'a -Carpio J., Koss M

    Burtscher L., Davies R. I., Graci \'a -Carpio J., Koss M. J., Lin M. Y., Lutz D., Nandra P., Netzer H., Orban de Xivry G., et al. 2016, , 586, A28

  11. [11]

    M., Akins H

    Casey C. M., Akins H. B., Kokorev V., McKinney J., Cooper O. R., Long A. S., Franco M., Manning S. M., 2024, , 975, L4

  12. [12]

    P., Labbe I., Wang B., Leja J., Matthee J., Katz H., Greene J

    de Graaff A., Rix H.-W., Naidu R. P., Labbe I., Wang B., Leja J., Matthee J., Katz H., Greene J. E. e. a., 2025, arXiv e-prints, p. arXiv:2503.16600

  13. [13]

    2019, , 623, A5

    De Vis P., Jones A., Viaene S., et al. 2019, , 623, A5

  14. [14]

    2025, arXiv e-prints, p

    D'Eugenio F., Maiolino R., Perna M., et al. 2025, arXiv e-prints, p. arXiv:2503.11752

  15. [15]

    C., Vasudevan R

    Fabian A. C., Vasudevan R. V., Gandhi P., 2008, , 385, L43

  16. [16]

    C., Vasudevan R

    Fabian A. C., Vasudevan R. V., Mushotzky R. F., Winter L. M., Reynolds C. S., 2009, , 394, L89

  17. [17]

    A., 2023, , 61, 373

    Fan X., Ba \ n ados E., Simcoe R. A., 2023, , 61, 373

  18. [18]

    2021, , 649, A18

    Galliano F., Nersesian A., et al. 2021, , 649, A18

  19. [19]

    M., Goosmann R

    Gaskell C. M., Goosmann R. W., Antonucci R. R. J., Whysong D. H., 2004, , 616, 147

  20. [20]

    Glikman E., LaMassa S., Piconcelli E., Zappacosta L., Lacy M., 2024, , 528, 711

  21. [21]

    J., Duncan K

    Gloudemans A. J., Duncan K. J., Eilers A.-C., Farina E. P., Harikane Y., Inayoshi K., Lambrides E., Vardoulaki E., 2025, arXiv e-prints, p. arXiv:2501.04912

  22. [22]

    E., Labbe I., Goulding A

    Greene J. E., Labbe I., Goulding A. D., Furtak L. J., Chemerynska I., Kokorev V., Dayal P., Volonteri M., et al. 2024, , 964, 39

  23. [23]

    N., Maiolino R., Juod z balis I., et al

    Hainline K. N., Maiolino R., Juod z balis I., et al. 2025, , 979, 138

  24. [24]

    Harikane Y., Zhang Y., Nakajima K., Ouchi M., Isobe Y., Ono Y., Hatano S., Xu Y., Umeda H., 2023, , 959, 39

  25. [25]

    Inayoshi K., Maiolino R., 2025, , 980, L27

  26. [26]

    Inayoshi K., Visbal E., Haiman Z., 2020, , 58, 27

  27. [27]

    C., 2016, , 463, 1291

    Ishibashi W., Fabian A. C., 2016, , 463, 1291

  28. [28]

    C., Hewett P

    Ishibashi W., Fabian A. C., Hewett P. C., 2024, , 533, 4384

  29. [29]

    C., Maiolino R., 2018, , 476, 512

    Ishibashi W., Fabian A. C., Maiolino R., 2018, , 476, 512

  30. [30]

    C., Ricci C., Celotti A., 2018, , 479, 3335

    Ishibashi W., Fabian A. C., Ricci C., Celotti A., 2018, , 479, 3335

  31. [31]

    2025, arXiv e-prints, p

    Ji X., Maiolino R., \"U bler H., Scholtz J., D'Eugenio F., Sun F., Perna M., Turner H., Arribas S., et al. 2025, arXiv e-prints, p. arXiv:2501.13082

  32. [32]

    D., Bischetti M., et al

    Jiang D., Onoue M., Jiang L., Lai S., Ba \ n ados E., Becker G. D., Bischetti M., et al. 2024, , 975, 214

  33. [33]

    D., Assef R

    Jun H. D., Assef R. J., Carroll C. M., Hickox R. C., Kim Y., Lee J., Ricci C., Stern D., 2021, , 906, 21

  34. [34]

    C., et al

    Juod z balis I., Ji X., Maiolino R., D'Eugenio F., Scholtz J., Risaliti G., Fabian A. C., et al. 2024, , 535, 853

  35. [35]

    2024, , 691, A52

    Killi M., Watson D., et al. 2024, , 691, A52

  36. [36]

    King A., 2025, , 536, L1

  37. [37]

    D., Finkelstein S

    Kocevski D. D., Finkelstein S. L., Barro G., Taylor A. J., Calabr \`o A., Laloux B., Buchner J., et al. 2024, arXiv e-prints, p. arXiv:2404.03576

  38. [38]

    D., Onoue M., Inayoshi K., et al

    Kocevski D. D., Onoue M., Inayoshi K., et al. 2023, , 954, L4

  39. [39]

    E., Bezanson R., Fujimoto S., Furtak L

    Labbe I., Greene J. E., Bezanson R., Fujimoto S., Furtak L. J., Goulding A. D., Matthee J., Naidu R. P., et al. 2025, , 978, 92

  40. [40]

    C., 2025, , 980, 36

    Li Z., Inayoshi K., Chen K., Ichikawa K., Ho L. C., 2025, , 980, 36

  41. [41]

    B., Sun F., Volonteri M., Yang J., et al

    Lin X., Wang F., Fan X., Cai Z., Champagne J. B., Sun F., Volonteri M., Yang J., et al. 2024, , 974, 147

  42. [42]

    2018, , 479, 5022

    Liu T., Merloni A., Wang J.-X., Tozzi P., Shen Y., Brusa M., et al. 2018, , 479, 5022

  43. [43]

    Madau P., Haardt F., 2024, , 976, L24

  44. [44]

    Maiolino R., Marconi A., Oliva E., 2001, , 365, 37

  45. [45]

    Maiolino R., Risaliti G., Signorini M., Trefoloni B., Juod z balis I., et al. 2025,

  46. [46]

    2024, , 691, A145

    Maiolino R., Scholtz J., Curtis-Lake E., Carniani S., Baker W., de Graaff A., et al. 2024, , 691, A145

  47. [47]

    D., Sommovigo L., Kohandel M., 2025, Nature Astronomy, 9, 458

    Markov V., Gallerani S., Ferrara A., Pallottini A., Parlanti E., Mascia F. D., Sommovigo L., Kohandel M., 2025, Nature Astronomy, 9, 458

  48. [48]

    S., Rumpl W., Nordsieck K

    Mathis J. S., Rumpl W., Nordsieck K. H., 1977, , 217, 425

  49. [49]

    P., Brammer G., Chisholm J., Eilers A.-C., Goulding A., Greene J., et al

    Matthee J., Naidu R. P., Brammer G., Chisholm J., Eilers A.-C., Goulding A., Greene J., et al. 2024, , 963, 129

  50. [50]

    F., Belladitta S., Vito F., et al

    Mazzolari G., Gilli R., Maiolino R., Prandoni I., Delvecchio I., Norman C., Jimenez-Andrade E. F., Belladitta S., Vito F., et al. 2024, arXiv e-prints, p. arXiv:2412.04224

  51. [51]

    Modeling Galaxies in the Early Universe with Supernova Dust Attenuation

    McKinney J., Cooper O., Casey C. M., Munoz J. B., Akins H., Lambrides E., Long A. S., 2025, arXiv e-prints, p. arXiv:2502.14031

  52. [52]

    Mizukoshi S., Minezaki T., Sameshima H., Kokubo M., Noda H., Kawamuro T., Yamada S., Horiuchi T., 2024, , 532, 666

  53. [53]

    P., Matthee J., Katz H., de Graaff A., Oesch P., Smith A., Greene J

    Naidu R. P., Matthee J., Katz H., de Graaff A., Oesch P., Smith A., Greene J. E., et al. 2025, arXiv e-prints, p. arXiv:2503.16596

  54. [54]

    Pacucci F., Narayan R., 2024, , 976, 96

  55. [55]

    \'E ., 2025, , 693, L2

    Perger K., Fogasy J., Frey S., Gab \'a nyi K. \'E ., 2025, , 693, L2

  56. [56]

    Popping G., P \'e roux C., 2022, , 513, 1531

  57. [57]

    P., Brammer G., Gottumukkala R., Harvey T., Heintz K

    Rusakov V., Watson D., Nikopoulos G. P., Brammer G., Gottumukkala R., Harvey T., Heintz K. E., et al. 2025, arXiv e-prints, p. arXiv:2503.16595

  58. [58]

    Schneider R., Maiolino R., 2024, , 32, 2

  59. [59]

    T., Davies R

    Shimizu T. T., Davies R. I., Koss M., Ricci C., Lamperti I., Oh K., Schawinski K., et al. 2018, , 856, 154

  60. [60]

    Tazaki R., Ichikawa K., 2020, , 892, 149

  61. [61]

    A., Heckman T

    Thompson T. A., Heckman T. M., 2024, , 62, 529

  62. [62]

    arXiv:2410.21867

    Trefoloni B., Ji X., Maiolino R., D'Eugenio F., \"U bler H., Scholtz J., Marconi A., Marconcini C., Mazzolari G., 2024, arXiv e-prints, p. arXiv:2410.21867

  63. [63]

    2024, arXiv e-prints, p

    Tripodi R., Martis N., Markov V., et al. 2024, arXiv e-prints, p. arXiv:2412.04983

  64. [64]

    2023, , 677, A145

    \"U bler H., Maiolino R., Curtis-Lake E., et al. 2023, , 677, A145

  65. [65]

    T., Panagiotou C., Kara E., Miyaji T., 2024, , 974, L26

    Yue M., Eilers A.-C., Ananna T. T., Panagiotou C., Kara E., Miyaji T., 2024, , 974, L26

This paper was first reviewed by deepseek-v4-flash on August 5, 2026.