Pith. sign in

REVIEW 3 major objections 5 minor 47 references

Inferring the mass of the circumgalactic medium using X-ray resonant scattering

T0 review · 3 major / 5 minor · reviewed 2026-07-13 · grok-4.5

Pith's one-line read Resonant scattering of OVII X-ray light from a galaxy's bright core can count the oxygen ions in its faint outer halo from a simple flux ratio.

desk verdict Clean geometric OVII-counting idea that works to 0.2 dex after observable cuts in TNG50; residual bias is openly model-dependent. read the letter →

arxiv 2603.25600 v2 pith:NSO45XSF submitted 2026-03-26 astro-ph.GA astro-ph.CO

classification astro-ph.GAastro-ph.CO
keywords circumgalacticmediumresonantscatteringOVIIX-rayspectroscopyCGMmassmicrocalorimeterTNG50
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

The hot gas that surrounds galaxies is hard to weigh because most of it emits almost no X-rays. This paper shows that the same gas can still be counted: oxygen ions in the outer halo scatter the bright OVII resonant line that comes from the central peak, and the ratio of the two observed fluxes is proportional to the number of those ions. When the method is tested on simulated galaxies that include satellites, asymmetries, and gas motions, and when the most irregular systems are first discarded using only X-ray observables, the outer OVII mass is recovered with a 10 percent bias and about 0.2 dex scatter. Because that OVII mass tracks total oxygen and total gas mass in the same shell, the technique gives a practical route to baryon budgets that future microcalorimeter missions can actually measure.

What carries the argument

Geometric OVII counting: under the thin-shell, optically thin limit the ion number equals a known geometric factor times the inverse average scattering cross-section times the outer-to-inner OVII flux ratio; the cross-section itself is evaluated from the observed line centroids and Doppler widths of the two regions.

What would settle it

Apply the identical flux-ratio estimator to a second cosmological simulation suite that produces substantially different outer-halo velocity fields; if the residual bias or scatter changes by more than the claimed 10 percent / 0.2 dex, the method's claimed accuracy fails.

Watch

Extended reading notes

Core claim

For a clean sample of galaxies selected solely by X-ray observables, the OVII ion mass inside an outer radial shell (R500c to R200c) follows directly from the observed ratio of scattered OVII flux in the corresponding annulus to direct OVII flux from the bright central region (r less than 0.2 R500c), recovering the true mass with only a 10 percent systematic underestimate and an rms scatter of roughly 0.2 dex.

Load-bearing premise

The line widths and centroids seen along our line of sight can be used as if the gas motions were isotropic and random, so that only a small, calibratable fraction of outer ions is missed by Doppler mismatch.

Editorial extensions

If this is right

  • Future microcalorimeter maps that resolve the OVII resonant line can convert a simple flux ratio into an outer-halo OVII mass without needing the continuum.
  • Once OVII mass is known, simulation-calibrated scalings convert it into total oxygen mass and total CGM gas mass inside the same shell.
  • Observable cuts on satellite contamination, azimuthal symmetry, and inner-line width let observers pre-select the galaxies for which the conversion is reliable.
  • The same geometric idea can be repeated for thinner radial shells once surface-brightness profiles are measured.

Reading between the lines

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

  • The residual 10 percent bias is itself a diagnostic of high-velocity outer gas that never enters the resonant window, so the method may constrain outflow and accretion kinematics as a byproduct.
  • Laboratory measurement of the true OVII scattering phase function would remove the last purely geometric systematic before real-world application.
  • If the OVII-to-total-oxygen and OVII-to-gas-mass scalings survive in other feedback models, the technique becomes a direct test of those models rather than a pure mass estimator.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper proposes a geometric method to count OVII ions (and thereby estimate outer-CGM mass) from resonant scattering of the OVIIr line at 574 eV. In the idealized static, spherical, optically thin limit, the outer-shell OVII number is proportional to the observed outer-to-inner flux ratio times a scattering cross-section and geometric factors (Eqs. 1–5, 11). The method is tested on TNG50 galaxies with Monte Carlo radiative transfer of OVIIr. After excluding systems with strong satellite contamination, azimuthal anisotropy, or large-scale outflows using X-ray observables, the estimator recovers the true R500c–R200c OVII mass with ~10% bias and ~0.2 dex rms scatter (Fig. 9). The residual bias is attributed to high-velocity outer gas outside the resonant window (Fig. 10). OVII mass is then linked to total oxygen and CGM mass via TNG50 scaling relations (Eqs. 12–13).

Significance. If the accuracy holds beyond TNG50, the method would give a direct, nearly model-independent count of OVII ions in the faint outer CGM of individual galaxies—precisely the regime where thermal emission is too weak for conventional mass estimates. That is a genuine observational advance for future microcalorimeter missions (NewAthena, HUBS). Strengths include a transparent geometric derivation, self-consistent RT testing, selection cuts defined on observables rather than on the target mass, and an open attribution of the residual bias. The OVII-to-total-mass scalings are secondary and model-dependent, but the primary OVII-counting result is a concrete, falsifiable prediction for real data.

major comments (3)
  1. §5 and Fig. 9: The central claim of 10% bias and ~0.2 dex scatter is demonstrated only for TNG50. The residual bias is explicitly attributed to high-velocity outer gas whose Doppler mismatch places it outside the resonant window of the inner-source photons (Fig. 10; §4.3.1). Different feedback prescriptions produce different outer velocity fields and density profiles, so both the bias and the post-cleaning scatter can change. Because the method is intended for real galaxies whose feedback physics is unknown, the quoted accuracy is not yet shown to be robust. At minimum the paper should (i) restate the abstract/conclusion accuracy as TNG50-specific, (ii) quantify how the bias scales with the outer high-velocity fraction, and (iii) either test a second simulation suite or provide a clear observational diagnostic that the high-velocity fraction is small.
  2. §2.3.2 and §5: Scattering is treated as isotropic, while the true OVII phase function is ∝(1+cos²θ). The paper correctly notes that this is self-consistent inside the simulation but will bias real applications (photons scattered near 90°). Before claiming readiness for NewAthena/HUBS, the geometric estimator (Eq. 11) and the RT pipeline should be re-run with the laboratory or theoretical anisotropic phase function, or a quantitative upper bound on the resulting bias should be given.
  3. Eq. (10) and §4.3.1: The substitution of line-of-sight observed Doppler widths and centroids for the 3D velocity distributions assumes isotropic random motions and that the outer velocity distribution is not broader than the inner one. Fig. 10 shows that the outer shell often has high-velocity wings beyond the inner range; those ions are invisible to the estimator. The paper treats this as a calibratable ~10% bias, but the assumption that LOS profiles adequately capture the resonant window is load-bearing and only weakly tested. A quantitative test (e.g., comparing ⟨σ_scat⟩ from LOS profiles vs. the full 3D velocity field for the clean sample) would strengthen the claim.
minor comments (5)
  1. §2.3.1: The ISM boost parameter b=10^{-4} is free; a short sensitivity check on how b affects the clean-sample recovery would help.
  2. §4.1–4.3: The satellite (15%), NSD (0.3), and W_D,inner (0.7 eV) thresholds are somewhat arbitrary. A brief robustness table showing how bias/scatter change when thresholds are varied would be useful.
  3. Fig. 2 and §3.1: The choice r_inner = 0.2 R500c is the sample median r_90; stating whether results are sensitive to modest changes (e.g., 0.15–0.25 R500c) would clarify generality.
  4. Eqs. (12)–(13): The OVII–oxygen and OVII–CGM scalings are TNG50-specific; the text should more clearly separate the primary geometric OVII count from these secondary, model-dependent conversions.
  5. Typographical: “GCM” appears for “CGM” in §2.2 heading; “esitmate” in §5; “emissivisity” in §2.3.1.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: geometric OVII estimator is independent first-principles; TNG50 supplies validation, average geometric corrections, and empirical mass scalings only.

full rationale

The load-bearing estimator (Eqs. 1–5, 11) is derived from isotropic optically-thin scattering geometry and the definition of optical depth; it does not contain the target outer-shell OVII mass as an input. Average correction prefactors Cτ≈0.92 and Cproj≈0.73 (Sec. 4.4, Fig. 8) are measured once from density profiles and projection geometry for the chosen shell radii and are explicitly described as recoverable from an observed β-model; they are not free parameters adjusted to force the one-to-one recovery in Fig. 9. The residual 10% bias is measured a posteriori, attributed to high-velocity outer gas outside the resonant window (Fig. 10, Sec. 5), and flagged as model-dependent rather than absorbed into the formula. Empirical M_O–M_OVII and M_CGM–M_OVII fits (Eqs. 12–13) are presented as simulation correlations that enable secondary estimates, not as first-principles predictions. Self-citations to Nelson et al. (2023) and Byrohl & Nelson (2025) supply the RT code and parent sample but do not underwrite uniqueness or force the accuracy claim. Observable-based cleaning cuts (satellite fraction, NSD, W_D,inner) remove outliers without tautologically defining the mass. The derivation chain therefore remains non-circular; model dependence of the residual bias is a correctness/transferability issue, not circularity.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The central claim rests on standard radiative-transfer geometry, the TNG50 galaxy-formation model, an isotropic-scattering approximation, and three hand-chosen selection thresholds that define the clean sample. No new physical entities are postulated. The residual 10% bias is accepted as a model-dependent systematic rather than corrected by an additional free parameter.

free parameters (5)
  • satellite-to-core emission threshold = 0.15
    15% cut used to exclude contaminated systems (§4.1); chosen by inspection of the distribution.
  • azimuthal anisotropy NSD threshold = 0.3
    NSD ≥ 0.3 used to flag asymmetric galaxies (§4.2); fiducial value chosen by hand.
  • inner Doppler-width outflow threshold = 0.7 eV
    WD,inner > 0.7 eV used to exclude outflow-dominated systems (§4.3.2); chosen from the sample distribution.
  • ISM boost parameter b = 1e-4
    Fiducial b = 10−4 multiplies hot-ISM OVII emission in the two-phase model (§2.3.1); free scaling parameter.
  • average shell-thickness and projection corrections Cτ, Cproj = Cτ≈0.92, Cproj≈0.73
    Numerical prefactors 0.92 and 0.73 taken from TNG50 averages (Fig. 8) and inserted into Eq. 11.
assumptions (5)
  • ad hoc to paper Scattering is treated as isotropic even though the true OVII phase function is ∝(1+cos²θ).
    Stated in §2.3.2; simulation and estimator are self-consistent, but real-world application will require the laboratory phase function.
  • domain assumption Ionization equilibrium under the Faucher-Giguère UV/X-ray background plus collisional ionization (CLOUDY tables).
    §2.3.1; standard but not re-derived.
  • domain assumption TNG50 baryonic physics (stellar and AGN feedback, metal enrichment) produce realistic CGM density, temperature, and velocity fields.
    Entire validation sample is drawn from TNG50; residual bias is model-dependent (§5).
  • ad hoc to paper Line-of-sight observed Doppler widths and centroids can be substituted for the 3D velocity distributions in the averaged cross-section (Eq. 10).
    §4.3.1; assumes isotropic random motions and that outer wings do not hide a large uncounted mass.
  • domain assumption Optically thin limit (τ ≪ 1) outside the galactic disk/bulge.
    §2.1; standard for CGM resonant lines at these columns.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Inferring the mass of the circumgalactic medium using X-ray resonant scattering." pith.science (2026). https://pith.science/paper/NSO45XSF

@misc{pith2026260325600,
  author       = {Pith},
  title        = {Pith review of: Inferring the mass of the circumgalactic medium using X-ray resonant scattering},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NSO45XSF}},
  note         = {Machine review of arXiv:2603.25600}
}
abstract

The circumgalactic medium (CGM) regulates galaxy growth and retains the imprint of feedback from supernovae and supermassive black holes. However, the bulk of the hot CGM produces little X-ray emission and is challenging to study with X-ray telescopes. We propose a novel method for evaluating the CGM mass using resonant scattering of the helium-like oxygen (\ovii) resonant line at $E=574$ eV. In a spherically symmetric and static CGM halo with a sharp central X-ray peak, the number of \ovii\ ions within an outer radial shell can be calculated from the ratio of the two directly observable quantities: the \ovii\ flux from the bright inner region and the scattered \ovii\ flux from the shell (where the scattered flux can be much higher than the intrinsic emission). To evaluate the accuracy of this geometric estimate for realistic galaxies -- with satellites, asymmetries, and gas velocities -- we use a sample of galaxies from the TNG50 cosmological simulation. We find that, when the most irregular systems are excluded based on their X-ray observables, we accurately predict the \ovii\ mass in the outer halo (e.g., in an $r=R_{\rm 500c}-R_{\rm 200c}$ shell) from the ratio of the fluxes in the corresponding annulus and the central peak region ($r<0.2R_{\rm 500c}$), with only a 10\% bias and an rms scatter of $\sim 0.2$ dex. As \ovii\ mass strongly correlates with the total oxygen and gas mass, this direct \ovii-counting method enables indirect estimates of those quantities by future X-ray microcalorimeter missions, such as {\em NewAthena}\/ and {\em HUBS}.

Figures

Figures reproduced from arXiv: 2603.25600 by the authors.

Figure 1
Figure 1. Resonant scattering can be used to deduce the mass of OVII ions a CGM halo. Most OVIIr photons are emitted within the inner CGM. These photons scatter off OVII ions in the outer CGM, where the intrinsic OVIIr emission is negligible in comparison. The observer sees both the direct OVIIr emission from the central (source) region and photons from the same source scattered off the OVII ions in the outer region. The rati… view at source ↗
Figure 2
Figure 2. Definition of the inner (source) and outer CGM regions based on OVIIr emission profiles and scattering enhancement. Left: The OVIIr cumulative intrinsic (i.e., not considering resonant scattering) emission profiles, normalized to total emission within 𝑅500c, are shown as a function of projected radius. Individual profiles are shown by thin lines, and the thick black line shows the sample median. The vertical dotted … view at source ↗
Figure 3
Figure 3. Effects of resonant scattering on the relation between the OVII mass in the 3D 𝑅500𝑐 − 𝑅200𝑐 shell and the OVIIr flux ratio between the outer and inner projected annuli. Each symbol represents a simulated galaxy in the full TNG50 sample; red and gray symbols show the flux ratios with and without resonant scattering, respectively. Shaded bands show the 16th − 84th percentile ranges and the red line is the red sample … view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Impact of satellite contamination on the scattering 𝑀OVII-flux ratio relation. (a), (b), and (c): Examples of individual galaxies with satellite contamination. Shown are OVIIr surface brightness maps, each 500 kpc on a side. The white circles mark the radii 𝑅500c and 𝑅…
Figure 5
Figure 5. Figure 5: Impact of azimuthal anisotropy in OVIIr emission on the 𝑀OVII-flux ratio relation. (a), (b), and (c): Examples of individual galaxies that exhibit significant anisotropy in their OVIIr surface brightness maps. The map size and annotations follow the same conventions as…
Figure 6
Figure 6. Figure 6: Effects of gas motion in the CGM on OVIIr resonant scattering. (a) and (b): OVIIr surface brightness maps of a TNG50 galaxy for two cases: without and with the velocity field included, respectively. The map size and annotations follow the same conventions as [PITH_FUL…
Figure 7
Figure 7. Figure 7: Effects of large-scale outflows in the inner CGM on OVIIr resonant scattering. (a): Surface brightness map of an example TNG50 galaxy exhibiting a powerful SMBH-driven outflow in the inner CGM. The map size and annotations follow the same conventions as [PITH_FULL_IMA…
Figure 8
Figure 8. Figure 8: Effects of shell thickness and projection. Left: Ratio of true optical depth to that of a uniform density shell as a function of the outer CGM OVII mass. Right: Ratio of the scattered flux ratio 𝐹 Outer OVIIr/𝐹 Inner OVIIr computed using only emission within the 3D inn…
Figure 9
Figure 9. Figure 9: Comparison between the OVII mass in the 𝑅500c − 𝑅200c 3D shell inferred from the scaling relation (equation 11) and the true OVII mass extracted directly from the simulation, for each of the 124 galaxies in the clean sample (Section 4). The shaded area indicates the 16…
Figure 10
Figure 10. Figure 10: Distributions of radial velocities in the inner and outer CGM regions for a TNG50 galaxy. The outer CGM often exhibits high-velocity wings extending beyond the velocity range of the inner region. These high-velocity gas parcels have suppressed OVIIr scattering cross-s…
Figure 11
Figure 11. Figure 11: Mass scaling relations in the outer CGM region: OVII mass vs. total oxygen mass (left) and CGM mass (right) in the outer 𝑅500c − 𝑅200𝑐 shell, for all TNG50 galaxies and the clean sample (filled). Solid lines represent the best-fit scaling relations for the clean sampl…
Figure 12
Figure 12. Figure 12: Phase-space diagram showing the OVII fraction of the total Oxygen content (color) for different gas temperatures and densities. The OVII fraction is calculated using the CLOUDY model described in Section 2, which includes collisional ionization and photoionization by …

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

47 extracted references · 6 canonical work pages

  1. [1]

    2023, MNRAS, 524, 5391, doi: 10.1093/mnras/stad2046

    Ayromlou, M., Nelson, D., & Pillepich, A. 2023, MNRAS, 524, 5391, doi: 10.1093/mnras/stad2046

  2. [2]

    2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

    Barret, D., Lam Trong, T., den Herder, J.-W., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

  3. [3]

    9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, ed

    Series, Vol. 9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, ed. J.-W. A. den Herder, T. Takahashi, & M. Bautz, 99052F, doi: 10.1117/12.2232432 Bogdán, Á., Bourdin, H., Forman, W. R., et al. 2017, ApJ, 850, 98, doi: 10.3847/1538-4357/aa9523

  4. [4]

    2023, Science China Physics, Mechanics, and Astronomy, 66, 299513, doi: 10.1007/s11433-023-2149-y

    Bregman, J., Cen, R., Chen, Y., et al. 2023, Science China Physics, Mechanics, and Astronomy, 66, 299513, doi: 10.1007/s11433-023-2149-y

  5. [5]

    2025, arXiv e-prints, arXiv:2507.11603, doi: 10.48550/arXiv.2507.11603

    Byrohl, C., & Nelson, D. 2025, arXiv e-prints, arXiv:2507.11603, doi: 10.48550/arXiv.2507.11603

  6. [6]

    2021, MNRAS, 506, 5129, doi: 10.1093/mnras/stab1958

    Byrohl, C., Nelson, D., Behrens, C., et al. 2021, MNRAS, 506, 5129, doi: 10.1093/mnras/stab1958

  7. [7]

    D., et al

    Chadayammuri, U., Bogdán, Á., Oppenheimer, B. D., et al. 2022, ApJL, 936, L15, doi: 10.3847/2041-8213/ac8936

  8. [8]

    1950, Radiative Transfer (New York: Dover Publications)

    Chandrasekhar, S. 1950, Radiative Transfer (New York: Dover Publications)

Show all 47 references
  1. [9]

    2001, MNRAS, 323, 93, doi: 10.1046/j.1365-8711.2001.04090.x

    Churazov, E., Haehnelt, M., Kotov, O., & Sunyaev, R. 2001, MNRAS, 323, 93, doi: 10.1046/j.1365-8711.2001.04090.x

  2. [10]

    2010, SSRv, 157, 193, doi: 10.1007/s11214-010-9685-4

    Churazov, E., Zhuravleva, I., Sazonov, S., & Sunyaev, R. 2010, SSRv, 157, 193, doi: 10.1007/s11214-010-9685-4

  3. [11]

    2022, A&A, 666, A156, doi: 10.1051/0004-6361/202243101

    Comparat, J., Truong, N., Merloni, A., et al. 2022, A&A, 666, A156, doi: 10.1051/0004-6361/202243101

  4. [12]

    2023, ApJ, 951, 125, doi: 10.3847/1538-4357/acd764

    Das, S., Chiang, Y.-K., & Mathur, S. 2023, ApJ, 951, 125, doi: 10.3847/1538-4357/acd764

  5. [13]

    2006, MNRAS, 368, 2, doi: 10.1111/j.1365-2966.2006.10145.x Faucher-Giguère, C.-A., Kereš, D., & Ma, C.-P

    Dekel, A., & Birnboim, Y. 2006, MNRAS, 368, 2, doi: 10.1111/j.1365-2966.2006.10145.x Faucher-Giguère, C.-A., Kereš, D., & Ma, C.-P. 2011, MNRAS, 417, 2982, doi: 10.1111/j.1365-2966.2011.19457.x Faucher-Giguère, C.-A., Lidz, A., Zaldarriaga, M., & Hernquist, L. 2009, ApJ, 703, ...

  6. [14]

    R., Syunyaev, R

    Gilfanov, M. R., Syunyaev, R. A., & Churazov, E. M. 1987, Pisma v Astronomicheskii Zhurnal, 13, 7

  7. [15]

    P., Hill, J

    Greco, J. P., Hill, J. C., Spergel, D. N., & Battaglia, N. 2015, ApJ, 808, 151, doi: 10.1088/0004-637X/808/2/151

  8. [16]

    Hamilton, D. R. 1947, ApJ, 106, 457, doi: 10.1086/144976

  9. [17]

    2019, MNRAS, 482, 4972, doi: 10.1093/mnras/sty2992 15

    Khabibullin, I., & Churazov, E. 2019, MNRAS, 482, 4972, doi: 10.1093/mnras/sty2992 15

  10. [18]

    2022, arXiv e-prints, arXiv:2211.09827, doi: 10.48550/arXiv.2211.09827

    Kraft, R., Markevitch, M., Kilbourne, C., et al. 2022, arXiv e-prints, arXiv:2211.09827, doi: 10.48550/arXiv.2211.09827

  11. [19]

    N., Wang, Q

    Li, J.-T., Bregman, J. N., Wang, Q. D., et al. 2017, ApJS, 233, 20, doi: 10.3847/1538-4365/aa96fc

  12. [20]

    H., Mo, H

    Lim, S. H., Mo, H. J., Li, R., et al. 2018, ApJ, 854, 181, doi: 10.3847/1538-4357/aaaa21

  13. [21]

    2018, MNRAS, 480, 5113, doi: 10.1093/mnras/sty2206

    Marinacci, F., Vogelsberger, M., Pakmor, R., et al. 2018, MNRAS, 480, 5113, doi: 10.1093/mnras/sty2206

  14. [22]

    2012, MNRAS, 426, 1870, doi: 10.1111/j.1365-2966.2012.21831.x

    Mineo, S., Gilfanov, M., & Sunyaev, R. 2012, MNRAS, 426, 1870, doi: 10.1111/j.1365-2966.2012.21831.x

  15. [23]

    P., Pillepich, A., Springel, V., et al

    Naiman, J. P., Pillepich, A., Springel, V., et al. 2018, MNRAS, 477, 1206, doi: 10.1093/mnras/sty618

  16. [24]

    2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040 —

    Nelson, D., Pillepich, A., Springel, V., et al. 2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040 —. 2019, MNRAS, 490, 3234, doi: 10.1093/mnras/stz2306

  17. [25]

    2023, MNRAS, 522, 3665, doi: 10.1093/mnras/stad1195

    Nelson, D., Byrohl, C., Ogorzalek, A., et al. 2023, MNRAS, 522, 3665, doi: 10.1093/mnras/stad1195

  18. [26]

    D., Crain, R

    Nica, A., Oppenheimer, B. D., Crain, R. A., et al. 2022, MNRAS, 517, 1958, doi: 10.1093/mnras/stac2020

  19. [27]

    Crain, R. A. 2018, MNRAS, 474, 4740, doi: 10.1093/mnras/stx2967 Péroux, C., Nelson, D., van de Voort, F., et al. 2020, MNRAS, 499, 2462, doi: 10.1093/mnras/staa2888

  20. [28]

    2021, MNRAS, 508, 4667, doi: 10.1093/mnras/stab2779 Pillepich,A.,Nelson,D., Hernquist,L.,etal.2018a,MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

    Pillepich, A., Nelson, D., Truong, N., et al. 2021, MNRAS, 508, 4667, doi: 10.1093/mnras/stab2779 Pillepich,A.,Nelson,D., Hernquist,L.,etal.2018a,MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

  21. [29]

    2018b, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656

    Pillepich, A., Springel, V., Nelson, D., et al. 2018b, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656

  22. [30]

    2019, MNRAS, 490, 3196, doi: 10.1093/mnras/stz2338 Planck Collaboration, Ade, P

    Pillepich, A., Nelson, D., Springel, V., et al. 2019, MNRAS, 490, 3196, doi: 10.1093/mnras/stz2338 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2013, A&A, 557, A52, doi: 10.1051/0004-6361/201220941 —. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830

  23. [31]

    A., et al

    Schellenberger, G., Bogdán, Á., ZuHone, J. A., et al. 2024, ApJ, 969, 85, doi: 10.3847/1538-4357/ad4548

  24. [32]

    2010, MNRAS, 401, 791, doi: 10.1111/j.1365-2966.2009.15715.x

    Springel, V. 2010, MNRAS, 401, 791, doi: 10.1111/j.1365-2966.2009.15715.x

  25. [33]

    2003, MNRAS, 339, 289, doi: 10.1046/j.1365-8711.2003.06206.x

    Springel, V., & Hernquist, L. 2003, MNRAS, 339, 289, doi: 10.1046/j.1365-8711.2003.06206.x

  26. [34]

    2018, MNRAS, 475, 676, doi: 10.1093/mnras/stx3304

    Springel, V., Pakmor, R., Pillepich, A., et al. 2018, MNRAS, 475, 676, doi: 10.1093/mnras/stx3304

  27. [35]

    A., & Zeldovich, Y

    Sunyaev, R. A., & Zeldovich, Y. B. 1969, Nature, 223, 721, doi: 10.1038/223721a0

  28. [36]

    Suresh, J., Rubin, K. H. R., Kannan, R., et al. 2017, MNRAS, 465, 2966, doi: 10.1093/mnras/stw2499

  29. [37]

    2021, MNRAS, 508, 1563, doi: 10.1093/mnras/stab2638

    Truong, N., Pillepich, A., Nelson, D., Werner, N., & Hernquist, L. 2021, MNRAS, 508, 1563, doi: 10.1093/mnras/stab2638

  30. [38]

    2023, MNRAS, 525, 1976, doi: 10.1093/mnras/stad2216

    Truong, N., Pillepich, A., Nelson, D., et al. 2023, MNRAS, 525, 1976, doi: 10.1093/mnras/stad2216

  31. [39]

    S., & Werk, J

    Tumlinson, J., Peeples, M. S., & Werk, J. K. 2017, ARA&A, 55, 389, doi: 10.1146/annurev-astro-091916-055240

  32. [40]

    A., Verner, E

    Verner, D. A., Verner, E. M., & Ferland, G. J. 1996, Atomic Data and Nuclear Data Tables, 64, 1, doi: 10.1006/adnd.1996.0018

  33. [41]

    2017, MNRAS, 465, 3291, doi: 10.1093/mnras/stw2944

    Weinberger, R., Springel, V., Hernquist, L., et al. 2017, MNRAS, 465, 3291, doi: 10.1093/mnras/stw2944

  34. [42]

    R., Churazov, E., & Scannapieco, E

    Werner, N., McNamara, B. R., Churazov, E., & Scannapieco, E. 2019, SSRv, 215, 5, doi: 10.1007/s11214-018-0571-9

  35. [43]

    White, S. D. M., & Frenk, C. S. 1991, ApJ, 379, 52, doi: 10.1086/170483

  36. [44]

    White, S. D. M., & Rees, M. J. 1978, MNRAS, 183, 341, doi: 10.1093/mnras/183.3.341

  37. [45]

    Yusef-Zadeh, F., Morris, M., & White, R. L. 1984, ApJ, 278, 186, doi: 10.1086/161780

  38. [46]

    2024a, A&A, 690, A267, doi: 10.1051/0004-6361/202449412 —

    Zhang, Y., Comparat, J., Ponti, G., et al. 2024a, A&A, 690, A267, doi: 10.1051/0004-6361/202449412 —. 2024b, A&A, 690, A268, doi: 10.1051/0004-6361/202449413 —. 2025, A&A, 693, A197, doi: 10.1051/0004-6361/202452273

  39. [47]

    2020, MNRAS, 499, 768, doi: 10.1093/mnras/staa2607

    Zinger, E., Pillepich, A., Nelson, D., et al. 2020, MNRAS, 499, 768, doi: 10.1093/mnras/staa2607

Pith tools

Reviewed July 13, 2026 · model on record in the stance chip above.