{"id":"16cb4bb9-96ae-447c-b3b2-7b3db8ac7472","arxiv_id":"2607.13132","paper_version":1,"verdict":"CONDITIONAL","confidence":"HIGH","novelty_score":6.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":3,"one_line_summary":"Fast AGN jets in cluster simulations heat low-density gas and double the tSZ signal outside filaments, making hot sparse gas a promising discriminator between jet feedback models.","lead":"This paper uses galaxy-cluster simulations with different black-hole jet settings — faster jets, no jets, or different jet directions — to see how each changes gas temperature and the cosmic microwave background's Sunyaev-Zel'dovich signal. Jet speed is the strongest lever: fast jets heat otherwise empty regions of space by early cosmic times, and future CMB experiments may be able to measure that heat to test how black holes shape their surroundings.","discovery_kind":"extension","skeptic_critique":{"model":"deepseek-v4-flash","headline":"The ~100% outside-filament tSZ enhancement probably depends on a filament mask fixed to the baseline run; re-deriving masks per run could shrink or remove the effect.","rationale":"The reader's weakest assumption is representativeness: the three regions are deliberately extreme and cluster-centered, and the paper itself warns they may not be average. That is a real constraint on generalization, but it is explicitly disclosed and does not invalidate the case study. The more immediately load-bearing problem is that the headline tSZ discriminator depends on a filament mask fixed to the baseline run. The paper says this was done to avoid noise, but it can systematically misclassify gas in the other feedback runs, inflating the apparent outside-filament enhancement even in region A. This concern is internal to the presented analysis and can be settled with existing outputs, so it is the right place to stress. I do not see a circular argument or a numerical error in the central derivations; the simulations, parameter variations, and observational comparisons are described transparently, and several limitations are acknowledged (resolution, small sample, one-projection filament analysis, qualitative eRASS1 match). The fixed-mask test should be reported before the ~100% outside-filament number is used as a quantitative prediction, but it does not change the overall conditional assessment: the paper is a promising case study whose strongest quantitative claim needs a robustness check. Hence the reader's CONDITIONAL verdict is appropriate and no verdict change is needed.","tokens_in":27679,"tokens_out":6905,"duration_ms":70021,"concrete_test":"Using the existing runs, re-run DisPerSE independently on the no-jet, baseline, and fast-jet y-maps at z=0.5 and z=1 with the same smoothing and persistence thresholds as Sec. 3.4. For each run, build inside/outside masks from that run's own skeleton, using a range of filament radii (e.g. 0.7, 1.5, 2.0 h^-1 cMpc), and recompute the median radial y profiles and the outside-filament fractional enhancement. Bootstrap over pixels to get uncertainties. If the fast/outside excess falls below ~50% or overlaps the no-jet profile at 1-sigma, the abstract's ~100% claim needs revision. Repeating with region B or another projection would test whether the effect is a single-line-of-sight artifact.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The abstract's headline that tSZ in under-dense regions outside filaments is enhanced by ~100% rests on the filament analysis in Sec. 3.4/4.4. DisPerSE is run only on the baseline y-map and the same skeleton is imposed on all feedback runs; pixels within a fixed 1.5 h^-1 cMpc radius are classified as 'inside', everything else 'outside', using one projection of region A. This is load-bearing because the quantity being compared is defined relative to a mask that can itself change with feedback. If fast jets heat and broaden pressure structures, gas that would be filamentary in a fast-jet y-map can be counted as 'outside' by the baseline mask, while the no-jet run may have a narrower pressure network, suppressing its 'outside' signal. The reported ~100% enhancement could then be partly an artifact of comparing different physical regions under a common mask. The authors say this choice avoids noise, but it replaces noise with a systematic classification bias. In addition, only one region, one projection, and no error bars support the headline ratio, so the magnitude is not yet robust even setting aside the mask issue. This is a concrete, checkable methodological concern rather than a challenge to the broader claim that jet velocity heats low-density gas in these cluster-proximate regions.","agreement_with_reader":"partial"},"referee_report":{"model":"deepseek-v4-flash","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.","tokens_in":28006,"tokens_out":10588,"duration_ms":113690,"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":[{"comment":"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.","section":"§3.4, §4.4, Fig. 6"},{"comment":"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.","section":"§2.4, Eq. (9)"},{"comment":"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.","section":"§2.2, §4.2, Abstract"},{"comment":"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.","section":"§4.3, Table 2"},{"comment":"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'.","section":"§4.6, Fig. 8"}],"minor_comments":[{"comment":"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.","section":"§4.4"},{"comment":"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.","section":"§4.3, Table 2"},{"comment":"The capitalization 'DiSperSE' is inconsistent with 'DisPerSE' in several places; please standardize.","section":"§3.4"},{"comment":"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.","section":"§4.5, Fig. 7"},{"comment":"Typo: 'anlayses' should be 'analyses.'","section":"§4.5"},{"comment":"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.","section":"§4.9–4.10"}],"recommendation":"major_revision","confidential_remarks":"This is a promising case study and the authors are appropriately hedged in several places, but the abstract and conclusions go beyond what the current analysis supports. The fixed-mask filament test and the FOSSIL comparison are the most important technical points; both are fixable. No concerns about citation practice or novelty. I would be happy to see a revised version."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"Worth reading, but take the headline numbers as provisional. This is a case study, not a population measurement: three deliberately extreme cluster zoom-ins, and the most striking claims come from one of them. Within that scope, the work does something genuinely new: it systematically varies three jet parameters within a single code and probes the gas response with filament-finding and oriented tSZ stacks. The finding that diffuse, low-overdensity gas is far more sensitive to jet velocity than dense cluster gas — order-of-magnitude changes in T>10^7 K mass at z~1-4 — is a real and useful diagnostic. The paper is also honest about many limitations: it says the regions “may not be representative of the average,” notes the voids are cluster-proximate and most susceptible to jet heating, and flags possible resolution effects. That candor is a point in its favor.\n\nThe softest spot is the ~100% tSZ enhancement outside filaments. That number rests on one region, one projection, and a filament skeleton computed only from the baseline run and imposed on the other runs. The stated reason — avoiding noise — trades one problem for another. If fast jets broaden or shift pressure structures, pixels classified as “outside filaments” in the baseline mask may not be the same physical regions in the other runs. That could inflate or even create part of the claimed contrast. This doesn’t destroy the broader claim that jet velocity heats low-density gas, but it does mean the headline ratio is not yet robust. The same caution applies to the overdensity results: they come from one region, with no error bars or variance across regions. I’d also note that changing vMax changes momentum and energy injection, not just “velocity,” so calling velocity the dominant parameter is partly a statement about which knob you turned. The comparison to eRASS1 is qualitative, based on ~100 BCG masses, so “best match” should not be oversold. Code and data are not released, which limits reproducibility.\n\nThis deserves a serious referee. It is a legitimate, internally consistent case study with a new observable angle, and the limitations are mostly fixable: re-derive filament masks per run, add variance estimates across regions and projections, reframe conclusions as conditional on the selected environments, and release the runs or analysis scripts. For someone working on tSZ or AGN feedback, it is worth engaging with now, with the caveats above.","headline":"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.","tokens_in":28496,"tokens_out":2963,"would_cite":true,"duration_ms":136030,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"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.","keywords":["AGN feedback","jet velocity","warm-hot intergalactic medium","thermal Sunyaev-Zel'dovich effect","cosmic filaments","galaxy clusters","hydrodynamical simulations"],"falsifier":"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.","tokens_in":27574,"feed_emoji":"🌌","tokens_out":7028,"duration_ms":74117,"temperature":0.7,"pith_summary":"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.","feed_headline":"Fast AGN jets pour hot gas into the sparse cosmic web","feed_subtitle":"Simulations show nearly 10x more T>10^7 K gas in low-density regions when jets are fast, a signal future CMB surveys could catch.","key_machinery":"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.","core_discovery":"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","pith_inferences":["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."],"forward_implications":["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."],"fun_headline_variants":["Fast jets heat sparse cosmic web tenfold","AGN jet speed shapes cosmic web gas","Faster jets dump hot gas into cosmic voids","Jet velocity heats low-density cosmic gas"],"cache_read_input_tokens":2304,"weakest_assumption_plain":"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.","fun_headline_variants_meta":{"raw":{"variants":["Fast jets heat sparse cosmic web tenfold","AGN jet speed shapes cosmic web gas","Faster jets dump hot gas into cosmic voids","Jet velocity heats low-density cosmic gas"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.0004,"raw_usage":{"total_tokens":1999,"prompt_tokens":893,"completion_tokens":1106,"prompt_tokens_details":{"cached_tokens":256},"prompt_cache_hit_tokens":256,"prompt_cache_miss_tokens":637,"completion_tokens_details":{"reasoning_tokens":1051}},"tokens_in":637,"tokens_out":1106,"duration_ms":9723,"temperature":1.0,"reasoning_tokens":1051,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-02T06:06:49.706149+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"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.","supporting_citations":[],"review_version":1}