Pith. sign in

REVIEW 2 major objections 5 minor 56 references

A cosmology-dependent halo concentration model keeps the cluster weak-lensing mass bias essentially constant.

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 →

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Cosmology-dependent concentration models remove most cosmology dependence of the cluster weak-lensing mass bias; residual trends track baryon fraction and require explicit baryonic modeling.

T0 review reviewed 2026-07-13 challenge →

load-bearing objection Clean, quantitative scan showing that a cosmology-aware concentration model largely kills the cosmology dependence of cluster WL mass bias; residual is small and the practical recommendation is already usable. the 2 major comments →

arxiv 2603.19898 v3 pith:H7M6MX3C submitted 2026-03-20 astro-ph.CO

On the cosmology dependence of the cluster weak-lensing mass bias

S. Bocquet , A. Fumagalli , C. T. Davies , K. Dolag , S. Grandis , J. J. Mohr This is my paper
classification astro-ph.CO
keywords weak gravitational lensinggalaxy clustersmass biasconcentration-mass relationcosmological parametershydrodynamical simulationsNFW profile
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

Galaxy-cluster cosmology relies on weak-lensing masses to calibrate the link between observed cluster properties and true mass. Those lensing masses are systematically offset from the true halo mass; the size of the offset is called the weak-lensing mass bias. This paper asks whether the bias itself changes when the background cosmology changes. Using more than 100,000 synthetic shear maps drawn from 15 large-volume simulations that span a wide range of matter density, fluctuation amplitude, baryon fraction and Hubble parameter, the authors show that a fixed concentration or a concentration-mass relation that ignores cosmology produces percent-level shifts in the bias. When the concentration is instead taken from a model that already depends on cosmology, those shifts largely disappear and the bias stays nearly constant. Hydrodynamical runs further indicate that the remaining variation is driven by the strength of baryonic feedback, so future models will need to track that as well. The practical message is that current analyses can keep their mass-bias systematics under control simply by adopting a cosmology-aware concentration prescription.

Core claim

Assuming a fixed halo concentration or a fixed concentration-mass relation produces cosmology-dependent changes in the weak-lensing mass bias of up to Δln b_WL = 0.030 across the 15 cosmologies examined. Replacing that prescription with a concentration model that itself depends on cosmology absorbs the profile changes and recovers essentially constant values of the bias (residual intrinsic scatter s_int ≈ 0.0027 in gravity-only runs).

What carries the argument

The weak-lensing mass bias b_WL ≡ M_WL / M_200c, obtained by fitting an NFW profile (with a chosen concentration model) to the reduced tangential shear measured in synthetic maps over the fixed radial window 0.5 < R/(h^{-1} Mpc) < 3.2 (1+z)^{-1}.

Load-bearing premise

The analysis treats the NFW profile plus a chosen concentration-mass relation as an adequate description of the reduced shear over a fixed radial window, and treats the simulation suite's baryonic feedback as representative of real clusters.

What would settle it

Repeat the same shear-map fitting exercise on an independent suite of hydrodynamical simulations that vary both cosmology and feedback strength; if a residual trend of b_WL with cosmology or baryon fraction remains after a cosmology-dependent concentration is used, the claimed near-constancy is false.

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

If this is right

  • Cluster cosmology pipelines that currently adopt a fixed concentration should switch to a cosmology-dependent concentration-mass relation to keep mass-bias systematics sub-percent.
  • The residual variation seen in hydrodynamical runs implies that future bias models must also be parametrized by baryon fraction or feedback strength.
  • Analyses that already employ a cosmology- and baryon-aware concentration relation remain robust across the cosmologies spanned by the simulation suite.
  • The absolute size of the cosmology-induced shifts is small compared with present-day systematic error budgets, so existing cosmological constraints are not strongly biased by this effect.

Where Pith is reading between the lines

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

  • Because the dominant residual is the baryon fraction rather than background cosmology, multi-feedback simulation campaigns will be more decisive for the next generation of mass-bias models than pure cosmology-variation suites.
  • The same near-constancy should appear in other mass-proxy calibrations (X-ray, SZ) once their profile models are likewise made cosmology-aware, providing a cross-check on the lensing result.
  • If local baryon fractions inside r_500 prove more predictive than the universal value, bias models can be further tightened by tying concentration to cluster gas fractions measured in the same data sets.
Share X Bluesky LinkedIn Reddit HN

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

2 major / 5 minor

Summary. The paper measures the cosmology dependence of the cluster weak-lensing mass bias b_WL ≡ M_WL/M_200c using 115920 synthetic reduced-tangential-shear maps of M_200c > 1.56 imes10^14 h^{-1} M_⊙ halos drawn from 15 Magneticum Box1a cosmologies (varying Ω_m, Ω_b, σ_8, H_0). Projected mass maps are converted to shear via Kaiser–Squires, then fit with an NFW profile over the fixed radial window 0.5 < R/(h^{-1} Mpc) < 3.2(1+z)^{-1}. In gravity-only runs a fixed concentration (c=3.5) or a cosmology-independent c–M relation produces a clear trend of ln b_WL with Ω_m and σ_8 (intrinsic scatter s_int ≈ 0.014, Δ ln b_WL up to 0.030 relative to WMAP7). Replacing the concentration model with the cosmology-dependent Diemer & Joyce (2019) relation reduces s_int to ≈ 0.0027 and removes residual trends. Hydrodynamical counterparts show an additional trend driven by the universal baryon fraction; the Magneticum-calibrated Ragagnin et al. (2021) concentration model largely absorbs it. The authors conclude that cosmology-dependent concentration models should be used and that future models must also encode baryonic feedback strength.

Significance. The result is directly useful for Stage-III/IV cluster cosmology: it quantifies a previously under-explored systematic at the few-percent level and shows that a standard, publicly available concentration model already removes most of the cosmology dependence in gravity-only runs. The analysis is large (15 cosmologies, three redshifts, gravity-only + hydro), the pipeline is standard and carefully documented, and the residual scatter is reported with an inverse-variance estimator. The recommendation to adopt cosmology-dependent concentration is actionable and low-cost for ongoing analyses (SPT, eROSITA, DES, Euclid). The hydrodynamical findings correctly flag that baryonic effects remain a separate modeling requirement.

major comments (2)
  1. Sect. 5.2 and Fig. 10: the Ragagnin et al. (2021) concentration model was calibrated on the same Magneticum suite used here. The dramatic reduction of s_int from 0.015 to 0.0030 is therefore partly a self-consistency test rather than an independent validation. The paper already notes this limitation, but the claim that the model “absorbs essentially all of the evolution” should be qualified more explicitly as internal to Magneticum; a short statement of how the residual would be expected to change under a different feedback prescription (or a pointer to FLAMINGO-style tests) would strengthen the hydrodynamical conclusions.
  2. Sect. 4.1: the projection depth is fixed at l_proj = 20 h^{-1} Mpc. While this choice is conventional for isolating the 1-halo term, the paper does not quantify residual large-scale structure contributions that vary with cosmology (growth rate, Ω_m). A brief robustness check—e.g., repeating a subset of cosmologies at l_proj = 10 and 40 h^{-1} Mpc—would confirm that the reported Δ ln b_WL is not contaminated by cosmology-dependent projection noise.
minor comments (5)
  1. Eq. (12): the definition of the intrinsic standard deviation s_int is written with nested square-root and summation symbols that are hard to parse; a clearer multi-line expression or an explicit statement that it is the inverse-variance weighted rms residual would help.
  2. Fig. 1 and Table 1: the Latin-hypercube sampling leaves Ω_m and f_b strongly correlated. A short remark in Sect. 3 that this degeneracy is intentional (to keep Ω_b h^{2} roughly fixed) would prevent readers from misinterpreting the hydrodynamical trend as pure Ω_m dependence.
  3. Sect. 4.3: the radial window is motivated by Grandis et al. (2021) but is written with mixed units (h^{-1} Mpc and a redshift factor). Stating the corresponding angular range for a typical source redshift would aid reproducibility.
  4. Throughout: the notation switches between M_halo, M_200c and M_WL; a single consistent symbol for the true spherical-overdensity mass would reduce ambiguity.
  5. References: a few recent cluster-lensing mass-calibration papers (e.g., the latest DES-Y3 and eROSITA analyses) are cited, but an explicit pointer to the concentration models used in those works would help readers map the present recommendation onto existing pipelines.

Circularity Check

1 steps flagged

No significant circularity: mass bias is measured from synthetic shear maps; mild self-consistency only when Ragagnin+21 (same Magneticum suite) is used on hydro runs.

specific steps
  1. self citation load bearing [Sect. 5.2, Fig. 10 and surrounding text]
    "Therefore, we now consider a concentration–mass relation that is calibrated on the same suite of Magneticum simulations we also use (Ragagnin et al. 2021). ... Using this model, we fit for the lensing mass bias and obtain an intrinsic standard deviation s_Ragagnin+21_int = 0.0030 that is about five times smaller than for the Diemer & Joyce (2019) model. ... We note that because Ragagnin et al. (2021) calibrated their model using the same hydrodynamical simulations as we do, there is no guarantee that the residuals would be similarly small when using other hydrodynamical simulations..."

    Ragagnin+21 was fitted to the identical Magneticum hydro suite; applying it back to the same suite necessarily absorbs the baryon-fraction trend that the paper itself attributes to those simulations. The reduction of s_int is therefore partly by construction for the hydro runs. The authors acknowledge the limitation, and the primary gravity-only result (Diemer & Joyce 2019) is independent, so the circularity is secondary and non-load-bearing.

full rationale

The paper's central claim is an empirical measurement, not a derivation that reduces to its inputs. Synthetic reduced-tangential-shear profiles are generated from projected mass maps of 115920 cluster projections across 15 Magneticum cosmologies (Sects. 4.1–4.2); M_WL is obtained by minimizing chi^2 against an NFW model over a fixed radial window (Eqs. 9–10, Sect. 4.3); b_WL = M_WL / M_200c is then compared across cosmologies. When concentration is held fixed (c=3.5) or taken from a cosmology-independent relation (Duffy+08), s_int ~ 0.014–0.015; when the independent Diemer & Joyce (2019) cosmology-dependent c–M relation is adopted, s_int falls to ~0.0027 with no residual trend (Sect. 5.1, Figs. 7–8). That comparison is external and falsifiable. The only mild self-consistency loop appears in the hydrodynamical section: Ragagnin et al. (2021) was calibrated on the same Magneticum suite and therefore absorbs the baryon-fraction trend by construction (Sect. 5.2, Fig. 10). The authors themselves flag this limitation and treat the Ragagnin result as secondary; the primary gravity-only claim does not rely on it. No self-definitional identity, fitted-input-as-prediction, uniqueness theorem, or ansatz-smuggling is present. Score 1 reflects only that secondary, non-load-bearing self-consistency.

Axiom & Free-Parameter Ledger

2 free parameters · 4 axioms · 0 invented entities

The central claim rests on standard N-body/hydro simulation assumptions, the NFW functional form, literature concentration models, and the Magneticum feedback implementation. No new free parameters are fitted to the lensing data themselves; the bias is measured, not adjusted. The only ad-hoc modeling choices are the fixed radial fitting window and the projection depth, both inherited from earlier calibration papers.

free parameters (2)
  • radial fitting window = 0.5–3.2 h^{-1} Mpc (scaled)
    Fixed to 0.5 < R/(h^{-1} Mpc) < 3.2(1+z)^{-1} following Grandis et al. (2021); choice affects which parts of the profile enter the mass fit.
  • projection depth l_proj = 20 h^{-1} Mpc
    Set to 20 h^{-1} Mpc by hand; controls the amount of correlated large-scale structure included in each map.
axioms (4)
  • domain assumption Halo density profiles are adequately described by the NFW functional form for the purpose of reduced-shear fitting.
    Invoked throughout Sect. 2 and 4.3; the entire mass-bias measurement is defined relative to this parametric model.
  • domain assumption The Diemer & Joyce (2019) and Ragagnin et al. (2021) concentration–mass–cosmology relations correctly capture the mean concentration of Magneticum halos.
    Used in Sect. 5.1–5.2 to absorb cosmology dependence; if the relations are biased, residual trends would remain.
  • domain assumption Magneticum baryonic feedback (cooling, star formation, SN and AGN feedback) produces a representative alteration of cluster mass profiles.
    Hydro results in Sect. 5.2–5.3 rest on this; different feedback strengths could change the baryon-fraction trend.
  • standard math Friends-of-friends + SUBFIND spherical-overdensity masses define the true halo mass M_200c.
    Standard halo-finding procedure stated in Sect. 3; used as the denominator of b_WL.

reviewed 2026-07-13 · how reviews work

0 comments
Cite this review

Pith. "Pith review of On the cosmology dependence of the cluster weak-lensing mass bias." pith.science (2026). https://pith.science/paper/H7M6MX3C

@misc{pith2026260319898,
  author       = {Pith},
  title        = {Pith review of: On the cosmology dependence of the cluster weak-lensing mass bias},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/H7M6MX3C}},
  note         = {Machine review of arXiv:2603.19898}
}
Share X Bluesky LinkedIn Reddit HN
abstract

Measurements of the shear induced by weak gravitational lensing around galaxy cluster lines of sight are the gold standard for calibrating cluster observable-mass relations, thereby enabling a robust and precise inference of cosmological parameters. The weak-lensing mass bias is the systematic offset between the true halo mass and the mass that is inferred from the lensing data using an imperfect model for the halo mass distribution. We study the impact of cosmology on the lensing mass bias to inform future cosmological analyses of galaxy clusters. We create synthetic lensing shear maps for 115,920 projections of clusters with $M_{200\mathrm c}>1.56\times10^{14}\,h^{-1}M_\odot$ in a suite of Magneticum simulations. The simulation boxes are $896\,h^{-1}$Mpc on a side and are set up with 15 different combinations of the cosmological parameters $\Omega_\mathrm{m}$, $\Omega_\mathrm{b}$, $\sigma_8$, and $H_0$. Assuming a Navarro-Frenk-White profile, we extract weak-lensing mass measurements and quantify their bias $b_\mathrm{WL}$ with respect to the true halo mass. To investigate the impact of baryonic effects, we perform the analysis on gravity-only simulations and on their full-physics hydrodynamical counterparts. We confirm that assuming a fixed halo concentration or a fixed concentration-mass relation leads to cosmology-dependent changes of the mass bias. We report changes of up to $\Delta\ln b_\mathrm{WL}=0.030$ with respect to the bias obtained at the fiducial WMAP7 cosmology. Adopting a model for the concentration that also depends on cosmology absorbs the changes in halo profiles and we recover essentially constant values for the mass bias. Our analysis of hydrodynamical simulations suggests that future, more accurate models will also need to explicitly account for the strength of baryonic effects.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

56 extracted references · 1 linked inside Pith

  1. [1]

    W., Evrard, A

    Allen, S. W., Evrard, A. E., & Mantz, A. B. 2011, ARA&A, 49, 409

    2011

  2. [2]

    E., von der Linden, A., Kelly, P

    Applegate, D. E., von der Linden, A., Kelly, P. L., et al. 2014, MNRAS, 439, 48 Article number, page 8 of 9

    2014

  3. [3]

    2025, arXiv:2509.02068 Bahé, Y

    Aymerich, G., Grandis, S., Douspis, M., et al. 2025, arXiv:2509.02068 Bahé, Y . M., McCarthy, I. G., & King, L. J. 2012, MNRAS, 421, 1073

    Pith/arXiv arXiv 2025

  4. [4]

    & Schneider, P

    Bartelmann, M. & Schneider, P. 2001, Phys. Rep., 340, 291

    2001

  5. [5]

    M., Murante, G., Arth, A., et al

    Beck, A. M., Murante, G., Arth, A., et al. 2016, MNRAS, 455, 2110

    2016

  6. [6]

    Becker, M. R. & Kravtsov, A. V . 2011, ApJ, 740, 25

    2011

  7. [7]

    2019, MNRAS, 484, 1598

    Bellagamba, F., Sereno, M., Roncarelli, M., et al. 2019, MNRAS, 484, 1598

    2019

  8. [8]

    P., Schrabback, T., et al

    Bocquet, S., Dietrich, J. P., Schrabback, T., et al. 2019, ApJ, 878, 55

    2019

  9. [9]

    2021, MNRAS, 500, 2316

    Castro, T., Borgani, S., Dolag, K., et al. 2021, MNRAS, 500, 2316

    2021

  10. [10]

    2020, ApJ, 891, 139

    Chen, K.-F., Oguri, M., Lin, Y .-T., & Miyazaki, S. 2020, ApJ, 891, 139

    2020

  11. [11]

    L., Habib, S., Heitmann, K., et al

    Child, H. L., Habib, S., Heitmann, K., et al. 2018, ApJ, 859, 55

    2018

  12. [12]

    2025, A&A, 704, A110

    Chiu, I.-N., Ghirardini, V ., Grandis, S., et al. 2025, A&A, 704, A110

    2025

  13. [13]

    N., Klein, M., Mohr, J., & Bocquet, S

    Chiu, I. N., Klein, M., Mohr, J., & Bocquet, S. 2023, MNRAS, 522, 1601

    2023

  14. [14]

    2019, MNRAS, 488, 4779 DES Collaboration

    Costanzi, M., Rozo, E., Simet, M., et al. 2019, MNRAS, 488, 4779 DES Collaboration. 2022, Phys. Rev. D, 105, 023520

    2019

  15. [15]

    & Joyce, M

    Diemer, B. & Joyce, M. 2019, ApJ, 871, 168

    2019

  16. [16]

    P., Bocquet, S., Schrabback, T., et al

    Dietrich, J. P., Bocquet, S., Schrabback, T., et al. 2019, MNRAS, 483, 2871

    2019

  17. [17]

    2009, MNRAS, 399, 497

    Dolag, K., Borgani, S., Murante, G., & Springel, V . 2009, MNRAS, 399, 497

    2009

  18. [18]

    2016, MNRAS, 463, 1797

    Dolag, K., Komatsu, E., & Sunyaev, R. 2016, MNRAS, 463, 1797

    2016

  19. [19]

    2017, Galaxies, 5, 35

    Dolag, K., Mevius, E., & Remus, R.-S. 2017, Galaxies, 5, 35

    2017

  20. [20]

    M., et al

    Dolag, K., Remus, R.-S., Valenzuela, L. M., et al. 2025, arXiv e-prints, arXiv:2504.01061

    arXiv 2025

  21. [21]

    R., Schaye, J., Kay, S

    Duffy, A. R., Schaye, J., Kay, S. T., & Dalla Vecchia, C. 2008, MNRAS, 390, L64 Euclid Collaboration: Giocoli, C., Meneghetti, M., Rasia, E., et al. 2024, A&A, 681, A67 Euclid Collaboration: Mellier, Y ., Abdurro’uf, Acevedo Barroso, J. A., et al. 2025, A&A, 697, A1

    2008

  22. [22]

    2024, A&A, 682, A148

    Fumagalli, A., Costanzi, M., Saro, A., Castro, T., & Borgani, S. 2024, A&A, 682, A148

    2024

  23. [23]

    2024, A&A, 689, A298

    Ghirardini, V ., Bulbul, E., Artis, E., et al. 2024, A&A, 689, A298

    2024

  24. [24]

    J., Klein, M., & Dolag, K

    Grandis, S., Bocquet, S., Mohr, J. J., Klein, M., & Dolag, K. 2021, MNRAS, 507, 5671

    2021

  25. [25]

    2024, A&A, 687, A178

    Grandis, S., Ghirardini, V ., Bocquet, S., et al. 2024, A&A, 687, A178

    2024

  26. [26]

    J., & Holder, G

    Haiman, Z., Mohr, J. J., & Holder, G. P. 2001, ApJ, 553, 545

    2001

  27. [27]

    2014, MNRAS, 442, 2304

    Hirschmann, M., Dolag, K., Saro, A., et al. 2014, MNRAS, 442, 2304

    2014

  28. [28]

    2013, Space Sci

    Hoekstra, H., Bartelmann, M., Dahle, H., et al. 2013, Space Sci. Rev., 177, 75 Ivezi´c, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111

    2013

  29. [29]

    E., Sheldon, E

    Johnston, D. E., Sheldon, E. S., Wechsler, R. H., et al. 2007, arXiv:07091159

    2007

  30. [30]

    & Squires, G

    Kaiser, N. & Squires, G. 1993, ApJ, 404, 441

    1993

  31. [31]

    Kravtsov, A. V . & Borgani, S. 2012, ARA&A, 50, 353

    2012

  32. [32]

    F., Marulli, F., Moscardini, L., et al

    Lesci, G. F., Marulli, F., Moscardini, L., et al. 2025, arXiv:250714285

    2025

  33. [33]

    B., von der Linden, A., Allen, S

    Mantz, A. B., von der Linden, A., Allen, S. W., et al. 2015, MNRAS, 446, 2205

    2015

  34. [34]

    J., et al

    Mazoun, A., Bocquet, S., Mohr, J. J., et al. 2025, Phys. Rev. D, 111, 083543

    2025

  35. [35]

    N., Gruen, D., et al

    McClintock, T., Varga, T. N., Gruen, D., et al. 2019, MNRAS, 482, 1352

    2019

  36. [36]

    2017, MNRAS, 469, 4899

    Melchior, P., Gruen, D., McClintock, T., et al. 2017, MNRAS, 469, 4899

    2017

  37. [37]

    2019, ApJ, 875, 63

    Miyatake, H., Battaglia, N., Hilton, M., et al. 2019, ApJ, 875, 63

    2019

  38. [38]

    2019, MNRAS, 488, 1728

    Nagarajan, A., Pacaud, F., Sommer, M., et al. 2019, MNRAS, 488, 1728

    2019

  39. [39]

    F., Frenk, C

    Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, ApJ, 462, 563

    1996

  40. [40]

    & Hamana, T

    Oguri, M. & Hamana, T. 2011, MNRAS, 414, 1851 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A24

    2011

  41. [41]

    W., Arnaud, M., Biviano, A., et al

    Pratt, G. W., Arnaud, M., Biviano, A., et al. 2019, Space Sci. Rev., 215, 25

    2019

  42. [42]

    2021, A&A, 647, A1

    Predehl, P., Andritschke, R., Arefiev, V ., et al. 2021, A&A, 647, A1

    2021

  43. [43]

    2021, MNRAS, 500, 5056

    Ragagnin, A., Saro, A., Singh, P., & Dolag, K. 2021, MNRAS, 500, 5056

    2021

  44. [44]

    N., Rozo, E., Wu, H.-Y ., et al

    Salcedo, A. N., Rozo, E., Wu, H.-Y ., et al. 2025, arXiv:2510.25706

    arXiv 2025

  45. [45]

    2022, ApJ, 934, 129

    Salvati, L., Saro, A., Bocquet, S., et al. 2022, ApJ, 934, 129

    2022

  46. [46]

    R., Hilton, M., et al

    Sarieddine, L., Bond, J. R., Hilton, M., et al. 2026, arXiv e-prints, arXiv:2602.03917

    arXiv 2026

  47. [47]

    2023, MNRAS, 526, 4978

    Schaye, J., Kugel, R., Schaller, M., et al. 2023, MNRAS, 526, 4978

    2023

  48. [48]

    P., et al

    Schrabback, T., Applegate, D., Dietrich, J. P., et al. 2018, MNRAS, 474, 2635

    2018

  49. [49]

    J., Lee, E., et al

    Shin, T., Baxter, E. J., Lee, E., et al. 2025, arXiv e-prints, arXiv:2512.18935

    arXiv 2025

  50. [50]

    2020, MNRAS, 494, 3728 SO Collaboration

    Singh, P., Saro, A., Costanzi, M., & Dolag, K. 2020, MNRAS, 494, 3728 SO Collaboration. 2019, J. Cosmology Astropart. Phys., 2019, 056

    2020

  51. [51]

    A., Anderson, A

    Sobrin, J. A., Anderson, A. J., Bender, A. N., et al. 2022, ApJS, 258, 42

    2022

  52. [52]

    2005, MNRAS, 364, 1105

    Springel, V . 2005, MNRAS, 364, 1105

    2005

  53. [53]

    Springel, V ., White, S. D. M., Jenkins, A., et al. 2005, Nature, 435, 629

    2005

  54. [54]

    Springel, V ., White, S. D. M., Tormen, G., & Kauffmann, G. 2001, MNRAS, 328, 726

    2001

  55. [55]

    F., Remus, R.-S., Dolag, K., et al

    Teklu, A. F., Remus, R.-S., Dolag, K., et al. 2015, ApJ, 812, 29 van Daalen, M. P., McCarthy, I. G., & Schaye, J. 2020, MNRAS, 491, 2424 V ogt, S. M. L., Bocquet, S., Davies, C. T., et al. 2025, Phys. Rev. D, 111, 043519 von der Linden, A., Allen, M. T., Applegate, D. E., et al. 2014a, MNRAS, 439, 2 von der Linden, A., Mantz, A., Allen, S. W., et al. 2014...

    2015

  56. [56]

    2022, A&A, 668, A18 Article number, page 9 of 9

    Zohren, H., Schrabback, T., Bocquet, S., et al. 2022, A&A, 668, A18 Article number, page 9 of 9

    2022

This paper was first reviewed by grok-4.5 on July 13, 2026.