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REVIEW 4 major objections 6 minor 65 references

This paper claims that group-scale halos dominate the baryonic suppression of the matter power spectrum, and that the same mass regime should leave a detectable imprint in stacked group-galaxy lensing.

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 →

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Group-scale halos (M200m ~ 10^13-10^14 Msun) drive most of the baryonic suppression of small-scale matter clustering, contributing about 10 of the ~20% total reduction in power.

T0 review reviewed 2026-08-03 challenge →

load-bearing objection Group-scale halos dominate baryonic P(k) suppression in TNG — a useful extension of van Loon & van Daalen, but the mass-conservation prescription needs validation before the 60% share is taken at face value. the 4 major comments →

arxiv 2511.10634 v3 pith:3KOSOQPX submitted 2025-11-13 astro-ph.CO

Baryonic Feedback across Halo Mass: Impact on the Matter Power Spectrum

Kyle Miller , Surhud More , Bhuvnesh Jain This is my paper
classification astro-ph.CO
keywords baryonic feedbackmatter power spectrumhalo mass dependenceweak gravitational lensinggroup-scale halosmass conservationhybrid simulationsIllustrisTNG
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 asks which halos are responsible for the small-scale suppression of matter clustering caused by baryonic feedback, and whether that signal can be seen in weak lensing. Using the IllustrisTNG simulations, it builds hybrid snapshots that replace gravity-only halo particles with full-physics particles out to a chosen radius, then measures the matter power spectrum. The central finding is that group-scale halos near 10^13 to 10^14 solar masses produce the dominant suppression, contributing roughly 10 percentage points of the total ~20 percent drop, while lower-mass and cluster-scale halos each contribute only a few percent. This near-additive, mass-dependent suppression should appear as a characteristic residual in stacked group-galaxy lensing, offering an observational test of feedback models. A sympathetic reader would care because upcoming weak-lensing surveys will reach the scales where this effect matters, and knowing which halo masses drive it tells theorists what to model and observers where to look.

Core claim

The paper establishes that baryonic feedback suppresses the matter power spectrum non-monotonically with halo mass: halos with M200m between 10^13 and 10^14 h^-1 Msun cause roughly 10 percent of the total suppression, about 60 percent of the effect from all resolved halos above 10^12, with smaller contributions from lower- and higher-mass halos. It also shows that the suppression from different mass bins adds almost linearly, meaning different halo populations act independently. Reproducing the full suppression requires redistributing matter beyond the virial radius while conserving mass, and the same group-scale regime produces the most detectable deviations in the differential surface dens

What carries the argument

The central device is a hybrid-snapshot construction: matched halos between the gravity-only and full-physics simulations are identified, and all particles within a sphere of radius alpha times R200m around each gravity-only halo are replaced with their full-physics counterparts, with alpha ranging from 0.5 to 2.0. To enforce mass conservation, the mass deficit from replacement is uniformly redistributed over a shell extending to twice the replacement radius, mimicking ejected baryons. Measuring the power spectrum of these modified snapshots, for individual mass bins or pairs of bins, isolates each halo population's contribution to suppression; the near-additivity of the per-bin suppressions

Load-bearing premise

The numbers stand on the assumption that swapping gravity-only particles inside a sphere of radius alpha R200m with full-physics particles, then spreading the mass deficit uniformly over a shell out to twice that radius, faithfully captures the full effect of baryonic feedback on each halo's surroundings without re-evolving the simulation.

What would settle it

Re-run one of the hybrid snapshots with the region outside the replacement radius allowed to respond dynamically to the injected redistribution: if the resulting power-spectrum suppression differs from the static hybrid prediction by more than the quoted few-percent level, the attribution scheme fails. Observationally, measure stacked group-galaxy lensing residuals in the 10^13 to 10^14 Msun bin; if the peak suppression shifts to another mass bin, the central claim is wrong.

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

If this is right

  • Nearly 90 percent of the total baryonic suppression of the matter power spectrum, which reaches about 20 percent at k ~ 10 h/Mpc, comes from halos above 10^12 h^-1 Msun.
  • Group-scale halos in the range 10^13 to 10^14 h^-1 Msun contribute roughly 10 percentage points of suppression, about 60 percent of the resolved-halo effect, with the contribution peaking at group scales.
  • The suppression from different halo mass bins adds linearly, so the total baryonic impact can be modeled as a superposition of independent mass-bin contributions.
  • The same group-scale regime produces the largest detectable deviations in stacked group-galaxy lensing, providing a direct observational probe of feedback models.
  • The results motivate emulators that jointly predict the matter power spectrum and halo-matter cross-correlations with baryonic effects included, enabling unbiased cosmological inference from small scales.

Where Pith is reading between the lines

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

  • If the group-scale dominance is robust across feedback prescriptions, then baryonic-correction models should prioritize reproducing the group regime; tuning only the total power spectrum can hide incorrect mass-dependent redistribution.
  • The near-additivity suggests a fast forward model: the suppression can be approximated as a sum over halo mass bins weighted by the mass fraction in each bin, enabling cheap emulators that predict both the power spectrum and halo-matter cross-spectrum.
  • Because the paper notes that the IllustrisTNG feedback prescription may underestimate feedback inferred from kinetic SZ observations, the quantitative percentages are likely lower bounds if real feedback is stronger, though the qualitative group-scale peak may persist.
  • The non-monotonic mass dependence could serve as a discriminator between feedback models: models that eject more gas from massive halos would shift the peak suppression to higher masses, and measuring the peak location in stacked group lensing would constrain feedback strength.
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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

4 major / 6 minor

Summary. The paper uses the IllustrisTNG300-1 and TNG300-1-Dark simulations, which share initial conditions, to isolate the contribution of baryonic feedback to the suppression of the matter power spectrum as a function of halo mass and radial scale. The authors construct hybrid snapshots by replacing gravity-only particles inside spheres of radius αR200m around matched halos with full-physics particles, then enforce global and halo-by-halo mass conservation by uniformly redistributing the mass deficit into a shell out to 2αR200m. Measuring P/P_GO, they find that group-scale halos with log M200m ∈ [13,14] dominate, contributing roughly 10 percentage points of the ~20% total suppression and about 60% of the effect from all halos above 10^12 Msun. They also report that the suppression is approximately additive across mass bins and that reproducing the full suppression requires redistributing matter beyond the virial radius. They translate these results into predicted group-galaxy lensing signals, arguing that stacked lensing by halo mass or group richness can provide an observational discriminant of feedback models.

Significance. If correct, the central result is significant: it identifies the halo-mass range that dominates baryonic suppression, demonstrates an approximate additivity that would simplify analytic models and emulators, and connects the power-spectrum suppression to a directly observable stacked-lensing signature. The paper has notable strengths: it uses matched full-physics and gravity-only simulations, carefully handles mass conservation with a physically motivated shell-redistribution scheme, tests robustness to replacement radius, compares with earlier BAHAMAS/cosmo-OWLS results, and makes a concrete, falsifiable prediction for group-galaxy lensing. The main limitation is that the hybrid-snapshot attribution device is not directly validated against the true radial mass redistribution in TNG, and the reported per-bin percentages carry no error bars. These issues affect the quantitative claims but are addressable within the scope of the manuscript.

major comments (4)
  1. [Sec. 3.1, Appendix A, Table 1] The headline per-bin suppression percentages and the derived ~60% group-halo share rest on the assumption that replacing the inner αR200m region with full-physics particles plus uniformly redistributing the mass deficit over [αR200m, 2αR200m] captures the complete TNG back-reaction. This is not demonstrated. Appendix A says 'various factors' were tried and conclusions were robust, but no curves or numbers are shown, and the fiducial shell is not checked against the actual radial mass profile of matched halos in TNG. Moreover, the statement in Sec. 3.1 that 'the relative contribution of each halo mass bin to suppression is entirely unchanged by this mass conservation method' is not supported by Fig. 5, where the two methods produce different P/P curves. Please validate the construction: (i) compare the 12+ hybrid suppression to the true full-physics suppression for each α, and (ii) measur
  2. [Sec. 4.1, Table 1] No measurement uncertainties are given. The power spectra come from a single TNG300 box, and the ratios in Figure 1 and Table 1 are presented without jackknife, bootstrap, or replicate errors. The paper interprets differences as small as 0.1-0.3 percentage points between α values (e.g., rows 12-12.5: 1.7 vs. 1.6; 13.5-14: 5.3 vs. 5.5) as evidence for radial dependence, and the headline '~60% from group halos' is a ratio of two measured suppressions whose uncertainties are unknown. A fractional error of even 0.5 percentage points in the denominator (the 12+ suppression) changes the reported share by several percent. Please provide bootstrap or jackknife error estimates over subvolumes, or otherwise quantify the pixelization/aliasing uncertainty in the FFT measurements, and state whether the mass-bin differences are statistically significant.
  3. [Sec. 3.1 and Sec. 4.1] The hard halo-exclusion scheme removes overlapping replacement regions, with about 20% of halos excluded for α=2 when all mass bins are replaced. The authors acknowledge this 'likely leads to a small underestimate' for large radii, but the excluded fraction varies with halo mass and radius. This could bias the mass-dependent radial trends reported in Sec. 4.1, in particular the decrease in suppression for low-mass halos with increasing α and the increase for high-mass halos, if low-mass halos inside groups are preferentially excluded. Please quantify the mass fraction excluded per bin and per α, and test sensitivity to an alternative overlap-assignment method that avoids artificial gaps (e.g., assigning overlapping particles to the most massive parent with explicit boundary handling).
  4. [Sec. 4.1, Fig. 2] The additivity claim is supported by only two illustrative examples and by the phrase 'nearly identical' without a quantitative tolerance. Since additivity is a central motivation for the proposed emulator/superposition modeling, it should be tested systematically: for each pairwise mass-bin combination in Table 1, compute the maximum difference between the summed individual-bin P/P ratios and the jointly replaced snapshot, and report a statistical criterion for agreement. The current visual inspection in Fig. 2 is not sufficient, especially because the mass-conservation shell itself introduces an additive component that could trivially make the sum work.
minor comments (6)
  1. [Sec. 4.1] The sentence 'the modification accounts for more 90% the total suppression' appears to contain a typo ('more' should be 'more than'). Also, the numeric support is not correct: Table 1 gives 17.8/20.7 ≈ 86% for α=0.5, about 84% for α=1, and 82% for α=2. Please revise to 'nearly 90%' or state the actual percentages.
  2. [Sec. 4.1, Eq. (4.1)] The statement that the effect 'is thus largest in the mass bin which contributes most to the mass fraction' is not quantitatively supported by the quoted numbers. The mass fraction in [13,14] is 8.4% versus 7.8% in [12,13], yet the suppression is 10.0% versus 5.2%. The mass dependence of suppression is much stronger than the mass-fraction dependence; please qualify this interpretation.
  3. [Sec. 4.2, Fig. 3] The text describing Fig. 3 appears to have a panel mix-up: the 'left-hand panel' is said to show the relative difference between full-physics and gravity-only profiles, but the right-hand panel is the residual plot. Please check the references to left/middle/right panels.
  4. [Fig. 3] The axis labels contain '10□1' and '10□2' placeholders; these should be typeset as 10^{-1} and 10^0 (or similar).
  5. [Section 5, bullet list] The bullet 'Effects of feedback ... redistributing some fraction of this mass expelled ... at a distance about 1.5 times larger' is vague. Specify the shell radius used (e.g., from Rreplace to 2Rreplace, which is 1.5 times larger than R_replace on average, or give the exact prescription).
  6. [Table 1] Typographical issue: the caption says 'T able 1' with a space. Also consider adding units (h^{-1} M_sun) consistently for the mass bins.

Circularity Check

0 steps flagged

No significant circularity: the suppression fractions are measured from hybrid snapshots, not fitted; additivity and the mass-fraction comparison are independent checks.

full rationale

The paper's central result—that group-scale halos dominate the matter-power suppression—is obtained by directly replacing gravity-only particles with full-physics particles inside alpha*R200m for each matched halo and then measuring P/P_GO from the resulting hybrid snapshot. This is a measurement-based attribution, not a prediction derived from fitted inputs. The comparison to the halo mass fraction in Eq. (4.1) is post hoc: the mass fractions (7.8, 8.4, 4.3 percent) are computed independently from the halo mass function and are not inputs to the hybrid construction. The additivity of suppression across mass bins is demonstrated empirically in Fig. 2 by comparing simultaneous replacement with the sum of single-bin replacements, rather than assumed. The mass-conservation redistributions are modeling choices, but Appendix A states that the conclusions are robust to the redistribution radius and explicitly compares a mass-rescaling alternative; this is a validation concern, not circularity. The self-citations ([29], [46]) are background or technical references and are not load-bearing for the main attribution. The acknowledged dependence on IllustrisTNG's feedback prescription and the external caveat of [22] are statements of model dependence and external falsifiability, not circular steps. No equation or parameter in the paper is equivalent by construction to the claimed suppression fractions.

Axiom & Free-Parameter Ledger

3 free parameters · 6 axioms · 0 invented entities

No free parameters are fitted to make the result work: the per-bin suppressions are direct measurements. The hand-chosen elements are the replacement radii alpha (0.5-2 x R200m), the hard-exclusion rule, and the mass-conservation scheme (uniform redistribution over [R,2R]); the authors test sensitivity to the shell choice and compare two conservation schemes, stating relative bin contributions are unchanged. The load-bearing input is the IllustrisTNG feedback model itself, plus the validity of the pasting construction - both are domain assumptions, not fitted parameters. No new entities are postulated.

free parameters (3)
  • Mass-conservation shell extent = 2 x R_replace (fiducial; varied in tests)
    Mass deficit of each halo is uniformly distributed over the shell [R_replace, 2 R_replace] (Sec. 3.1, App. A). The authors state they experimented with other shell factors and conclusions are robust; the choice affects the small-scale suppression amplitude.
  • Mass-conservation prescription (uniform shell redistribution vs. local particle rescaling) = Uniform shell redistribution (fiducial); rescaling tested and rejected
    The two schemes in Fig. 5 give different small-scale suppression amplitudes; the fiducial is chosen because it preserves the physical expulsion effect. Relative bin contributions are stated to be unchanged, but this is asserted, not shown in detail.
  • Hard halo exclusion for overlapping replacement regions = Exclusive replacement assigned to the more massive halo
    Overlapping halos are excluded (~5-20% of halos at large alpha); the authors acknowledge this causes a small underestimate of suppression at large replacement radii (Sec. 3.1).
axioms (6)
  • domain assumption IllustrisTNG's subgrid prescriptions (AGN, SN feedback) are a representative realization of baryonic feedback
    The whole attribution exercise measures TNG's feedback. The paper itself notes [22] finds TNG underestimates feedback observed in kSZ clusters, so quantitative values may be lower limits (Sec. 4.2).
  • domain assumption Pasting full-physics particles into a gravity-only snapshot without re-evolving the box is a valid controlled decomposition
    Replaced particles are not dynamically relaxed; the surrounding gravity-only medium is unperturbed except for the uniform mass-conservation shell (Sec. 3.1, App. A).
  • domain assumption LHaloTree bidirectional matching via firstSubSubhalo correctly identifies corresponding halos between TNG300-1 and TNG300-1-Dark
    About 3% of halos have no match and are ignored (Sec. 2.1); mismatches would mis-attribute suppression across mass bins.
  • domain assumption Redshift evolution of the suppression is mild for z<~1
    z=0 measurements are applied to cosmic shear observables peaking near z~0.5, citing [57] for mild evolution (Sec. 5.1).
  • domain assumption Mass conservation via uniform shell redistribution removes the spurious large-scale boost without changing relative bin contributions
    Checked in Fig. 5 and stated in Sec. 3.1/App. A; the invariance of relative contributions is asserted, and the shell width is tested only for robustness of the qualitative conclusions.
  • standard math Standard FFT/folding power spectrum methodology and jackknife resampling
    Used in Sec. 3.2 (Nbodykit, self-folding per Jenkins et al. 1998); no new mathematical claims are made.

reviewed 2026-08-03 · how reviews work

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Cite this review

Pith. "Pith review of Baryonic Feedback across Halo Mass: Impact on the Matter Power Spectrum." pith.science (2026). https://pith.science/paper/3KOSOQPX

@misc{pith2026251110634,
  author       = {Pith},
  title        = {Pith review of: Baryonic Feedback across Halo Mass: Impact on the Matter Power Spectrum},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3KOSOQPX}},
  note         = {Machine review of arXiv:2511.10634}
}
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abstract

Upcoming weak-lensing surveys will probe the matter distribution at a few percent level on nonlinear scales ($k>1\,{\rm h\,Mpc}^{-1}$) where baryonic feedback from galaxy formation modifies the clustering of matter. Using the IllustrisTNG hydrodynamical simulations, we quantify the mass and radial dependence of baryonic suppression of the matter power spectrum by selectively replacing matter around the center of halos out to a specified radius in the collisionless run with that around their full-physics counterparts. We find that group-scale halos with $\log M_{\rm 200m}/h^{-1}M_\odot \in[13, 14]$ dominate the suppression, contributing a large fraction of the total reduction in power at $k\sim2-30\,h\,{\rm Mpc}^{-1}$, with smaller suppression on either sides of this mass bin. Correctly reproducing the full suppression of the power spectrum requires accounting for matter redistribution (while enforcing mass conservation) beyond the virial radius of each halo. We show that the same group-scale regime produces the most detectable deviations in the weak gravitational lensing of background galaxies measured around foreground galaxy groups binned by mass or richness. Such a lensing signal could be a powerful observational test of feedback models together with SZ measurements. Our results motivate emulators that jointly predict the matter power spectrum and halo-matter cross-power spectrum including baryonic effects, enabling unbiased cosmological inference from small scales.

discussion (0)

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Reference graph

Works this paper leans on

65 extracted references · 15 linked inside Pith

  1. [1]

    Acevedo, H

    J.F. Acevedo, H. An, Y. Boukhtouchen, J. Bramante, M.L.A. Richardson and L. Sansom,Dark matter induced baryonic feedback in galaxies,Phys. Rev. D110(2024) 083004

    2024

  2. [2]

    Biernacki and R

    P. Biernacki and R. Teyssier,The combined effect of agn and supernovae feedback in launching massive molecular outflows in high-redshift galaxies,Monthly Notices of the Royal Astronomical Society475(2018) 5688–5703

    2018

  3. [3]

    Chisari, A.J

    N.E. Chisari, A.J. Mead, S. Joudaki, P.G. Ferreira, A. Schneider, J. Mohr et al.,Modelling baryonic feedback for survey cosmology,The Open Journal of Astrophysics2(2019)

    2019

  4. [4]

    Duffy, J

    A.R. Duffy, J. Schaye, S.T. Kay, C. Dalla Vecchia, R.A. Battye and C.M. Booth,Impact of baryon physics on dark matter structures: a detailed simulation study of halo density profiles, Mon. Not. Roy. Astron. Soc.405(2010) 2161 [1001.3447]

    Pith/arXiv arXiv 2010

  5. [5]

    van Daalen, J

    M.P. van Daalen, J. Schaye, C.M. Booth and C. Dalla Vecchia,The effects of galaxy formation on the matter power spectrum: a challenge for precision cosmology: Galaxy formation and the matter power spectrum,Monthly Notices of the Royal Astronomical Society415(2011) 3649–3665

    2011

  6. [6]

    Velliscig, M.P

    M. Velliscig, M.P. van Daalen, J. Schaye, I.G. McCarthy, M. Cacciato, A.M.C. Le Brun et al., The impact of galaxy formation on the total mass, mass profile and abundance of haloes, Mon. Not. Roy. Astron. Soc.442(2014) 2641 [1402.4461]

    Pith/arXiv arXiv 2014

  7. [7]

    Gebhardt, D

    M. Gebhardt, D. Angl´ es-Alc´ azar, J. Borrow, S. Genel, F. Villaescusa-Navarro, Y. Ni et al., Cosmological baryon spread and impact on matter clustering in camels, 2023

    2023

  8. [8]

    Schaye, R.A

    J. Schaye, R.A. Crain, R.G. Bower, M. Furlong, M. Schaller, T. Theuns et al.,The eagle project: simulating the evolution and assembly of galaxies and their environments,Monthly Notices of the Royal Astronomical Society446(2014) 521–554

    2014

  9. [9]

    Nicola, F

    A. Nicola, F. Villaescusa-Navarro, D.N. Spergel, J. Dunkley, D. Angl´ es-Alc´ azar, R. Dav´ e et al., Breaking baryon-cosmology degeneracy with the electron density power spectrum,Journal of Cosmology and Astroparticle Physics2022(2022) 046

    2022

  10. [10]

    Pandey, J.C

    S. Pandey, J.C. Hill, A. Alarcon, O. Alves, A. Amon, D. Anbajagane et al.,Constraints on cosmology and baryonic feedback with joint analysis of dark energy survey year 3 lensing data and act dr6 thermal sunyaev-zel’dovich effect observations, 2025

    2025

  11. [11]

    A. Chen, G. Aric` o, D. Huterer, R.E. Angulo, N. Weaverdyck, O. Friedrich et al.,Constraining the baryonic feedback with cosmic shear using the des year-3 small-scale measurements, Monthly Notices of the Royal Astronomical Society518(2022) 5340–5355

    2022

  12. [12]

    Semboloni, H

    E. Semboloni, H. Hoekstra, J. Schaye, M.P. van Daalen and I.G. McCarthy,Quantifying the effect of baryon physics on weak lensing tomography: Baryon physics and weak lensing tomography,Monthly Notices of the Royal Astronomical Society417(2011) 2020–2035

    2011

  13. [13]

    Zentner, E

    A.R. Zentner, E. Semboloni, S. Dodelson, T. Eifler, E. Krause and A.P. Hearin,Accounting for baryons in cosmological constraints from cosmic shear,Physical Review D87(2013)

    2013

  14. [14]

    van Loon and M.P

    M.L. van Loon and M.P. van Daalen,The contribution of massive haloes to the matter power spectrum in the presence of agn feedback, 2023. – 17 –

    2023

  15. [15]

    van Daalen, I

    M.P. van Daalen, I. Koutalios, J.C. Broxterman, B.J.H. Wolfs, J.C. Helly, M. Schaller et al., The resummation model in flamingo: precisely predicting matter power suppression from observed halo baryon fractions, 2025

    2025

  16. [16]

    Zentner, D.H

    A.R. Zentner, D.H. Rudd and W. Hu,Self-calibration of tomographic weak lensing for the physics of baryons to constrain dark energy,Physical Review D77(2008)

    2008

  17. [17]

    Semboloni, H

    E. Semboloni, H. Hoekstra and J. Schaye,Effect of baryonic feedback on two- and three-point shear statistics: prospects for detection and improved modelling,Monthly Notices of the Royal Astronomical Society434(2013) 148–162

    2013

  18. [18]

    A.J. Mead, S. Brieden, T. Tr¨ oster and C. Heymans,¡scp¿hmcode-2020¡/scp¿: improved modelling of non-linear cosmological power spectra with baryonic feedback,Monthly Notices of the Royal Astronomical Society502(2021) 1401–1422

    2020

  19. [19]

    Osato and D

    K. Osato and D. Nagai,Baryon pasting algorithm: halo-based and particle-based pasting methods,Monthly Notices of the Royal Astronomical Society519(2022) 2069–2082

    2022

  20. [20]

    P.R. S., E. Krause, K. Dolag, K. Benabed, T. Eifler, E. Ay¸ coberry et al.,Impact of cosmology dependence of baryonic feedback in weak lensing, 2024

    2024

  21. [21]

    C.-H. To, S. Pandey, E. Krause, N. Dalal, D. Anbajagane and D.H. Weinberg,Deciphering baryonic feedback with galaxy clusters, 2024

    2024

  22. [22]

    Hadzhiyska, S

    B. Hadzhiyska, S. Ferraro, B.R. Guachalla, E. Schaan, J. Aguilar, N. Battaglia et al.,Evidence for large baryonic feedback at low and intermediate redshifts from kinematic sunyaev-zel’dovich observations with act and desi photometric galaxies, 2025

    2025

  23. [23]

    Huang, T

    H.-J. Huang, T. Eifler, R. Mandelbaum, G.M. Bernstein, A. Chen, A. Choi et al.,Dark energy survey year 1 results: Constraining baryonic physics in the universe,Monthly Notices of the Royal Astronomical Society502(2021) 6010–6031

    2021

  24. [24]

    Schneider, S.K

    A. Schneider, S.K. Giri, S. Amodeo and A. Refregier,Constraining baryonic feedback and cosmology with weak-lensing, x-ray, and kinematic sunyaev–zeldovich observations,Monthly Notices of the Royal Astronomical Society514(2022) 3802–3814

    2022

  25. [25]

    Bigwood, A

    L. Bigwood, A. Amon, A. Schneider, J. Salcido, I.G. McCarthy, C. Preston et al.,Weak lensing combined with the kinetic sunyaev zel’dovich effect: A study of baryonic feedback, 2024

    2024

  26. [26]

    J. Xu, T. Eifler, E. Krause, V. Miranda, J. Salcido and I. McCarthy,Constraining baryonic feedback and cosmology from des y3 and planck pr4 6×2pt data. i.λcdm models, 2025

    2025

  27. [27]

    Siegel, A

    J. Siegel, A. Amon, I.G. McCarthy, L. Bigwood, M. Yamamoto, E. Bulbul et al.,Joint x-ray, kinetic sunyaev-zeldovich, and weak lensing measurements: toward a consensus picture of efficient gas expulsion from groups and clusters, 2025

    2025

  28. [28]

    Terasawa, X

    R. Terasawa, X. Li, M. Takada, T. Nishimichi, S. Tanaka, S. Sugiyama et al.,Exploring the baryonic effect signature in the hyper suprime-cam year 3 cosmic shear two-point correlations on small scales: thes 8 tension remains present, 2024

    2024

  29. [29]

    Sarmiento, A

    K.P. Sarmiento, A. Lagu¨ e, M. Madhavacheril, B. Jain and B. Sherwin,Reconstructing the shape of the non-linear matter power spectrum using cmb lensing and cosmic shear, 2025

    2025

  30. [30]

    Le Brun, I.G

    A.M.C. Le Brun, I.G. McCarthy, J. Schaye and T.J. Ponman,Towards a realistic population of simulated galaxy groups and clusters,Monthly Notices of the Royal Astronomical Society441 (2014) 1270–1290

    2014

  31. [31]

    McCarthy, J

    I.G. McCarthy, J. Schaye, S. Bird and A.M.C. Le Brun,The bahamas project: calibrated hydrodynamical simulations for large-scale structure cosmology,Monthly Notices of the Royal Astronomical Society465(2016) 2936–2965

    2016

  32. [32]

    Nelson, V

    D. Nelson, V. Springel, A. Pillepich, V. Rodriguez-Gomez, P. Torrey, S. Genel et al.,The – 18 – IllustrisTNG simulations: public data release,Computational Astrophysics and Cosmology6 (2019) 2 [1812.05609]

    Pith/arXiv arXiv 2019

  33. [33]

    Pillepich, D

    A. Pillepich, D. Nelson, L. Hernquist, V. Springel, R. Pakmor, P. Torrey et al.,First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies, Mon. Not. Roy. Astron. Soc.475(2018) 648 [1707.03406]

    Pith/arXiv arXiv 2018

  34. [34]

    Marinacci, M

    F. Marinacci, M. Vogelsberger, R. Pakmor, P. Torrey, V. Springel, L. Hernquist et al.,First results from the IllustrisTNG simulations: radio haloes and magnetic fields, Mon. Not. Roy. Astron. Soc.480(2018) 5113 [1707.03396]

    Pith/arXiv arXiv 2018

  35. [35]

    Naiman, A

    J.P. Naiman, A. Pillepich, V. Springel, E. Ramirez-Ruiz, P. Torrey, M. Vogelsberger et al., First results from the IllustrisTNG simulations: a tale of two elements - chemical evolution of magnesium and europium,Mon. Not. Roy. Astron. Soc.477(2018) 1206 [1707.03401]

    Pith/arXiv arXiv 2018

  36. [36]

    Springel, R

    V. Springel, R. Pakmor, A. Pillepich, R. Weinberger, D. Nelson, L. Hernquist et al.,First results from the IllustrisTNG simulations: matter and galaxy clustering, Mon. Not. Roy. Astron. Soc.475(2018) 676 [1707.03397]

    Pith/arXiv arXiv 2018

  37. [37]

    Vogelsberger, S

    M. Vogelsberger, S. Genel, V. Springel, P. Torrey, D. Sijacki, D. Xu et al.,Introducing the Illustris Project: simulating the coevolution of dark and visible matter in the Universe, Mon. Not. Roy. Astron. Soc.444(2014) 1518 [1405.2921]

    Pith/arXiv arXiv 2014

  38. [38]

    Genel, M

    S. Genel, M. Vogelsberger, V. Springel, D. Sijacki, D. Nelson, G. Snyder et al.,Introducing the Illustris project: the evolution of galaxy populations across cosmic time, Mon. Not. Roy. Astron. Soc.445(2014) 175 [1405.3749]

    Pith/arXiv arXiv 2014

  39. [39]

    Sijacki, M

    D. Sijacki, M. Vogelsberger, S. Genel, V. Springel, P. Torrey, G.F. Snyder et al.,The Illustris simulation: the evolving population of black holes across cosmic time, Mon. Not. Roy. Astron. Soc.452(2015) 575 [1408.6842]

    Pith/arXiv arXiv 2015

  40. [40]

    Vogelsberger, S

    M. Vogelsberger, S. Genel, V. Springel, P. Torrey, D. Sijacki, D. Xu et al.,Properties of galaxies reproduced by a hydrodynamic simulation,Nature509(2014) 177 [1405.1418]

    Pith/arXiv arXiv 2014

  41. [41]

    Springel,E pur si muove: Galilean-invariant cosmological hydrodynamical simulations on a moving mesh,Mon

    V. Springel,E pur si muove: Galilean-invariant cosmological hydrodynamical simulations on a moving mesh,Mon. Not. Roy. Astron. Soc.401(2010) 791 [0901.4107]

    Pith/arXiv arXiv 2010

  42. [42]

    Weinberger, V

    R. Weinberger, V. Springel and R. Pakmor,The arepo public code release,The Astrophysical Journal Supplement Series248(2020) 32

    2020

  43. [43]

    Springel, S.D.M

    V. Springel, S.D.M. White, G. Tormen and G. Kauffmann,Populating a cluster of galaxies - I. Results at z=0,Mon. Not. Roy. Astron. Soc.328(2001) 726 [astro-ph/0012055]

    Pith/arXiv arXiv 2001

  44. [44]

    Dolag, S

    K. Dolag, S. Borgani, G. Murante and V. Springel,Substructures in hydrodynamical cluster simulations,Mon. Not. Roy. Astron. Soc.399(2009) 497 [0808.3401]

    Pith/arXiv arXiv 2009

  45. [45]

    Nelson, A

    D. Nelson, A. Pillepich, S. Genel, M. Vogelsberger, V. Springel, P. Torrey et al.,The illustris simulation: Public data release,Astronomy and Computing13(2015) 12–37

    2015

  46. [46]

    More, F.C

    S. More, F.C. van den Bosch, M. Cacciato, R. Skibba, H.J. Mo and X. Yang,Satellite kinematics - iii. halo masses of central galaxies in sdss: Satellite kinematics - iii,Monthly Notices of the Royal Astronomical Society410(2010) 210–226

    2010

  47. [47]

    N. Hand, Y. Feng, F. Beutler, Y. Li, C. Modi, U. Seljak et al.,Nbodykit: An open-source, massively parallel toolkit for large-scale structure,The Astronomical Journal156(2018) 160

    2018

  48. [48]

    Jenkins, C.S

    A. Jenkins, C.S. Frenk, F.R. Pearce, P.A. Thomas, J.M. Colberg, S.D.M. White et al., Evolution of structure in cold dark matter universes,The Astrophysical Journal499(1998) 20–40

    1998

  49. [49]

    A. Amon, D. Gruen, M. Troxel, N. MacCrann, S. Dodelson, A. Choi et al.,Dark energy survey year 3 results: Cosmology from cosmic shear and robustness to data calibration,Physical Review D105(2022) . – 19 –

    2022

  50. [50]

    J. Prat, J. Blazek, C. S´ anchez, I. Tutusaus, S. Pandey, J. Elvin-Poole et al.,Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing, Physical Review D105(2022)

    2022

  51. [51]

    Campbell, C.M

    D.J.R. Campbell, C.M. Baugh, P.D. Mitchell, J.C. Helly, V. Gonzalez-Perez, C.G. Lacey et al., A new methodology to test galaxy formation models using the dependence of clustering on stellar mass,Mon. Not. Roy. Astron. Soc.452(2015) 852 [1412.3804]

    Pith/arXiv arXiv 2015

  52. [52]

    Pillepich, V

    A. Pillepich, V. Springel, D. Nelson, S. Genel, J. Naiman, R. Pakmor et al.,Simulating galaxy formation with the illustristng model,Monthly Notices of the Royal Astronomical Society473 (2017) 4077–4106

    2017

  53. [53]

    Weinberger, V

    R. Weinberger, V. Springel, L. Hernquist, A. Pillepich, F. Marinacci, R. Pakmor et al., Simulating galaxy formation with black hole driven thermal and kinetic feedback,Monthly Notices of the Royal Astronomical Society465(2016) 3291–3308

    2016

  54. [54]

    Chisari, M.L.A

    N.E. Chisari, M.L.A. Richardson, J. Devriendt, Y. Dubois, A. Schneider, A.M.C. Le Brun et al.,The impact of baryons on the matter power spectrum from the horizon-agn cosmological hydrodynamical simulation,Monthly Notices of the Royal Astronomical Society480(2018) 3962–3977

    2018

  55. [55]

    Secco, S

    L. Secco, S. Samuroff, E. Krause, B. Jain, J. Blazek, M. Raveri et al.,Dark energy survey year 3 results: Cosmology from cosmic shear and robustness to modeling uncertainty,Physical Review D105(2022)

    2022

  56. [56]

    Aric` o, R.E

    G. Aric` o, R.E. Angulo, M. Zennaro, S. Contreras, A. Chen and C. Hern´ andez-Monteagudo, Des y3 cosmic shear down to small scales: Constraints on cosmology and baryons,Astronomy & Astrophysics678(2023) A109

    2023

  57. [57]

    Schneider, R

    A. Schneider, R. Teyssier, J. Stadel, N.E. Chisari, A.M.L. Brun, A. Amara et al.,Quantifying baryon effects on the matter power spectrum and the weak lensing shear correlation,Journal of Cosmology and Astroparticle Physics2019(2019) 020–020

    2019

  58. [58]

    Lucie-Smith, H.V

    L. Lucie-Smith, H.V. Peiris, A. Pontzen, A. Halder, J. Schaye, M. Schaller et al.,Cosmological feedback from a halo assembly perspective,Physical Review D112(2025)

    2025

  59. [59]

    Hadzhiyska, S

    B. Hadzhiyska, S. Ferraro, R. Pakmor, S. Bose, A.M. Delgado, C. Hern´ andez-Aguayo et al., Interpreting sunyaev-zel’dovich observations with millenniumtng: Mass and environment scaling relations, 2023

    2023

  60. [60]

    Roper, Y.-C

    F.A. Roper, Y.-C. Cai and J.A. Peacock,Mass dependence of halo baryon fractions from the kinetic sunyaev-zeldovich effect, 2025

    2025

  61. [61]

    Z. Lin, N. Huang, C. Avestruz, W.L.K. Wu, S. Trivedi, J. Caldeira et al.,Deepsz: identification of sunyaev–zel’dovich galaxy clusters using deep learning,Monthly Notices of the Royal Astronomical Society507(2021) 4149–4164

    2021

  62. [62]

    Zhang, H

    Z. Zhang, H. Wang, W. Luo, H. Mo, J. Zhang, X. Yang et al.,Halo mass-observable proxy scaling relations and their dependencies on galaxy and group properties, 2023

    2023

  63. [63]

    Collaboration, M

    T.S.O. Collaboration, M. Abitbol, I. Abril-Cabezas, S. Adachi, P. Ade, A.E. Adler et al.,The simons observatory: Science goals and forecasts for the enhanced large aperture telescope, 2025

    2025

  64. [64]

    Nishimichi, M

    T. Nishimichi, M. Takada, R. Takahashi, K. Osato, M. Shirasaki, T. Oogi et al.,Dark quest. i. fast and accurate emulation of halo clustering statistics and its application to galaxy clustering, The Astrophysical Journal884(2019) 29

    2019

  65. [65]

    Aric` o, R.E

    G. Aric` o, R.E. Angulo, S. Contreras, L. Ondaro-Mallea, M. Pellejero-Iba˜ nez and M. Zennaro, The bacco simulation project: a baryonification emulator with neural networks,Monthly Notices of the Royal Astronomical Society506(2021) 4070–4082. – 20 –

    2021

This paper was first reviewed by deepseek-v4-flash on August 3, 2026.