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The thermal Sunyaev-Zeldovich power spectrum of Coma places the cluster's effective viscosity below 5% of the standard Coulomb value.

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Constrained Coma cluster simulations predict that the thermal SZ signal is sensitive to ICM viscosity, and comparison with Planck suggests effective viscosity below 5% of the Spitzer value.

T0 review reviewed 2026-08-01 challenge →

load-bearing objection Promising proof-of-concept for tSZ-based viscosity constraints, but the headline <5% Spitzer value is not supported as presented because the power-spectrum comparison likely ignores beam convolution and the paper's own radial-profile analysis points the other way. the 3 major comments →

arxiv 2607.19753 v1 pith:QVEUWNTK submitted 2026-07-22 astro-ph.CO

Constraining Effective Viscosity in the Intracluster Medium via the Thermal Sunyaev-Zeldovich Effect -- Predictions from the SLOW Constrained Coma Cluster Simulations

Frederick Groth , Yuan Li , Joseph Golec , Benjamin A. Seidel , Jenny G. Sorce , Tirso Marin-Gilabert , Klaus Dolag This is my paper
classification astro-ph.CO
keywords intracluster mediumeffective viscositythermal Sunyaev-Zeldovich effectComa clustertSZ power spectrumconstrained cosmological simulationsgalaxy cluster pressure profileskinetic Sunyaev-Zeldovich
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 aims to establish the thermal Sunyaev-Zeldovich (tSZ) effect—the distortion of the cosmic microwave background by hot electrons in galaxy clusters—as an independent probe of viscosity in the intracluster medium. Using a constrained hydrodynamical simulation of the Coma cluster run at five viscosity levels from zero to the full Coulomb-collision value, it finds a consistent signature: viscosity raises the central Compton-y signal, suppresses it in the outskirts, and elevates the amplitude of the one-halo tSZ power spectrum across scales. Comparing mock maps with existing microwave observations, the paper argues that Coma's effective viscosity is below 5% of the Coulomb value, in line with earlier X-ray-based bounds. If correct, this gives observers a new, independent way to measure how magnetic fields and plasma instabilities damp transport in cluster gas, before higher-resolution instruments sharpen the test.

Core claim

The central discovery is a systematic, monotone mapping from viscosity to tSZ observables. In the simulated Coma analog, raising viscosity from zero to full Coulomb levels leaves the gas temperature nearly unchanged but concentrates the gas density—roughly an order of magnitude more central density—so the Compton-y profile grows in the center and falls in the outskirts, and the tSZ power spectrum rises on all scales without changing its slope. The break scale between bulk and turbulent motions moves to smaller scales with viscosity. Because the effect channels through density rather than temperature, the paper argues it is distinguishable from cooling and feedback, which mainly alter tempera

What carries the argument

The load-bearing object is the one-halo thermal Sunyaev-Zeldovich power spectrum of a single cluster, computed from mock Compton-y maps that match the observed field of view and pixel scale. The mechanism is that viscosity suppresses turbulent mixing: infalling substructure sinks deeper, raising central density and thus central y, while reducing y in the outskirts and shifting the turbulence break scale. On top of that, the paper uses unsharp-masked maps and topological shape statistics—coherence length and isoperimetric ratio—to show that shock structures at roughly 100 kpc scales are larger and more coherent at high viscosity, though not yet observable with current instruments.

Load-bearing premise

The whole constraint rests on the simulation with no cooling and no AGN feedback being a faithful stand-in for the real Coma cluster; if feedback or cooling reshapes the central one-halo pressure fluctuations, the inferred 5% bound can shift.

What would settle it

Take a high-resolution (≲1 arcmin, roughly 100 kpc) tSZ map of Coma's center and outskirts and compare the one-halo power-spectrum amplitude and break scale with the five simulation runs: if the data track the 0.3-times-Coulomb or full-Coulomb curve rather than the 0.05 run, the central claim fails. On the mechanism, an X-ray measurement of the central gas density profile that does not show the order-of-magnitude density enhancement predicted between zero and full viscosity would weaken the density-based explanation.

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

If this is right

  • The tSZ power spectrum becomes a practical viscosity test: a single cluster's pressure fluctuations, not just its mean profile, can discriminate viscosity levels.
  • The viscosity bound agrees with prior X-ray constraints, so an independent one-cluster measurement corroborates that the intracluster medium is far less viscous than Coulomb expectations.
  • Future high-resolution millimeter observations that resolve roughly 100 kpc scales could detect the predicted shock-coherence differences, turning unsharp-masked tSZ maps into a small-scale viscosity diagnostic.
  • Combining tSZ (pressure-sensitive) with X-ray (density- and temperature-sensitive) observations can help separate viscosity from cooling and feedback, because viscosity acts primarily on density in these runs.
  • The kinetic SZ signal shows weaker, merger-timing-dependent trends and is unlikely to constrain viscosity with current data.

Where Pith is reading between the lines

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

  • A natural extension the authors leave implicit: apply the same mock-map and power-spectrum pipeline to other nearby clusters with existing tSZ maps; if the low-viscosity preference persists across a stack, a single-cluster coincidence becomes a population constraint.
  • Because the mechanism is density-mediated, the paper's picture predicts a specific X-ray surface-brightness fluctuation amplitude for the same simulation suite; an X-ray measurement of Coma's central density contrast at 100-kpc scales could test the mechanism without waiting for high-resolution SZ data.
  • If viscosity is truly below 5% of the Coulomb value, unresolved plasma micro-instabilities or magnetic fields are the likely suppressors; that would also imply weak turbulent pressure support, so hydrostatic masses in Coma should not need a large turbulence correction.
  • The paper's own caveat about mass and distance rescaling suggests the bound is not airtight; anchoring the simulation's mass to a lensing-based measurement of Coma rather than its virial estimate would sharpen or shift the quoted 5% limit.
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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

3 major / 5 minor

Summary. The paper uses constrained zoom-in simulations of a Coma cluster analog with controlled values of physical viscosity (0, 0.05, 0.125, 0.3, and 1.0 times the Spitzer value) to predict thermal and kinetic Sunyaev-Zeldovich signals. The authors compare mock tSZ maps with Planck observations using radial profiles, power spectra, unsharp-masked maps, and Minkowski-function-based shape statistics. They report consistent trends — higher viscosity increases central tSZ signal, suppresses outskirts, and raises the tSZ power spectrum amplitude — and claim that comparison of the power spectrum with Planck data favors an effective viscosity below 5% of the Spitzer value. The paper frames tSZ as an independent probe of ICM viscosity.

Significance. If the quantitative claim survives closer scrutiny, this would be a valuable new route to constraining ICM viscosity: the simulated trends are physically well motivated, the viscosity levels are inputs rather than fitted parameters, and the use of a constrained Coma analog enables a cluster-to-cluster comparison. The paper also demonstrates several diagnostics (profiles, power spectra, unsharp masking, Minkowski functionals) that could be useful for future high-resolution SZ observations. The main significance, however, currently rests on a single visual comparison between the simulated and observed tSZ power spectra, and that comparison lacks an explicit treatment of the Planck beam and of statistical uncertainties.

major comments (3)
  1. [Sec. 3, Fig. 4] The headline constraint η≲0.05η_Spitzer is derived by comparing the power spectrum of mock maps with the observed Planck tSZ map, but the text never states that the mock maps are convolved with the Planck beam, nor that the observed spectrum is deconvolved. The constraint range, 3×10^-3<k<2×10^-2 kpc^-1, extends up to the Planck resolution limit k≈0.02 kpc^-1. For a Gaussian beam with FWHM≈300 kpc, the spherical-average suppression of P(k) is exp(-k^2σ^2), which varies from ≈0.86 at k=3×10^-3 to ≈0.002 at k=2×10^-2. This scale-dependent suppression of the observed amplitude mimics low viscosity and could explain the discrepancy with the radial-profile result in the same section, where the authors state that Planck agrees best with η_Spitzer>η>0.3η_Spitzer. Please forward-convolve the simulated maps with the Planck window function (or deconvolve the observed spectrum) and restrict the com
  2. [Sec. 3, Fig. 4] The power-spectrum constraint is presented as a visual match: the observed spectrum 'agrees best with strongly suppressed viscosity'. No noise realizations, error bars, or goodness-of-fit statistic are included, so the uncertainty on the inferred viscosity cannot be assessed. This is particularly important because the radial-profile comparison in Fig. 2 prefers higher viscosity (η>0.3η_Spitzer), meaning the two diagnostics are in apparent tension. A quantitative likelihood or chi-square over the one-halo range, including Planck noise and beam uncertainties, is needed to determine whether the claimed <5% constraint is statistically significant and to propagate the cluster-mass/distance rescaling uncertainty mentioned in the text.
  3. [Sec. 2.2 and Sec. 4] The one-halo power spectrum is the basis of the central claim, yet the simulations exclude cooling and AGN feedback. The paper itself concedes in Sec. 4 that feedback 'can potentially alter the central power spectrum' and that 'some degeneracy of the effect of viscosity with feedback strength is expected'. Because the central power spectrum is exactly the region used for the constraint, a qualitative expectation is insufficient; the authors should provide a quantitative robustness test, for example a simulation with feedback/cooling or an analytic model of how feedback reshapes the pressure profile and propagates into the <5% bound.
minor comments (5)
  1. [Abstract] Typo: 'and and' appears in the Methods sentence. Also, the spelling of 'Sunyaev-Zel'dovich' vs 'Sunyaev-Zeldovich' should be made consistent throughout.
  2. [Sec. 3, histogram paragraph] The inequality 'r<0.2R vir <r' is garbled; it should read '0.2R_vir < r < R_vir'.
  3. [Sec. 3, unsharp masking] Typo: 'substracted' should be 'subtracted'. Please also define the filtered quantity δY/Y explicitly rather than only in words.
  4. [Fig. 4] The y-axis label 'P[(map units kpc)^2]' is unclear. Specify the exact units, e.g., y^2 kpc^2 or dimensionless y^2 with an explicit conversion to physical kpc.
  5. [Sec. 3, Minkowski functionals] The text refers to 'Minkowski functional' in the singular but discusses the isoperimetric ratio and coherence length, which are derived from multiple functionals. Clarify which functionals are computed and how the degradation factor of 16 is chosen.

Circularity Check

0 steps flagged

No circularity: viscosity is a simulation input, Planck data are external, and the viscosity constraint is produced by model comparison, not by construction.

full rationale

The derivation chain is not circular. The five viscosity levels (η=0, 0.05, 0.125, 0.3, 1.0 η_Spitzer) are inputs to the OpenGadget3 simulations (Sec. 2.2), not outputs fitted to the SZ maps. The comparison targets are externally published Planck data (Planck Collaboration et al. 2013; Churazov et al. 2021), so the statement that the observed tSZ power spectrum 'agrees best with strongly suppressed viscosity η≲0.05η_Spitzer' (Sec. 3, Fig. 4) is an inference from an external benchmark, not a re-labeling of a fitted parameter. Self-citations to SLOW/LOWER DECKS initial conditions, the smac map-maker, and prior viscosity implementations supply tools and initial conditions; none of these citations define the target tSZ signal in terms of the viscosity value, and the central claim does not collapse into any of them. The paper itself flags the relevant caveats — Planck beam resolution dominating k>0.02 kpc^-1 and the expected degeneracy with feedback (Secs. 3-4) — but those are validity limitations, not circular reductions. The skeptic's beam-convolution concern is a systematic-error/correctness question: even if valid it would mean the constraint is miscalibrated, not that the inference is equivalent to its inputs by construction. No equation in the paper equates the inferred viscosity to the y-map statistics by definition.

Axiom & Free-Parameter Ledger

4 free parameters · 5 axioms · 0 invented entities

No parameters were fitted to the Planck data. The analysis varies viscosity levels as inputs and compares a posteriori; the only hand-tuned analysis parameters are the unsharp-masking scale and resolution degradation. The main unstated premises are the fidelity of the constrained realization and the unimportance of cooling/feedback.

free parameters (4)
  • viscosity level η/η_Spitzer = 0, 0.05, 0.125, 0.3, 1.0
    Inputs to the simulation suite, chosen by hand to bracket possible ICM viscosity; not fitted to the SZ data.
  • unsharp-masking smoothing scale σ = 100 kpc
    Chosen because it 'yields the clearest differences between the maps' (Sec. 3), a post hoc analysis choice.
  • Minkowski functional resolution degradation factor = 16
    Chosen to avoid strong fragmentation of structures (Sec. 3, Fig. 6).
  • radial exclusion radius = 0.2 R_vir
    Excluded central resolution-limited region from tSZ/kSZ histograms; analysis choice.
axioms (5)
  • domain assumption SLOW/LOWER DECKS constrained initial conditions faithfully reproduce the real Coma cluster's structure and environment.
    Sec. 2.1 invokes prior validation ('These simulations have been shown to very well reproduce the structure of local galaxy clusters') to justify a one-to-one cluster-to-cluster comparison with Planck.
  • domain assumption MFM solver introduces negligible numerical viscosity, so the physical viscosity parameter is the only relevant viscosity.
    Sec. 2.2 states MFM has 'very low numerical viscosity' and 'no artificial viscosity is required'; if numerical viscosity were significant, the physical-viscosity trends could be artifacts.
  • domain assumption Cooling and AGN feedback are unimportant for Coma's tSZ signal.
    Sec. 2.2: 'we expect these not to be important in the Coma cluster'; Sec. 4 concedes 'some degeneracy of the effect of viscosity with feedback strength is expected.'
  • domain assumption The Planck y-map and its zero-level offset y_off = -6.3e-7 are reliable at the angular scales used.
    Sec. 3 uses the Planck Collaboration (2013) map and the offset suggested there; if the zero-level or background subtraction is wrong, the profile and power-spectrum comparisons shift.
  • domain assumption Gnomonic projection distortions do not affect the viscosity ranking.
    Sec. 3 acknowledges deformations of 'a few percent' but argues they affect simulations and observations equally; this is plausible but unquantified for the power-spectrum comparison.

reviewed 2026-08-01 · how reviews work

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Cite this review

Pith. "Pith review of Constraining Effective Viscosity in the Intracluster Medium via the Thermal Sunyaev-Zeldovich Effect -- Predictions from the SLOW Constrained Coma Cluster Simulations." pith.science (2026). https://pith.science/paper/QVEUWNTK

@misc{pith2026260719753,
  author       = {Pith},
  title        = {Pith review of: Constraining Effective Viscosity in the Intracluster Medium via the Thermal Sunyaev-Zeldovich Effect -- Predictions from the SLOW Constrained Coma Cluster Simulations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/QVEUWNTK}},
  note         = {Machine review of arXiv:2607.19753}
}
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abstract

We study the effect of viscosity on the Sunyaev-Zeldovich signal in a simulated constrained Coma cluster analog. We aim to provide alternative constraints on the amount of viscosity in the ICM. We use the Coma cluster realization with different levels of viscosity from the LOWER DECKS zoom-ins of the SLOW constrained simulations. We generate mock thermal and kinetic Sunyaev-Zeldovich maps and and analyze their statistics. We compare them to Planck observations. Viscosity shows a consistent trend in thermal SZ (tSZ) profiles, increasing the signal in the center and suppressing it in the outskirts. Viscosity also has a strong effect on the tSZ power spectrum, elevating its amplitude on all scales. Comparisons with Planck observations suggest that the effective ICM viscosity is below $5\%$ of the Spitzer value. Unsharp masking reveals an effect on small scales, which are, however, not yet detectable with current observational data. The thermal Sunyaev-Zeldovich effect shows clear and consistent trends that allow us to probe the effective viscosity of the ICM. Our analysis suggests suppressed ICM viscosity below $5\%$ of the Spitzer value, consistent with previous X-ray analysis. Our results validate the strength of the SZ effect as an independent method to constrain ICM viscosity.

Figures

Figures reproduced from arXiv: 2607.19753 by Benjamin A. Seidel, Frederick Groth, Jenny G. Sorce, Joseph Golec, Klaus Dolag, Tirso Marin-Gilabert, Yuan Li.

Figure 1
Figure 1. Figure 1: Top: Mock-observation tSZ Y maps with different amounts of viscosity compared to Planck Collaboration et al. (2013); Churazov et al. (2021) observations of the Coma cluster. Bottom: Mock kSZ w maps for the same simulations. The circle indicates Rvir, based on subfind (Springel et al. 2001; Dolag et al. 2009) for simulated clusters, and the observed value by Malavasi et al. (2020) for the Planck Collaborati… view at source ↗
Figure 3
Figure 3. Figure 3: We focus on the central halo, excluding adjacent substruc [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗
Figure 2
Figure 2. Figure 2: Radial tSZ Y (left) and kSZ w (right) profiles. Different colors denote simulations with different amounts of physical viscosity in units of the Spitzer viscosity; the shaded area indicates the 1σ uncertainty range. Black diamonds show published profiles by Planck Collaboration et al. (2013). The horizontal line indicates the background level −yoff, the vertical lines (from left to right): the HEALPix pixe… view at source ↗
Figure 3
Figure 3. Figure 3: Histograms of the tSZ (left) / kSZ (right) values from the (mock) SZ maps within 0.2Rvir < r < Rvir. The vertical line for the tSZ his￾togram denotes the background level −yoff, the one for kSZ the zero￾value. Same colors as in [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Power spectrum calculated from the (mock) SZ images of the tSZ (left) / kSZ (right) data. Same colors as in [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Unsharp masking maps of tSZ Y (top) and kSZ w (bottom) at a scale σ = 100 kpc with increasing amount of viscosity from left to right, zoomed into the center compared to [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Shape parameter S (left) and coherence length l (right) of the inverted unsharp-masked tSZ maps. consistent compared to the tSZ signal. More coherent motions are visible for higher viscosity levels, as structures are destroyed later, but this strongly depends on the region analyzed as well as timing differences. In addition, such small differences in the kSZ signal would be very difficult to measure with c… view at source ↗

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Works this paper leans on

41 extracted references · 3 linked inside Pith

  1. [1]

    2020, Mon

    Angelinelli, M., Vazza, F., Giocoli, C., et al. 2020, Mon. Not. R. Astron. Soc., 495, 864

    2020

  2. [2]

    Churazov, E., Khabibullin, I., Lyskova, N., Sunyaev, R., & Bykov, A. M. 2021, Astron. Astrophys., 651, A41

    2021

  3. [3]

    W., & Leibundgut, B

    Dhawan, S., Jha, S. W., & Leibundgut, B. 2018, Astron. Astrophys., 609, A72

    2018

  4. [4]

    2009, Mon

    Dolag, K., Borgani, S., Murante, G., & Springel, V . 2009, Mon. Not. R. Astron. Soc., 399, 497

    2009

  5. [5]

    G., Pilipenko, S., et al

    Dolag, K., Sorce, J. G., Pilipenko, S., et al. 2023, Astron. Astrophys., 677, A169

    2023

  6. [6]

    2018, Space Sci

    Donnert, J., Vazza, F., Brüggen, M., & ZuHone, J. 2018, Space Sci. Rev., 214, 122

    2018

  7. [7]

    S., et al

    Galitzki, N., Ali, A., Arnold, K. S., et al. 2018, in Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy IX, V ol. 10708, eprint: arXiv:1808.04493, 1070804

    Pith/arXiv arXiv 2018

  8. [8]

    P., Valentini, M., & Dolag, K

    Groth, F., Steinwandel, U. P., Valentini, M., & Dolag, K. 2023, Mon. Not. R. Astron. Soc., 526, 616

    2023

  9. [9]

    A., et al

    Groth, F., Valentini, M., Seidel, B. A., et al. 2026, Astrophys. J., 1000, 75

    2026

  10. [10]

    P., Vallés-Pérez, D., & Dolag, K

    Groth, F., Valentini, M., Steinwandel, U. P., Vallés-Pérez, D., & Dolag, K. 2025, Astron. Astrophys., 693, A263 Hernández-Martínez, E., Dolag, K., Seidel, B., et al. 2024, Astron. Astrophys., 687, A253 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al. 2016, Nature, 535, 117 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al. 2018, Publ. Astr...

    2025

  11. [11]

    J., Cha, S., & Cho, H

    HyeongHan, K., Jee, M. J., Cha, S., & Cho, H. 2024, Nat. Astron., 8, 377

    2024

  12. [12]

    2024, Astrophys

    Ignesti, A., Brunetti, G., Gullieuszik, M., et al. 2024, Astrophys. J., 977, 219

    2024

  13. [13]

    G., et al

    Kim, J., Golwala, S., Bartlett, J. G., et al. 2022, Astrophys. J., 926, 179

    2022

  14. [14]

    Kravtsov, A. V . & Borgani, S. 2012, Annu. Rev. Astron. Astrophys., 50, 353

    2012

  15. [15]

    W., Schekochihin, A

    Kunz, M. W., Schekochihin, A. A., & Stone, J. M. 2014, Phys. Rev. Lett., 112, 205003

    2014

  16. [16]

    T., Kravtsov, A

    Lau, E. T., Kravtsov, A. V ., & Nagai, D. 2009, Astrophys. J., 705, 1129

    2009

  17. [17]

    G., Aghanim, N., & Pasté, J

    Lebeau, T., Ettori, S., Sorce, J. G., Aghanim, N., & Pasté, J. 2026, Astron. As- trophys., 707, A336

    2026

  18. [18]

    2023, Mon

    Li, Y ., Luo, R., Fossati, M., Sun, M., & Jáchym, P. 2023, Mon. Not. R. Astron. Soc., 521, 4785

    2023

  19. [19]

    2020, Astron

    Malavasi, N., Aghanim, N., Tanimura, H., Bonjean, V ., & Douspis, M. 2020, Astron. Astrophys., 634, A30

    2020

  20. [20]

    G., Dolag, K., & Aghanim, N

    Malavasi, N., Sorce, J. G., Dolag, K., & Aghanim, N. 2023, Astron. Astrophys., 675, A76

    2023

  21. [21]

    P., Valentini, M., Vallés-Pérez, D., & Dolag, K

    Marin-Gilabert, T., Steinwandel, U. P., Valentini, M., Vallés-Pérez, D., & Dolag, K. 2024, Density Fluctuations in the Intracluster Medium: An Attempt to Constrain Viscosity with Cosmological Simulations

    2024

  22. [22]

    P., & Dolag, K

    Marin-Gilabert, T., Valentini, M., Steinwandel, U. P., & Dolag, K. 2022, Mon. Not. R. Astron. Soc., 517, 5971

    2022

  23. [23]

    2021, Mon

    Mohapatra, R., Federrath, C., & Sharma, P. 2021, Mon. Not. R. Astron. Soc., 500, 5072

    2021

  24. [24]

    Monaghan, J. J. & Lattanzio, J. C. 1985, Astron. Astrophys., 149, 135

    1985

  25. [25]

    2024, in Mm Universe 2023 - Observing the Universe at Mm Wavelengths, V ol

    Perotto, L., Adam, R., Ade, P., et al. 2024, in Mm Universe 2023 - Observing the Universe at Mm Wavelengths, V ol. 293 (eprint: arXiv:2310.04553: EDP), 00040 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2014, Astron. Astro- phys., 571, A16 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2013, Astron. Astro- phys., 554, A140

    Pith/arXiv arXiv 2024

  26. [26]

    2021, Mon

    Sayers, J., Sereno, M., Ettori, S., et al. 2021, Mon. Not. R. Astron. Soc., 505, 4338

    2021

  27. [27]

    Seidel, B., Dolag, K., & Sorce, J. G. 2026, Cutting with Precision – Leveraging Collapse V olumes to Generate the next Generation of Zoom-in Initial Condi- tions

    2026

  28. [28]

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

    Seidel, B. A., Dolag, K., Remus, R.-S., et al. 2024, SLOW IV: Not All That Is Close Will Merge in the End. Superclusters and Their Lagrangian Collapse Regions

    2024

  29. [29]

    & Springel, V

    Sijacki, D. & Springel, V . 2006, Mon. Not. R. Astron. Soc., 371, 1025

    2006

  30. [30]

    Sorce, J. G. 2018, Mon. Not. R. Astron. Soc., 478, 5199

    2018

  31. [31]

    G., Dubois, Y ., Blaizot, J., et al

    Sorce, J. G., Dubois, Y ., Blaizot, J., et al. 2021, Mon. Not. R. Astron. Soc., 504, 2998

    2021

  32. [32]

    1962, Physics of Fully Ionized Gases

    Spitzer, L. 1962, Physics of Fully Ionized Gases

    1962

  33. [33]

    Springel, V ., White, S. D. M., Tormen, G., & Kauffmann, G. 2001, Mon. Not. R. Astron. Soc., 328, 726

    2001

  34. [34]

    A., Quataert, E., & Kunz, M

    Squire, J., Schekochihin, A. A., Quataert, E., & Kunz, M. W. 2019, J. Plasma Phys., 85, 905850114

    2019

  35. [35]

    P., McAlpine, S., Stiskalek, R., et al

    Steinwandel, U. P., McAlpine, S., Stiskalek, R., et al. 2026, Learning the Uni- verse: Constrained Simulations of the Coma Galaxy Cluster – I. Radial X-ray and Compton-y Signatures

    2026

  36. [36]

    G., et al

    Tanimura, H., Hinshaw, G., McCarthy, I. G., et al. 2022, in Mm Universe @ NIKA2 - Observing the Mm Universe with the NIKA2 Camera, V ol. 257 (eprint: arXiv:2111.02088: EDP), 00045

    Pith/arXiv arXiv 2022

  37. [37]

    & Brunetti, G

    Vazza, F. & Brunetti, G. 2025, On the Interpretation of XRISM X-ray Measure- ments of Turbulence in the Intracluster Medium: A Comparison with Cosmo- logical Simulations

    2025

  38. [38]

    2011, Mon

    Vazza, F., Dolag, K., Ryu, D., et al. 2011, Mon. Not. R. Astron. Soc., 418, 960

    2011

  39. [39]

    W., Abi-Saad, S., Ade, P., et al

    Wilson, G. W., Abi-Saad, S., Ade, P., et al. 2020, in Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy X, V ol. 11453, 1145302 XRISM Collaboration, Audard, M., Awaki, H., et al. 2025a, Astrophys. J., 985, L20 XRISM Collaboration, Audard, M., Awaki, H., et al. 2025b, Astrophys. J., 993, L11 XRISM Science Team. 2022, X...

    2020

  40. [40]

    A., et al

    Zhuravleva, I., Churazov, E., Schekochihin, A. A., et al. 2019, Nat. Astron., 3, 832

    2019

  41. [41]

    A., Kunz, M

    ZuHone, J. A., Kunz, M. W., Markevitch, M., Stone, J. M., & Biffi, V . 2014, Astrophys. J., 798, 90 Article number, page 7 of 7

    2014

This paper was first reviewed by deepseek-v4-flash on August 1, 2026.