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REVIEW 5 major objections 6 minor 114 references

AGN jet speed is the dominant tested parameter for heating low-density cosmic gas, so hot diffuse gas can reveal how black hole jets shape the universe.

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2026-08-02 06:06 UTC pith:MV4BO3QG

load-bearing objection A genuinely useful case study of jet-parameter variation in Simba-C, but the headline tSZ ratio outside filaments is shakier than the abstract implies: one region, one projection, and a filament mask fixed to the baseline run. the 5 major comments →

arxiv 2607.13132 v1 pith:MV4BO3QG submitted 2026-07-14 astro-ph.CO astro-ph.GA

Here, There and Everywhere: How AGN jets affect galaxy cluster environments

Isaac Rosenberg , Martine Lokken , Ren\'ee Hlo\v{z}ek , Weiguang Cui , Sara Santoni , Romeel Dav\'e This is my paper
classification astro-ph.CO astro-ph.GA
keywords AGN feedbackjet velocitywarm-hot intergalactic mediumthermal Sunyaev-Zel'dovich effectcosmic filamentsgalaxy clustershydrodynamical simulations
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.

This paper asks which knob in the sub-grid recipe for AGN jets—speed, direction, or how long the jet travels before coupling to the gas—most changes the observable state of gas around galaxy clusters. The answer, across three zoom-in cluster simulations, is jet velocity: raising the velocity cap from 7,000 to 35,000 km/s produces nearly an order of magnitude more gas above 10^7 K in underdense regions at z≈1–4, while orientation and delayed coupling have weaker, messier effects. The authors argue this hot gas in low-density intergalactic space is the most sensitive observable signature of jet feedback, and that the signal outside filaments is roughly doubled—unlike the ~10% change inside clusters and filaments—so next-generation CMB experiments could distinguish feedback models. If true, the emptiest parts of the cosmic web become a laboratory for calibrating how black holes redistribute baryons over megaparsec scales.

Core claim

The central claim is that jet velocity is the dominant parameter among those varied in determining the thermal state of gas outside clusters at high redshift. Using zoom-in hydrodynamic simulations of three cluster regions, the paper compares runs with no jets, baseline jets (v_max = 7,000 km/s), and fast jets (v_max = 35,000 km/s), as well as random jet orientation and a longer decoupling time. In the most diffuse gas (overdensities δ<8), the fast-jet run contains up to nearly an order of magnitude more mass at T>10^7 K at z≈1–4, and about twice the Compton-y signal outside filaments compared with the baseline, while inside filaments the difference is only ~10%. The paper further finds that

What carries the argument

The central object is the jet-feedback prescription in the galaxy-formation simulation, parameterized by a velocity cap v_max that sets the maximum kick speed of momentum-loaded jets, a decoupling time that lets jets travel freely before interacting, and the jet emission direction. The analysis machinery is the comparison of these runs through overdensity-binned mass-weighted gas temperature and mock Compton-y maps, with a topological filament-finding algorithm used to separate signal inside and outside filaments. These tools let the paper ask which parameter most changes the thermal state of large-scale structure.

Load-bearing premise

The three simulated cluster regions were chosen for extreme superclustering, high ellipticity, and abundant black holes, and the paper itself cautions they may not be representative, so the claimed sensitivity of low-density gas to jet speed could be an artifact of sampling voids that sit unusually close to massive clusters.

What would settle it

A future measurement of the stacked Compton-y in cluster outskirts beyond ~5 Mpc, at the sensitivity of a spectral-distortion experiment (σ_⟨y⟩ ≈ 1.6×10^-8), would directly test the predicted gap between fast-jet and no-jet models; if the mean-y difference outside clusters does not appear, the claimed sensitivity of underdense gas to jet velocity fails. A cheaper calculation: run the same feedback variations in a large periodic simulation box and check whether the order-of-magnitude boost of T>10^7 K gas at δ<8 survives outside cluster-proximate environments.

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

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If this is right

  • A ~100% enhancement of Compton-y outside filaments (versus ~10% inside) means stacked tSZ measurements around clusters could discriminate jet models even though the absolute signal there is faint.
  • The order-of-magnitude boost in T>10^7 K gas in δ<8 regions at z≈1–4 identifies the presence of very hot gas in sparse environments as a redshift-dependent marker of jet activity.
  • Higher-velocity jets matching observed BCG stellar masses and baryon fractions implies that strong kinetic jet feedback, not just winds or thermal feedback, is needed to explain massive central galaxies.
  • Because random jet orientation and delayed coupling produce subtler, non-uniform effects, future model comparisons should prioritize jet velocity (momentum) over angular details.
  • Future CMB spectral-distortion and high-resolution tSZ experiments could provide a direct test of the predicted mean-y difference between no-jet and fast-jet scenarios.

Where Pith is reading between the lines

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

  • A testable extension not in the paper: run the same jet-parameter variations in a large periodic cosmological box and stack tSZ outside filaments around field halos, which would show whether the ~100% underdense boost survives outside the cluster-proximate voids the paper samples.
  • The paper does not separate jet velocity from momentum flux, since mass-loading is held fixed; varying the two independently would clarify whether the dominant physical quantity is speed itself or total momentum injection.
  • If hot low-density gas is as sensitive as claimed, AGN jet feedback could measurably affect interpretations of the 'missing baryons' problem and cosmological surveys that rely on the thermal SZ background, since low-density gas outside clusters is usually assumed to be cool.
  • An observational follow-up could compare stacked tSZ around clusters with known giant radio jets versus radio-quiet clusters; the paper's model predicts stronger outside-filament signal in the former.

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

5 major / 6 minor

Summary. The paper presents zoom-in hydrodynamical simulations of three massive cluster regions from the Three Hundred project using Simba-C, varying the AGN jet velocity cap (7,000 vs 35,000 km/s, plus a no-jet run), the jet decoupling time (alpha = 1e-4 vs 2e-3), and the jet emission direction (angular-momentum-aligned vs random). It measures IGM gas temperature and density in bins of gas overdensity, mock tSZ maps, filament classification with DisPerSE, oriented stacking of halo tSZ profiles, and compares BCG stellar masses, BH-halo relations, and baryon fractions to eRASS1 and other X-ray data. The central claim is that jet velocity is the dominant tested parameter for heating low-density gas at z > 1, and that the tSZ signal in regions outside filaments is enhanced by ~100%, making hot low-density gas a promising observational probe of AGN feedback. The paper explicitly frames itself as a case study and includes several caveats about the specialized simulation regions and resolution limits.

Significance. If the result holds, it would identify a new observational discriminator for AGN jet feedback — the thermal state of diffuse, cluster-exterior gas at z~1–4 — and would motivate targeted stacking with next-generation tSZ surveys. The study has genuine strengths: the jet parameters are varied a priori within a fixed simulation code and are not fitted to the comparison data, so the eRASS1 BCG masses and BH-halo data provide an independent check; the mock tSZ pipeline is clearly described; and the paper is careful about resolution and about the non-representative nature of its regions. However, at present the headline quantitative claims are not fully robust because the ~100% outside-filament ratio rests on a single region, a single projection, and a filament mask fixed to the baseline run, and because the varied 'jet velocity' is entangled with mass/energy injection. With additional robustness tests and appropriately qualified conclusions, the paper would be a useful contribution.

major comments (5)
  1. [§3.4, §4.4, Fig. 6] The ~100% outside-filament enhancement is measured with a filament mask derived from the baseline run only. DisPerSE is run on the baseline y-map and the same skeleton is imposed on all feedback runs, with a fixed 1.5 h^-1 cMpc radius and one projection of region A. If fast jets broaden or shift pressure structures, gas that would be filamentary in the fast-jet map is classified as 'outside', while the no-jet run's narrower pressure network suppresses its outside signal. The headline ratio in the Abstract is therefore not robust to this classification choice. Please rerun filament finding per run, or at least vary the persistence threshold and filament width, and report the sensitivity. Multiple regions/projections with error bars are also needed to support the stated magnitude.
  2. [§2.4, Eq. (9)] Changing v_Max while keeping Eq. (9) fixed simultaneously changes the jet mass outflow rate and the kinetic energy injection rate; if instead the mass outflow is held constant, the momentum flux changes. The sentence 'The mass-loading remains constant ... so in changing the jet velocity we are also modifying the momentum flux' is not internally consistent. The causal statement that 'jet velocity is the dominant parameter' should therefore be rephrased in terms of the actual injected energy/momentum, or the separate contributions should be quantified. Without this, the attribution of the effect specifically to 'velocity' is not clean.
  3. [§2.2, §4.2, Abstract] The quantitative hot-gas results come from only three regions deliberately selected for extreme superclustering, high ellipticity, and high BH abundance (Eq. 3). The underdense gas sampled is cluster-proximate, and the paper itself states that 'these are the voids that would be most susceptible to jet-induced heating' and that the regions 'may not be representative of the average.' The Abstract's unqualified phrases 'low-density environments' and 'under-dense regions outside filaments' overstate the scope. Please qualify the central claim to cluster-proximate supercluster environments, or provide evidence (e.g., volume/overdensity statistics) that the effect is generic.
  4. [§4.3, Table 2] The comparison to FOSSIL's global <y> sensitivity is not appropriate. Table 2 reports the mean y in an overdense zoom-in region, not a global sky signal, and the difference between feedback models in this region cannot be equated with the change in the global monopole. The sentence indicating that FOSSIL 'might be able to discriminate such feedback models' is therefore unsupported. Please remove or reframe this claim, or compute the expected contribution of such regions to the global y and its uncertainty.
  5. [§4.6, Fig. 8] The claim that the fast-jet run 'provides the best match' to eRASS1 is based on a visual comparison of ~100 BCGs with no goodness-of-fit statistic, and the BCG aperture/ICL systematics are acknowledged. Since this statement appears in the Abstract, it needs either a quantitative assessment (e.g., scatter, selection function, or a likelihood) or a more hedged formulation such as 'consistent with' rather than 'best match'.
minor comments (6)
  1. [§4.4] The sentence 'The Compton-y profile is computed from the baseline y-map' is ambiguous. The middle and right columns of Fig. 6 compare several feedback models, so the text should clarify that the profiles are extracted from each run's y-map using the baseline-derived filament mask.
  2. [§4.3, Table 2] Please provide uncertainties for the mean-y values in Table 2. Without them, it is difficult to judge whether the reported differences between runs are meaningful.
  3. [§3.4] The capitalization 'DiSperSE' is inconsistent with 'DisPerSE' in several places; please standardize.
  4. [§4.5, Fig. 7] The caption says the shaded bands show the 'estimated standard error on the mean for equivalent SO observations,' while the text states the bands are ±0.2 C_m(r)/sqrt(3). Please align the figure, caption, and text.
  5. [§4.5] Typo: 'anlayses' should be 'analyses.'
  6. [§4.9–4.10] The random-direction and late-coupling runs are performed in single, different regions. Please state explicitly that comparisons of their relative impact to the velocity runs rely on within-region comparisons, and avoid cross-region statements without noting this limitation.

Circularity Check

0 steps flagged

No circularity: varied jet parameters are prescribed inputs and external comparisons are independent checks.

full rationale

The paper's central claim is that jet velocity cap is the dominant tested parameter for heating low-density gas and that hot gas outside filaments is a sensitive observable. This is a simulation comparison, not a derivation in which an input is constructed from the output. The varied parameters (vMax=7,000/35,000 km/s, alpha=1e-4/2e-3, jet direction) are prescribed in Sec. 2.4, and the eRASS1/Gaspari/Giodini comparisons in Secs. 4.6-4.8 are external observational checks. Simba-C was calibrated to different summary statistics (z=0 stellar mass function, M_BH-M*, quenched fraction, Sec. 2.1), so the fast-jet match to BCG and gas fractions is not a fitted-input-called-prediction. The paper's own caveats - the fixed baseline DisPerSE skeleton, one region/projection for the ~100% outside-filament tSZ ratio, and low-density regions 'most susceptible to jet-induced heating' - are limitations on robustness/generalization, not circularity: the outside-filament ratio is still computed from simulated y-maps in a fixed mask and does not reduce to an input parameter by construction. Self-citations (Lokken et al. 2023 for supercluster selection; Santoni et al. 2024/2026 for persistence cuts) are auxiliary methodological choices with independent content and do not force the physical conclusions.

Axiom & Free-Parameter Ledger

3 free parameters · 4 axioms · 0 invented entities

The paper contributes parameter variations on top of the The300/Simba-C framework; the central results inherit all of that model's calibrated subgrid physics. The three parameters varied here are hand-chosen, not fitted to the observational comparisons. No new physical entities are introduced. The most consequential unvalidated input is the jet decoupling prescription, which lets jets travel freely for α t_Hubble before coupling; the conclusion that fast jets heat underdense gas depends on this free-flight assumption.

free parameters (3)
  • Jet velocity cap vMax = 7,000 (baseline), 35,000 (fast), disabled (no jets) km/s
    Chosen by hand to probe model limits; not fitted to target data. Since mass-loading is constant, changing vMax also changes momentum flux, so the 'velocity' variation conflates velocity and momentum.
  • Decoupling time scaling alpha = 1e-4 (baseline), 2e-3 (late)
    Hand-chosen; sets distance jets travel before coupling (Eq. 10).
  • Jet direction model = aligned with angular momentum; randomized
    Hand-chosen to represent coherent vs chaotic accretion scenarios.
axioms (4)
  • domain assumption Planck 2016 cosmological parameters (H0=67.77, Ωm=0.307, Ωb=0.048, σ8=0.823, ns=0.96)
    Fiducial background model assumed in MDPL2/The300; results may depend on this cosmology.
  • domain assumption Simba-C subgrid galaxy formation model (chemical enrichment, BH seeding, torque/Bondi accretion, X-ray/wind/jet feedback) is a valid representation of baryon physics on cluster scales
    Inherited from prior calibration; the paper's results are conditional on this model.
  • ad hoc to paper Jet feedback prescription: mass-loaded jets with fixed momentum flux 20 c η Ṁ_BH, velocity cap vMax, and free propagation for t_dec = α t_Hubble before coupling
    This scheme is prescriptive (Section 2.3); the conclusion that fast jets heat underdense gas depends on jets propagating decoupled to large radii and depositing energy later.
  • domain assumption DisPerSE persistence thresholds (1 and 1.5) and fixed filament radius 1.5 h^-1 cMpc robustly define filament membership; the baseline skeleton is used for all feedback runs
    Filament classification in Section 3.4; using a fixed skeleton avoids noise but assumes feedback does not move filaments.

reviewed 2026-08-02 · how reviews work

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Cite this review

Pith. "Pith review of Here, There and Everywhere: How AGN jets affect galaxy cluster environments." pith.science (2026). https://pith.science/paper/MV4BO3QG

@misc{pith2026260713132,
  author       = {Pith},
  title        = {Pith review of: Here, There and Everywhere: How AGN jets affect galaxy cluster environments},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/MV4BO3QG}},
  note         = {Machine review of arXiv:2607.13132}
}
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read the original abstract

Active galactic nuclei (AGN) feedback via black hole-driven jets and winds plays a key role in redistributing matter across megaparsec scales. However, the implementation of jet feedback in cosmological simulations remains highly prescriptive, leading to uncertainties in the predicted state of the Warm-Hot Intergalactic Medium and other extragalactic observables. We investigate how variations in AGN jet velocity, orientation, and delayed hydrodynamic coupling impact the thermodynamic state of gas surrounding galaxy clusters. We aim to identify observational signatures in the thermal Sunyaev-Zel'dovich (tSZ) effect and galaxy properties that can constrain these models. We employ zoom-in hydrodynamic simulations centered on three galaxy clusters from The Three Hundred, utilizing the SIMBA-C model and various feedback parameters. We use filament-finding algorithms and oriented stacking to probe the effect on large-scale structure and compare our results to observational data for brightest cluster galaxies from eRASS1, black hole-halo mass relations and baryonic mass fractions. Jet velocity is the dominant tested parameter in heating low-density environments at $z > 1$. At lower-$z$, higher velocity jets quench star formation, expel baryonic matter, and prevent black hole growth. While the tSZ signal within the central cluster and surrounding filaments is only affected by $\sim10\%$, the signal in under-dense regions outside filaments is enhanced by $\sim100\%$. In this case study, high velocity AGN jets provide the best match to galaxy properties from eRASS1 and other X-ray surveys. We find that hot gas in low-density regimes is a sensitive probe of AGN feedback. Future high-resolution tSZ surveys like the Simons Observatory and spectral-distortion experiments like FOSSIL have the potential to probe the thermal state of the gas outside clusters to distinguish between these feedback models.

Figures

Figures reproduced from arXiv: 2607.13132 by Isaac Rosenberg, Martine Lokken, Ren\'ee Hlo\v{z}ek, Romeel Dav\'e, Sara Santoni, Weiguang Cui.

Figure 1
Figure 1. Figure 1: Various jet properties as a function of redshift for all of the runs. The first column is the black hole mass fraction for halos [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A mass-weighted gas temperature projection of the no jets [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: In each box of the plot above is the projection of a box with dimensions 30 [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The mass-weighted fractions of IGM gas for three di [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Left: a 30 h −1 cMpc×30 h −1 cMpc×30 h −1 cMpc projection of the overdensity field at redshift z = 0. The particles are colored by their value of overdensity in bins: δ > 100 (red), 10 < δ < 100 (yellow), 0 < δ < 10 (green) and δ < 0 (blue). These overdensities are used to illustrate trends in the behaviour of the gas at different temperatures as shown on right and [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: The center and right columns show the median Compton [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Stacked low-mass (M < 1013.5 M⊙, middle two panels) and high-mass halos (M > 1013.5 M⊙, right two panels) oriented by the dark matter field (shown at the far left) smoothed with a Gaussian of 0.5 and 5 Mpc FWHM, respectively. The y-maps are pixelated at SO pixel size but not smoothed with a beam. Radial profiles show the isotropic and dipole moments of the stacked images. Shaded bands show the estimated st… view at source ↗
Figure 8
Figure 8. Figure 8: Stellar mass of the brightest cluster galaxy (BCG) as a function of halo mass ( [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Total BH mass in the host halo as a function of halo [PITH_FULL_IMAGE:figures/full_fig_p013_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Left: Gas mass fraction within R500 in the host halo (for halos within 15 h −1 cMpc) as a function of the halo mass (M500) at redshift z = 0. All of the simulation regions for a given jet velocity are combined. The different colours correspond to different jet feedback runs, and the dotted black line is the cosmic baryon fraction. Right: Same as the left but for stellar mass fraction. Four sets of observa… view at source ↗
Figure 11
Figure 11. Figure 11: The gas mass above T > 107 K (top row) and between 105 − 107 K (bottom row) for different feedback runs divided by the baseline run, with separate lines for different overdensity val￾ues. An example of the separation of the gas into density groups is shown in [PITH_FULL_IMAGE:figures/full_fig_p015_11.png] view at source ↗

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This paper was first reviewed by deepseek-v4-flash on August 2, 2026.