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

T0 review · 4 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read A joint fit of kinematic Sunyaev-Zel'dovich and X-ray gas-fraction data concludes that baryonic feedback suppresses the matter power spectrum by 1–8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$ and by 20–25 percent at…

desk verdict Solid joint fit that resolves a reported kSZ-X-ray tension and makes a testable strong-feedback prediction; the main caveat is an untested redshift-independence assumption that the kSZ constraints lean on. read the letter →

arxiv 2507.07991 v1 pith:YGCWYFS5 submitted 2025-07-10 astro-ph.CO

Michael Kovač , Andrina Nicola , Jozef Bucko , Aurel Schneider , Robert Reischke , Sambit K. Giri , Romain Teyssier , Matthieu Schaller
show 1 more author
Joop Schaye
This is my paper
classification astro-ph.CO
keywords baryonicfeedbackbaryonificationkinematicSunyaev-Zel'dovicheffectX-raygasfractionsmatterpowerspectrumsuppressionlarge-scalestructureweaklensingcosmologygalaxyclusters
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

Using the component-wise baryonification (BFC) framework, which displaces particles in gravity-only N-body simulations to mimic the effects of gas and stars, the paper jointly fits stacked kinematic Sunyaev-Zel'dovich (kSZ) measurements with X-ray gas fractions from a recent survey. It reports that the two data sets are mutually consistent and both favor feedback stronger than assumed in most hydrodynamical simulations, while older gas-fraction measurements disagree with kSZ and are attributed to selection bias. The best-fit model predicts matter power-spectrum suppression exceeding one percent for wavenumbers $k\gtrsim0.3$–$0.6\,h\,\mathrm{Mpc}^{-1}$, reaching 2–8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$ and 20–25 percent at $k=5\,h\,\mathrm{Mpc}^{-1}$, tracking the strongest-feedback simulation variant. The same parameters reproduce the observed gas density and pressure profiles of massive clusters, supporting a self-consistent picture across mass scales. If correct, upcoming weak-lensing surveys must account for percent-level baryonic suppression on the small scales they exploit.

What carries the argument

The load-bearing object is the component-wise baryonification (BFC) model, which turns a gravity-only N-body simulation into a baryon-aware prediction by duplicating each particle into dark-matter and baryon copies and displacing them radially according to analytic halo profiles. The gas component is set by a density profile whose outer slope varies with halo mass through a pivot mass and a transition steepness, together with a hydrostatic-equilibrium pressure profile that includes a non-thermal pressure fraction; a two-halo term adds the correlated gas around each halo. These ingredients map the model parameters onto the kSZ temperature profile, the enclosed gas fraction $f_{\mathrm{gas},500}$, and the matter power-spectrum suppression, so one parameter set can be tested against multiple observables.

What would settle it

A measurement of the gas-fraction–mass relation at $z\approx0.55$ that disagrees with the $z\approx0.1$ relation by more than the model's 68% band would invalidate the redshift-independence assumption; alternatively, a cosmic-shear analysis finding less than about one percent suppression at $k\approx1\,h\,\mathrm{Mpc}^{-1}$ would contradict the predicted 2–8 percent suppression.

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Extended reading notes

Core claim

The paper's central claim is that baryonic feedback is strong. A single set of baryonification gas parameters can jointly explain the stacked kSZ signal from the galaxy-halo sample and the X-ray gas fractions from the recent survey, and this combined fit suppresses the matter power spectrum by more than one percent at $k\gtrsim0.3$–$0.6\,h\,\mathrm{Mpc}^{-1}$, by 2–8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$, and by 20–25 percent at $k=5\,h\,\mathrm{Mpc}^{-1}$. The paper further claims that the older, pre-survey X-ray gas-fraction compilation is in tension with the kSZ data, that this tension likely reflects selection bias in the older samples, and that the newer survey resolves it. As supporting evidence, the same best-fit parameters reproduce the gas density and pressure profiles of massive clusters without being fitted to them, which the authors interpret as the model capturing feedback across halo masses.

Load-bearing premise

The gas-profile parameters fitted at the kSZ redshift ($z\approx0.55$) are assumed to stay approximately constant down to the X-ray gas-fraction redshift ($z\approx0.1$), so any significant evolution of feedback strength over that range would be misattributed to stronger feedback.

Editorial extensions

If this is right

  • Matter-clustering analyses that use modes above $k\sim0.3\,h\,\mathrm{Mpc}^{-1}$ must include baryonic feedback corrections at the percent level or risk biased cosmological parameters.
  • The joint kSZ plus X-ray data favor a strong-feedback scenario close to the strongest hydrodynamical simulation variant, not the fiducial feedback model calibrated on older X-ray data.
  • The older gas-fraction samples should be revisited with consistent mass estimates, since the paper attributes their disagreement with kSZ to selection bias rather than to the feedback model.
  • The calibrated baryonification parameters provide an explicit, testable prediction for the matter power-spectrum suppression that weak-lensing surveys can verify independently.
  • Because the same parameters also reproduce cluster-scale gas and pressure profiles, the framework is ready to be used in joint cosmological and baryonic analyses of upcoming multiwavelength surveys.

Reading between the lines

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

  • If strong feedback is confirmed, cosmic-shear surveys will need to treat baryonic suppression as a percent-level systematic; the predicted suppression curve gives a concrete prior to fold into or cross-check emulators.
  • A sharp test of the redshift-independence assumption would be to measure the gas-fraction–mass relation at the kSZ redshift and compare it with the lower-redshift X-ray relation; any significant evolution would change the inferred suppression amplitude.
  • The same framework could be inverted to constrain cosmology and feedback simultaneously by adding thermal Sunyaev-Zel'dovich and X-ray surface-brightness data, where the non-thermal pressure component matters.
  • The older-data discrepancy suggests that compilations mixing hydrostatic-mass-based X-ray samples need explicit selection-function modeling; a mass-matched reanalysis would show whether the offset is purely selection-driven.
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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

4 major / 5 minor

Summary. The paper uses the component-wise baryonification (BFC) framework of Paper I to jointly fit ACT kinematic Sunyaev-Zel'dovich (kSZ) measurements of BOSS CMASS halos and eROSITA X-ray gas fractions, with the goal of constraining baryonic feedback without calibrating to hydrodynamical simulations. The authors find that the two data sets are mutually consistent and jointly favor strong feedback, corresponding to gas fractions close to the FLAMINGO fgas–8σ model. Using the best-fit parameters they predict a matter power spectrum suppression exceeding 1% at k > 0.3–0.6 h/Mpc and reaching 20–25% at k = 5 h/Mpc. They also compare the predicted gas density and pressure profiles with X-COP cluster observations and report good agreement. A parallel fit using pre-eROSITA gas fractions is found to be in tension with the kSZ data, which the authors attribute to selection effects and mass-estimation differences.

Significance. If the central result holds, it implies that baryonic feedback is strong enough to require percent-level corrections to matter clustering on scales relevant for upcoming weak-lensing surveys, and it demonstrates that a single baryonification parameter set can describe kSZ, X-ray gas fractions, and cluster profiles. The paper is commendable for using public observational data, for reporting goodness-of-fit statistics (χ2 = 24.57, PTE = 0.41 for the joint eROSITA fit), for performing a documented parameter-reduction analysis, and for including a satellite-contribution robustness check in Appendix F. The predicted power-spectrum suppression is a concrete, falsifiable output that can be compared with future lensing and clustering measurements. However, the main inference rests on assumptions that are stated but not stress-tested, most notably the redshift independence of the BFC gas parameters between the kSZ and eROSITA epochs, and these assumptions need to be addressed before the strong-feedback conclusion can be considered secure.

major comments (4)
  1. [Sec. 5.1 and Fig. 5] The joint fit assumes that the BFC gas parameters Mc, µ, and δ are approximately constant between z ≈ 0.1 (eROSITA) and z ≈ 0.55 (ACT kSZ), with the justification deferred to Paper I. This assumption is load-bearing: Fig. 5 shows that the eROSITA-only fit predicts substantially weaker suppression and that the kSZ data drive the strong-feedback conclusion. If these parameters evolve over this redshift range, the joint fit would mix two different epochs and the z = 0 suppression curve in Fig. 5 would be biased. No sensitivity test is presented. Please add one, for example by allowing a simple redshift dependence in Mc or δ and re-fitting, or by comparing the parameter posteriors from kSZ-only and eROSITA-only fits as a bound on the systematic.
  2. [Sec. 4.2.1 and Fig. 1] The three lowest-mass eROSITA gas-fraction points (M500 < 10^13 M_sun) are excluded with the statement that the results are insensitive to this choice, but no fit including these points is shown. This matters because those masses overlap the kSZ sample mean (M200,ksz ≈ 3 × 10^13 M_sun), and the low-mass shape of fgas(M) is precisely where the kSZ data impose suppression. Please include the excluded points in a robustness fit, or present the posterior shift and the resulting change in the predicted P(k) suppression; if the insensitivity claim is correct, this is a one-figure test.
  3. [Sec. 5.1 and Table 2] The gas-fraction likelihood uses only the diagonal entries of the covariance matrix, explicitly neglecting correlations between data points. The eROSITA gas fractions are derived from stacked X-ray surface-brightness profiles with shared mass calibration, so bin-to-bin correlations are expected. The quoted χ2 = 2.00 (PTE = 0.82) for the gas-fraction data alone and the joint PTE = 0.41 may therefore be overconfident, and the consistency statement between kSZ and eROSITA could be weakened under a more realistic covariance. Please provide an estimate of the correlation matrix, or repeat the fit under a conservative correlation model, and report how the PTE and parameter constraints change.
  4. [Sec. 6.2.1 and Fig. 4] The X-COP comparison is presented as 'excellent agreement' and as evidence that the model is predictive across mass scales. However, the X-COP cluster masses are used as inputs when computing the predicted profiles, and the comparison is made at z = 0.065 while the model parameters were constrained partly at z ≈ 0.55. This is not circular, but the role of the assumed masses and the redshift extrapolation should be quantified, for example by varying the X-COP masses within their reported uncertainties and re-computing the profile comparison. The current statement that the model 'reproduces' X-COP is stronger than what the test supports without this sensitivity check.
minor comments (5)
  1. [Sec. 5.1] Typo: 'theses parameters' should be 'these parameters'.
  2. [Table 1] The parameter α0,nt is listed without a prior distribution, while other free parameters have priors; please clarify whether it is fixed or sampled and, if sampled, specify its prior.
  3. [Sec. 6.2.1 and footnote 11] The notation z1 and z2 in the footnote is confusing; please define explicitly (e.g., z_obs = 0.065 and z_sim = 0.1) or use descriptive subscripts.
  4. [Sec. 4.2.2] The discussion of selection biases in pre-eROSITA samples is plausible but speculative; the text should more clearly separate this interpretation from the measured tension, since the central conclusion of the paper does not depend on it.
  5. [Sec. 2.3] The two-halo approximation is stated to agree with the exact result to 1–2%, but the associated figure (Fig. 6) is in Appendix A; a brief pointer in the main text would help the reader.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the P(k) suppression and X-COP comparison are genuine model predictions derived from parameters fitted to kSZ and eROSITA, not re-statements of the input data.

full rationale

The derivation chain is not circular. The BFC gas parameters (Mc, mu, delta) are fit to ACT kSZ and eROSITA fgas,500 via Eq. (5.1); the matter power spectrum suppression in Fig. 5 is computed by baryonifying an N-body simulation with the resulting best-fit parameters. P(k) does not appear in the likelihood, so the suppression is a genuine derived prediction rather than a fitted quantity relabelled as a prediction. The X-COP density and pressure comparison in Fig. 4 is also not in the likelihood; although the X-COP mass range overlaps the eROSITA fgas data, the resolved 3D profiles are different observables from the integrated fgas,500 used in the fit, and the paper explicitly states that only the masses of the X-COP sample are used. The label 'predicted gas fractions' on Fig. 1 refers to the best-fit model evaluated against the fitted eROSITA data; this is loose presentation but not an independent predictive claim and therefore not a fitted-input-called-prediction step. The redshift-independence assumption stated in Sec. 5.1 is a modelling assumption (parameters constant between z=0 and z=0.55) justified by Paper I's Fig. 11; it does not force any output to equal an input by construction, though it is a legitimate limitation and should be weighed as a correctness risk. Self-citations to Paper I and to FLAMINGO [38] are used for model construction and robustness checks, but the central strong-feedback claim is supported by the jointly fitted parameters and the resulting P(k) prediction, which do not reduce to those citations. No equation or fitted parameter is renamed as a prediction, and no uniqueness theorem is imported from the authors' prior work.

Assumptions & free parameters 11 free parameters · 8 assumptions · 0 invented entities

The joint inference is driven by four fitted parameters (Mc, mu, delta, M200,ksz) plus the hydrostatic bias in the pre-eROSITA fit. A larger set of profile and fraction parameters is fixed by hand or inherited from Paper I, and two shape parameters in Eq. 2.6 (alpha, gamma) are not tabulated. The redshift-independence and central-galaxy-only assumptions are the most consequential domain choices. No new physical entities are introduced.

free parameters (11)
  • log10 Mc (pivot mass) = posterior (Fig. 10)
    Mass scale of the gas-profile slope transition; fitted jointly to kSZ and gas fractions; the kSZ and pre-eROSITA data favor different values, causing tension.
  • mu (transition steepness) = posterior (Fig. 10)
    Sharpness of the mass-dependent slope transition; constrained primarily by gas-fraction data.
  • delta (outer profile slope) = posterior (Fig. 10)
    Truncation sharpness of the gas profile; most tightly constrained by the kSZ data.
  • M200,ksz (effective kSZ halo mass) = posterior (Fig. 10)
    Mean halo mass of the CMASS kSZ sample; left free in the fit and recovered consistent with independent estimates (log10 M500c = 13.34 in Ref. [38]).
  • b_hse (hydrostatic mass bias) = posterior (pre-eROSITA fit only)
    Gaussian prior N(0.26,0.07) from Hurier and Angulo; applied only when fitting pre-eROSITA gas fractions.
  • theta_co (core radius scale) = 0.3 (fixed)
    Core radius of the hot gas profile relative to r200; fixed in parameter reduction because it mainly affects inner regions not probed by the observables.
  • eta, d_eta, Nstar (stellar fraction parameters) = 0.1, 0.22, 0.030 (fixed)
    Stellar mass fraction shape and normalization; fixed from Paper I best-fit stellar profile values for the 3p fit, varied in the 6p robustness fit.
  • ciga (cold gas fraction) = 0.1 (fixed)
    Fraction of cold inner gas relative to central galaxy stars; fixed in parameter reduction due to negligible effect on kSZ and fgas.
  • alpha0,nt (non-thermal pressure amplitude) = 0.1 (fixed)
    Mean non-thermal to total pressure ratio at z=0; affects the X-COP pressure comparison but not the kSZ or gas-fraction likelihood.
  • alpha, gamma (gas profile shape parameters, Eq. 2.6) = not listed in Table 1
    These parameters appear in Eq. 2.6 but are absent from the parameter table and appendix summaries; presumably fixed in Paper I, but the printed model is underspecified.
  • epsilon0, epsilon1 (NFW truncation parameters) = 4.0, 0.5 (fixed)
    Set the halo truncation radius rt = epsilon(M) r200, following Ref. [49]; affect the outer gas profile and the two-halo normalization.
assumptions (8)
  • domain assumption Gas in halos moves coherently with the halo bulk velocity, so the kSZ signal factorizes into halo optical depth times a fixed rms velocity vr = 1.06e-3 c (Eqs. 2.17-2.19).
    Standard for kSZ stacking analyses; ignores internal gas velocity structure. Entered in Sec 2.2 and justified by common practice in Refs. [40,55,56].
  • domain assumption BFC gas parameters are redshift-independent between z~0 and z~0.55.
    Sec 5.1: 'we assume they remain approximately constant between z=0 and z=0.55', justified by weak evolution in Paper I. If feedback evolves over this range, the joint kSZ (z=0.55) + eROSITA (z~0.1) fit would be biased.
  • domain assumption Hydrostatic equilibrium plus a non-thermal pressure model give the halo pressure profile (Eqs. 2.14-2.16).
    Used only for the X-COP pressure comparison, not for the kSZ or gas-fraction fits; inaccurate for unrelaxed or low-mass halos, as the text acknowledges.
  • ad hoc to paper The analytic gas, stellar, and fraction parameterization (Eqs. 2.6-2.13) is flexible enough to describe baryon redistribution across mass and redshift.
    This is the paper's chosen model, validated in Paper I against FLAMINGO and IllustrisTNG. Model rigidity could bias the inferred feedback strength if the true gas distribution has a different functional form.
  • domain assumption The approximate two-halo term with halo exclusion (Eqs. 2.23-2.28, Ae=0.4) is accurate to 1-2 percent in the relevant radial range.
    Checked in Appendix A and Fig. 6; the approximation error is small compared to current data uncertainties but is still an approximation.
  • domain assumption The CMASS kSZ signal comes only from central galaxies; satellite contributions are neglected in the fiducial fit.
    Sec 6.1.1 and Appendix F; satellites could add 20-30 percent to the predicted kSZ signal. The paper rescales with Ref. [38] and finds results robust at current signal-to-noise.
  • standard math Sheth-Tormen bias and Tinker08 mass function supply the halo bias and mass function (Sec 2.3).
    Standard halo-model ingredients implemented in CCL; the integration mass range 1e10-1e15 Msun changes results by less than 2 percent.
  • domain assumption The fiducial FLAMINGO cosmology (Omega_m=0.306, Omega_b=0.0486, sigma8=0.807, H0=68.1, ns=0.967) is fixed throughout.
    Sec 1: the paper fixes this cosmology and does not marginalize over it; incorrect cosmology would shift gas fractions and kSZ predictions, though this is common for feedback-constraint studies.

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Cite this review

Pith. "Pith review of Baryonification II: Constraining feedback with X-ray and kinematic Sunyaev-Zel'dovich observations." pith.science (2026). https://pith.science/paper/YGCWYFS5

@misc{pith2026250707991,
  author       = {Pith},
  title        = {Pith review of: Baryonification II: Constraining feedback with X-ray and kinematic Sunyaev-Zel'dovich observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YGCWYFS5}},
  note         = {Machine review of arXiv:2507.07991}
}
abstract

Baryonic feedback alters the matter distribution on small and intermediate scales, posing a challenge for precision cosmology. The new, component-wise baryonification (BFC) approach provides a self-consistent framework to model feedback effects for different observables. In this paper we use this framework to fit kinematic Sunyaev-Zel'dovich (kSZ) observations from the Atacama Cosmology Telescope (ACT) alongside halo X-ray gas fractions from eROSITA, investigating baryonic feedback in a cosmological context. We first show that the kSZ data from ACT is consistent with the gas fractions from eROSITA, both suggesting a feedback model that is stronger than what is assumed in most hydrodynamical simulations. This finding is in contrast to older, pre-eROSITA gas fraction measurements that point towards weaker feedback in tension with the kSZ results. We suspect these discrepancies to be due to selection bias in the pre-eROSITA sample, or differences in halo mass estimation between the two data sets. In a further step, we use the BFC model to predict the baryonic suppression of the matter power spectrum. Based on our combined fit to data from ACT and eROSITA, we find a power spectrum suppression that exceeds the percent-level at modes above $k=0.3-0.6 \,h\,\mathrm{Mpc}^{-1}$, growing to 2-8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$, and to 20-25 percent at $k=5\,h\,\mathrm{Mpc}^{-1}$, consistent with strong-feedback hydrodynamical simulations. Finally, we compare our best-fitting model to the observed gas density and pressure profiles of massive galaxy clusters from the X-COP sample, finding excellent agreement. These results show that BFC provides a self-consistent picture of feedback across mass- and length scales as well as different cosmological observables, thus making it promising for applications to multiwavelength studies to jointly constrain cosmology and baryonic effects.

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Forward citations

Cited by 8 Pith papers

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Reference graph

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