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Cosmological feedback from a halo assembly perspective

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read The paper claims that baryonic feedback redistributes gas most efficiently when halos reach $M_{200\mathrm{m}}\simeq 10^{12.8}\,\mathrm{M}_\odot$, regardless of redshift, and that this single mass scale resolves apparent conflicts between…

desk verdict A careful synthesis showing kSZ and tSZ/X-ray/lensing probes target different halo populations, reconciling conflicting feedback constraints; the main caveat is the FLAMINGO-based halo mass assignment for LRGs, which is real but not fatal. read the letter →

arxiv 2505.18258 v2 pith:XAERC2JA submitted 2025-05-23 astro-ph.CO astro-ph.GA

Luisa Lucie-Smith , Hiranya V. Peiris , Andrew Pontzen , Anik Halder , Joop Schaye , Matthieu Schaller , John Helly , Robert J. McGibbon
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Willem Elbers
This is my paper
classification astro-ph.COastro-ph.GA
keywords baryonicfeedbackhaloassemblyhistorieskineticSunyaev-Zel'dovicheffectthermalweaklensingX-raygalaxyclustersFLAMINGOsimulationsmassfunctionsensitivity
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper argues that the impact of galaxy-formation feedback on cosmology is best understood through halo mass assembly histories rather than the usual suppression of the matter power spectrum. By computing which halo masses and redshifts each probe actually sees, the authors find two distinct halo populations: tSZ, X-ray, and weak-lensing measurements mostly see massive clusters near $10^{15}\,\mathrm{M}_\odot$ at $z<1$, while stacked kSZ measurements of DESI luminous red galaxies see lower-mass halos near $10^{13.1}\,\mathrm{M}_\odot$ at $z\sim0.5$-$1$. The central discovery is that feedback most efficiently removes baryons when a halo crosses $M_{200\mathrm{m}}\simeq10^{12.8}\,\mathrm{M}_\odot$, independent of when in cosmic history that happens, and becomes negligible by $10^{15}\,\mathrm{M}_\odot$ as ejected gas is re-accreted. This explains why kSZ observations appear to demand strong feedback while X-ray, lensing, and tSZ observations do not: they are probing different halo populations at different stages of assembly.

What carries the argument

The central object is the halo mass assembly history (MAH), the track of a halo's mass over time supplied by following self-bound structures across simulation snapshots. Halos in hydrodynamical runs are matched to their counterparts in gravity-only runs through the ten most strongly bound particles, so the same objects can be compared with and without feedback. The argument then uses gas and baryon mass fractions in three apertures ($R_{500c}$, $R_{200m}$, and $5R_{500c}$) as functions of both present-day mass and instantaneous mass; the key identity is the universal trough in gas fraction at $M_{200\mathrm{m}}\sim10^{12.8}\,\mathrm{M}_\odot$ seen at all redshifts, which converts assembly history into observable imprints.

What would settle it

Measure the halo masses of the same DESI LRG sample with galaxy-galaxy lensing; if the mean $M_{200\mathrm{m}}$ comes out above roughly $10^{13.5}\,\mathrm{M}_\odot$ or overlaps the $\sim10^{15}\,\mathrm{M}_\odot$ cluster population, the two-population separation collapses. Alternatively, run an independent hydrodynamical simulation suite and check whether the minimum of the gas-to-total mass ratio stays at $M_{200\mathrm{m}}\simeq10^{12.8}\,\mathrm{M}_\odot$ at every redshift.

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Extended reading notes

Core claim

The paper's central claim is that baryonic feedback redistributes baryons most efficiently at a single characteristic halo mass, $M_{200\mathrm{m}}\simeq 10^{12.8}\,\mathrm{M}_\odot$, regardless of redshift. This is established by measuring the gas mass fraction as a function of instantaneous halo mass at many redshifts in hydrodynamical simulations: every redshift shows the deepest suppression at about the same halo mass, with the exact value shifting by only 0.1-$0.3$ dex between feedback calibrations. When halos grow past $\sim10^{14}\,\mathrm{M}_\odot$ the suppression fades, and by $\sim10^{15}\,\mathrm{M}_\odot$ it is negligible because expelled gas is re-accreted. Because the thermal Sunyaev-Zel'dovich power spectrum, X-ray cluster counts, and weak-lensing one-halo terms are most sensitive to $\sim10^{15}\,\mathrm{M}_\odot$ clusters at $z\lesssim1$, while stacked kSZ profiles of the DESI LRG sample probe $\sim10^{13.1}\,\mathrm{M}_\odot$ halos at $z\sim0.5$-$1$, the two families of observables are measuring different halo populations; the strong feedback needed for kSZ does not contradict the weak feedback inferred from X-rays.

Load-bearing premise

The argument assumes that the DESI LRG galaxies used for kSZ stacks really live in halos near $M_{200\mathrm{m}}\sim10^{13.1}\,\mathrm{M}_\odot$, as assigned by one stellar-mass-to-halo-mass relation, and that the feedback behaviour measured in this one suite of simulations carries over to the real Universe.

Editorial extensions

If this is right

  • Feedback constraints from tSZ, X-ray, and weak-lensing measurements of clusters cannot be directly transferred to stacked kSZ measurements of groups, and vice versa.
  • The same cluster population was noticeably feedback-suppressed at $z\sim2$-$4$, but its baryon fractions return toward the cosmic mean by $z=0$ through re-accretion, so local cluster gas fractions underestimate early feedback.
  • DES-style scale cuts on cosmic shear, combined with masking the rarest high-mass clusters, should keep lensing analyses close to feedback-free; explicit kernel-nulling methods should do even better.
  • If the low tSZ power at $\ell>1000$ is baryonic in origin, it must come from a mechanism that lowers gas density without raising temperature, such as ejection far into the outskirts, non-thermal pressure, or more baryons locked in stars.
  • The intermediate halo-mass range around $M_{500}\sim10^{13.5}$-$10^{14.5}\,\mathrm{M}_\odot$ is where the fiducial simulated gas masses exceed current eROSITA estimates, matching the halo-mass range where feedback variations matter most.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the $10^{12.8}\,\mathrm{M}_\odot$ trough is truly redshift-independent, baryonification and emulator models could parameterise feedback with a single characteristic mass plus a reaccretion rate, rather than fitting the full mass-redshift plane.
  • The 0.1-$0.2$ dex uncertainty in the inferred halo masses of the DESI LRG sample is testable with galaxy-galaxy lensing of the same galaxies; a measured mean mass near $10^{13.5}\,\mathrm{M}_\odot$ or higher would seriously weaken the claim that the kSZ and cluster populations are cleanly separated.
  • The same reasoning implies that future kSZ stacks around lower-mass galaxies, or tSZ and lensing measurements pushed to higher redshift, should see systematically larger feedback imprints, giving observational routes to map the efficiency trough directly.
  • The redshift independence of the characteristic mass hints that feedback efficiency is set by a fixed potential depth or binding energy threshold, which could allow the scale to be predicted from gravitational collapse energetics rather than calibrated from simulations.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper reframes baryonic feedback effects on cosmological observables in terms of halo mass assembly histories rather than the usual matter power spectrum suppression. Using analytic halo-model sensitivity calculations (tSZ power spectrum, weak-lensing two-point functions, eROSITA cluster counts) and matched hydrodynamical/gravity-only FLAMINGO simulations, it maps which halo mass and redshift populations each observable probes, and how feedback modifies the baryonic and gas content of those halos over time. The central claims are: (i) the tSZ, X-ray, and weak-lensing probes jointly target high-mass clusters (M200m ~ 10^15 Msun at z<1); (ii) stacked kSZ measurements of DESI LRGs target a distinct lower-mass population (M200m ~ 10^13.1-13.3 Msun at z ~ 0.4-1); and (iii) feedback most efficiently redistributes baryons when halos reach M200m ~ 10^12.8 Msun, independent of redshift, becoming ineffective by M200m ~ 10^15 Msun. These results are used to reconcile apparently strong kSZ-derived feedback constraints with weaker X-ray-derived constraints, and to suggest lensing analysis strategies that minimize feedback sensitivity.

Significance. If the central two-population picture holds, the paper provides a genuinely useful physical organizing principle for interpreting disparate feedback constraints: different observables simply see different stages of halo assembly. The analytic sensitivity maps (Figs. 1-3) follow standard halo-model practice, agree with previous work (e.g., To et al. 2024, Komatsu & Seljak 2002), and are clearly presented. The simulation analysis benefits from careful halo matching between hydrodynamical and gravity-only runs, from the use of multiple FLAMINGO feedback variations, and from treatment of several radial definitions (R500c, R200m, 5xR500c). The paper also offers concrete, falsifiable predictions: kSZ and X-ray/lensing constraints need not agree because they probe different populations, and lensing scale cuts such as DES's should suppress one-halo feedback sensitivity. The main significance risk is that the quantitative claims—the 10^12.8 Msun characteristic mass and the separation of the kSZ population—rest on a single simulation suite and on a stellar-mass-to-halo-mass assignment for DESI LRGs that is not independently calibrated to the kSZ host halos.

major comments (3)
  1. [Sec. IV E and Fig. 3] The kSZ halo-mass population is assigned entirely through the FLAMINGO fiducial stellar-mass-to-halo-mass relation at z=0.7. The paper states that the mean inferred mass can shift by 0.1-0.2 dex depending on the SMHM prescription and satellite fraction, but this range appears to cover only the internal variations discussed, not the full spread among published SMHM relations (e.g., Behroozi et al. 2010, Moster et al. 2010). A systematic offset of 0.3-0.5 dex in SMHM normalization or slope would move the mean kSZ halo mass to log M200m ~ 13.5-13.8, overlapping the eROSITA and weak-lensing footprints. Since the reconciliation of kSZ and X-ray constraints is the central application of this paper, the authors should quantify the robustness of the population separation under alternative SMHM relations (including abundance matching and galaxy-galaxy lensing mass estimates) or explicitly show what magnitude of SMHM offset would erase the separation.
  2. [Sec. V C and Fig. 5] The claim that feedback is most efficient at M200m ~ 10^12.8 Msun 'regardless of redshift' is measured only within the FLAMINGO subgrid models. The paper itself acknowledges in Sec. V C that 'It would be interesting to check the extent to which these findings generalize to different simulation suites.' This is a load-bearing assumption for the paper's central unifying narrative. I recommend either (a) testing the same instantaneous-mass scaling in at least one independent simulation suite or semi-empirical model, or (b) explicitly reframing the conclusion as a FLAMINGO-based result and discussing how the characteristic mass might shift under different feedback implementations beyond the fgas-8sigma and jet-AGN variants shown.
  3. [Sec. V B and Figs. 4-7] All quantitative statements about feedback impact (e.g., 5-10% mass suppression at 2<z<4 for clusters, 5-20% for lower-mass halos) are based on median histories only, with no scatter or uncertainty bands shown. Since the matched halo samples for the M200m ~ 10^15 Msun population are necessarily small, and since the conclusion that high-mass clusters are 'largely insensitive' is a strong quantitative claim, the paper should report at least the interquartile range or bootstrap uncertainties for the ratios in Figs. 4-7, or state the sample sizes that justify the median as a representative statistic.
minor comments (4)
  1. [Sec. IV B, Eq. (3)] The definition of sensitivity as the second derivative d^2 C_l / (dz d lnM) is a response density rather than a probability distribution, so the 33% and 66% contour levels in Fig. 1 are somewhat arbitrary. It would help to state explicitly that these contours are normalized to the peak of this density and that they do not integrate to a fixed fraction of the total signal by construction.
  2. [Sec. IV C, Eq. (7)] The notation dP1h/dM and dP2h/dM in Eq. (7) is used before defining them in Eqs. (8)-(9); reordering the equations or adding a sentence of orientation would improve readability.
  3. [Fig. 6 caption] The caption says 'Left panel' and 'Right panel' but the figure actually contains two groups of three rows each; the text should refer to 'left column' and 'right column' to avoid confusion, and the panel labels in the figure itself would help.
  4. [Sec. V D, Fig. 7] The middle panel is described as probing R500c of high-mass clusters, but the text says 'inner regions of groups' in one place; please align the wording (groups vs. clusters) with the mass range shown in the panel.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central feedback-mass relation is an emergent FLAMINGO result, not a fitted or self-defined target observable.

full rationale

The paper's central claims are derived from two independent ingredients: analytic halo-model sensitivity calculations for tSZ and weak lensing using external mass functions, bias models, and pressure profiles; and the FLAMINGO simulations, whose subgrid parameters are calibrated to external stellar mass function and X-ray/weak-lensing gas fraction data, not to the kSZ, tSZ, or lensing observables analyzed here. The characteristic mass M_200m ~ 10^12.8 M_sun at which feedback most efficiently redistributes baryons is an emergent property of the FLAMINGO simulations, read off Fig. 5 from the gas fraction as a function of halo mass at fixed redshift; it is not fitted to the kSZ or tSZ measurements, nor is it defined in terms of the probe sensitivities. The kSZ halo mass assignment for DESI LRGs uses the FLAMINGO stellar-mass-to-halo-mass relation, which introduces a model dependence, but this is an externally calibratable galaxy-halo connection rather than a fit to the kSZ data, and the paper explicitly tests the sensitivity to the SMHM prescription and satellite contamination, finding only a 0.1-0.2 dex shift. The reconciliation of kSZ and X-ray/tSZ constraints is an interpretive application of these independent simulation outputs, not a reduction of the output to the input. Self-citations to FLAMINGO and companion papers provide the simulation data and calibration, but they are not used as unverified uniqueness theorems or ansatz-justifying authorities. The stated limitation that the feedback results are specific to FLAMINGO's subgrid models is a generality caveat, not circularity. No equation in the paper reduces a predicted quantity to a fitted parameter by construction.

Assumptions & free parameters 1 free parameters · 4 assumptions · 0 invented entities

No new free parameters or invented entities are introduced. The central claims rest on standard halo-model ingredients, the halo identification and matching procedure, the FLAMINGO feedback calibrations, and the SMHM conversion for DESI LRGs. These are all drawn from prior literature or the simulations themselves.

free parameters (1)
  • Mass demarcation for weak feedback regime = M200m > 10^14 solar masses
    Chosen by hand in Sec. V B to split halo populations into weak and strong feedback regimes in Fig. 4. It is a plotting aid rather than a fitted parameter.
assumptions (4)
  • domain assumption The Tinker mass function and bias, Diemer and Joyce concentration-mass relation, and generalized NFW pressure profile describe the halo population and gas distribution.
    Used in Sec. IV B and IV C for the analytic tSZ and weak lensing sensitivity calculations. These are standard empirical ingredients from the literature.
  • domain assumption HBT-HERONS halo matching by the ten most-bound particles identifies the same physical halos in hydrodynamical and gravity-only simulations.
    This matching underlies all comparisons of hydro and DMO mass accretion histories in Secs. V B to V D.
  • domain assumption The FLAMINGO fiducial and enhanced-feedback simulations bracket the plausible range of baryonic feedback in the real universe.
    The paper's conclusions about feedback efficiency rely on the three FLAMINGO subgrid implementations; the authors note in Sec. V C that generalizing to other simulation suites remains to be checked.
  • domain assumption DESI LRG stellar masses map to halo masses through the FLAMINGO fiducial stellar-to-halo mass relation at z=0.7, including scatter.
    This conversion, described in Sec. IV E and Appendix A, sets the halo mass distribution for the kSZ sensitivity analysis and is the main source of systematic uncertainty in the kSZ population.

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Cite this review

Pith. "Pith review of Cosmological feedback from a halo assembly perspective." pith.science (2026). https://pith.science/paper/XAERC2JA

@misc{pith2026250518258,
  author       = {Pith},
  title        = {Pith review of: Cosmological feedback from a halo assembly perspective},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XAERC2JA}},
  note         = {Machine review of arXiv:2505.18258}
}
abstract

The impact of feedback from galaxy formation on cosmological probes is typically quantified in terms of the suppression of the matter power spectrum in hydrodynamical compared to gravity-only simulations. In this paper, we instead study how baryonic feedback impacts halo assembly histories and thereby imprints on cosmological observables. We investigate the sensitivity of the thermal Sunyaev-Zel'dovich effect (tSZ) power spectrum, X-ray number counts, weak lensing and kinetic Sunyaev-Zel'dovich (kSZ) stacked profiles to halo populations as a function of mass and redshift. We then study the imprint of different feedback implementations in the FLAMINGO suite of cosmological simulations on the assembly histories of these halo populations, as a function of radial scale. We find that kSZ profiles target lower-mass halos ($M_{200\mathrm{m}}\sim 10^{13.1}~\mathrm{M}_\odot$) compared to all other probes considered ($M_{200\mathrm{m}}\sim 10^{15}~\mathrm{M}_\odot$). Feedback is inefficient in high-mass clusters with $\sim 10^{15} \, \mathrm{M}_\odot$ at $z=0$, but was more efficient at earlier times in the same population, with a $\sim 5$-$10\%$ effect on mass at $2<z<4$ (depending on radial scale). Conversely, for lower-mass halos with $\sim10^{13}~\mathrm{M}_\odot$ at $z=0$, feedback exhibits a $\sim5$-$20\%$ effect on mass at $z=0$ but had little impact at earlier times ($z>2$). These findings are tied together by noting that, regardless of redshift, feedback most efficiently redistributes baryons when halos reach a mass of $M_{\rm 200m} \simeq {10^{12.8}}\,\mathrm{M}_{\odot}$ and ceases to have any significant effect by the time $M_{\rm 200m} \simeq {10^{15}}\,\mathrm{M}_{\odot}$. We put forward strategies for minimizing sensitivity of lensing analyses to baryonic feedback, and for exploring baryonic resolutions to the unexpectedly low tSZ power in cosmic microwave background observations.

Figures

Figures reproduced from arXiv: 2505.18258 by the authors.

Figure 1
Figure 1. FIG. 1. The sensitivity of the tSZ power spectrum to halos as a function of their mass and redshift, as defined by Eq. ( [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. The sensitivity of cosmic shear two point correlation function, [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Sensitivity of different cosmological probes to the imprint of feedback on halo populations. As illustrative probes we [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: FIG. 4. The fraction of baryon mass (left panels) and gas mass (right panels) relative to the total mass as a function of redshift [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5. The fraction of gas mass relative to the total mass as [PITH_FULL_IMAGE:figures/full_fig_p011_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6 [PITH_FULL_IMAGE:figures/full_fig_p012_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. A more detailed view of the differences in the median gas mass histories for different feedback implementations relative [PITH_FULL_IMAGE:figures/full_fig_p013_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. 2D histogram of the stellar masses (top panel) and [PITH_FULL_IMAGE:figures/full_fig_p015_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Sensitivity of cosmic shear [PITH_FULL_IMAGE:figures/full_fig_p016_9.png]

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Interpreting the stacked kinetic SZ effect I: velocity reconstruction and non-linear velocity effects

    astro-ph.CO 2026-07 conditional novelty 7.0 of 10

    Non-linear velocity terms cancel in real-space linear reconstruction, but redshift-space distortions reintroduce a 10–20% small-scale suppression of the stacked kSZ signal.

  2. Missing baryons recovered: a measurement of the gas fraction in galaxies and groups with the kinematic Sunyaev-Zel'dovich effect and CMB lensing

    astro-ph.CO 2025-07 conditional novelty 6.0 of 10

    CMB lensing mass calibration of DESI galaxies, combined with kSZ gas profiles, measures gas fractions that reach the cosmic baryon fraction at large radii but drop to about 30 percent near the virial radius.

  3. Baryonification II: Constraining feedback with X-ray and kinematic Sunyaev-Zel'dovich observations

    astro-ph.CO 2025-07 conditional novelty 6.0 of 10

    ACT kSZ and eROSITA gas fractions are mutually consistent in a baryonification fit and imply strong feedback, with predicted matter power suppression reaching 20-25 percent at k=5 h/Mpc.

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