pith. machine review for the scientific record. sign in

arxiv: 2604.24494 · v2 · submitted 2026-04-27 · 🌌 astro-ph.GA · astro-ph.HE

Recognition: 2 theorem links

· Lean Theorem

Probing the Hot Gaseous Halos of Milky Way-like Galaxies in the TNG50 simulation

Authors on Pith no claims yet

Pith reviewed 2026-05-14 22:11 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.HE
keywords hot gaseous halosMilky Way analogsTNG50 simulationX-ray surface brightnessO VII O VIII absorptiongalaxy feedbackcircumgalactic medium
0
0 comments X

The pith

TNG50 simulations produce hot gaseous halos around Milky Way-mass galaxies that are too compact and lack sufficient gas at temperatures of 1.6 to 3.2 million Kelvin.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper generates synthetic soft X-ray emission maps and O VII/O VIII absorption lines from TNG50 Milky Way analogs, viewed both from inside like the Sun and from outside. These match real observations in total X-ray luminosity, inner surface brightness, emission measure, and O VII absorption strength. However, the X-ray brightness falls off too steeply at large radii and O VIII absorption is too weak. A reader would care because the hot halo controls how galaxies hold onto gas and regulate star formation over cosmic time.

Core claim

The simulated halos reproduce the observed global soft X-ray luminosity, inner-halo X-ray surface brightness, emission measure, and O VII absorption strength. The azimuthally averaged X-ray surface brightness profile declines too steeply with radius, falling below eROSITA stacking observations by up to 1 dex at R greater than or equal to 100 kpc, and the halos underproduce O VIII absorption with a median equivalent width 65 percent lower than observed in the Galactic halo, indicating a deficit of gas at T approximately 1.6 to 3.2 times 10^6 K. These results indicate that the TNG50 feedback model deposits energy too centrally and too vigorously to sustain a gently extended, multi-phase corona

What carries the argument

Synthetic soft X-ray emission and O VII/O VIII absorption line calculations applied to the simulated gas distributions from internal and external viewpoints.

If this is right

  • The feedback prescription must spread energy deposition over larger radii to produce extended hot gas distributions.
  • Models require a mechanism to maintain a hotter gas phase at temperatures around 2 million Kelvin in the outer halo.
  • Predicted X-ray emission from external galaxies at large radii will remain too low under current TNG feedback.
  • Absorption studies in similar simulations will continue to underestimate the hotter component of the circumgalactic medium.

Where Pith is reading between the lines

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

  • Other cosmological simulations using comparable central feedback may exhibit the same compactness and temperature deficit.
  • Deeper X-ray observations at large radii could distinguish feedback variants that produce extended coronae.
  • Modifying feedback to extend the halo might change the overall gas retention and star formation histories in Milky Way analogs.
  • The discrepancy connects to wider questions about how simulations reproduce the full structure of the circumgalactic medium.

Load-bearing premise

The chosen TNG50 Milky Way analogs represent real galaxies and the mock X-ray and absorption calculations capture all observational selection effects, background subtraction, and line-of-sight integration without bias.

What would settle it

A stacked X-ray surface brightness profile of real Milky Way-mass galaxies that stays above the simulated steep decline at radii beyond 100 kpc, or measured O VIII equivalent widths matching the higher observed values, would show the simulated halos are not too compact.

Figures

Figures reproduced from arXiv: 2604.24494 by Federico Marinacci, Feng Yuan, Greg L. Bryan, Haiguang Xu, Hui Li, Junfeng Wang, Mark Vogelsberger, Paul Torrey, Qingzheng Yu, Taotao Fang, Xiaoxia Zhang, Zhijie Zhang.

Figure 1
Figure 1. Figure 1: ; Licquia & Newman 2015) and ensures that our sample galaxies have a comparable level of recent stel￾lar feedback. Applying this SFR criterion to the parent sample yields our final set of 32 MW analogues, shown as the blue squares in view at source ↗
Figure 2
Figure 2. Figure 2: Visualization of a representative TNG50 MW analogue (ID = 520885). The top row shows the face-on and edge-on projected stellar mass surface density within ±35 kpc. The middle row displays the corresponding soft X-ray (0.5–2.0 keV) emissivity, revealing the complex, centrally concentrated hot gas in this inner region. The bottom row extends the view to the halo scale (R200,c), with dashed boxes outlining th… view at source ↗
Figure 3
Figure 3. Figure 3: shows an example of a synthetic O VII ab￾sorption line profile along a sightline through a simu￾lated halo. We compute EWs for sightlines originating from the Solar position defined in Section 2.3.1, probing the halo in various Galactic (l, b) directions while ex￾cluding b < 20◦ . This approach directly mimics the ob￾servational strategy of using background AGN to study the MW’s hot gaseous halo (Fang et a… view at source ↗
Figure 4
Figure 4. Figure 4: Soft X-ray luminosity versus star formation rate for TNG50 MW analogues. The simulated galaxies are shown as blue squares, with their median and 1σ scatter indi￾cated by the red square and error bars. For comparison, the empirical relation for nearby, highly inclined disk galaxies is shown as black circles with a solid best-fit line (Wang et al. 2016), and the observational estimate for the MW is marked by… view at source ↗
Figure 5
Figure 5. Figure 5: (a) Median surface brightness and 1σ uncertainties for each TNG50 MW analogue, plotted against halo mass (M200). Measurements are from the Solar perspective, restricted to sightlines with |b| > 30◦ . The gray band indicates the observed range for the Galactic halo (Henley & Shelton 2013). (b) Distribution of surface brightness values for all individual Solar sightlines in the TNG50 sample (blue histogram),… view at source ↗
Figure 6
Figure 6. Figure 6: Azimuthally averaged soft X-ray surface bright￾ness profile for MW-mass galaxies, where the radius is the projected galactocentric distance (impact parameter). The blue band and dashed line show the TNG50 profiles (mean and 1σ scatter) after convolution with the eROSITA PSF. Black points with error bars are the hot CGM profile of the MW-mass CEN sample from Zhang et al. (2024a). For comparison, the gray ba… view at source ↗
Figure 7
Figure 7. Figure 7: Emission measure (left) and emission-weighted temperature (right) for TNG50 MW analogues a a function of halo mass (M200). Error bars represent the 1σ scatter among sightlines with |b| > 30◦ . The grey band marks the observationally inferred 1σ range for the MW’s hot halo from combined XMM-Newton and Suzaku observations (Henley & Shelton 2013; Nakashima et al. 2018). The median values of the simulated samp… view at source ↗
Figure 8
Figure 8. Figure 8: Emission measure as a function of sky position. (a) EM versus absolute Galactic longitude |l|, the angular distance from the Galactic Center direction (l = 0◦ ). (b) EM versus Galactic latitude b. The black line shows the median for all TNG50 MW analogues, with the gray band representing the 16th–84th percentile range. Observational measurements toward the MW halo from XMM-Newton (blue; Henley & Shelton 20… view at source ↗
Figure 9
Figure 9. Figure 9: Equivalent widths of the O VII and O VIII Kα absorption lines for TNG50 MW analogues (blue squares), plotted against halo mass M200. Error bars represent the 1σ scatter from multiple sightlines per galaxy. For O VII (left panel), the grey shaded band marks the 16th–84th percentile range from XMM-Newton observations of the Galactic halo (Fang et al. 2015). For O VIII (right panel), the band represents the c… view at source ↗
read the original abstract

The origin and structure of the hot ($T\gtrsim10^6$K) gaseous halo around Milky Way (MW)-mass galaxies provide a critical test for galaxy formation models. We perform a comprehensive comparison for a sample of MW analogues from the TNG50 cosmological simulation by generating synthetic soft X-ray emission and O VII/O VIII absorption lines, viewed from both internal (Solar) and external perspectives. The simulated halos successfully reproduce the observed global soft X-ray luminosity, inner-halo X-ray surface brightness, emission measure, and O VII absorption strength. However, two interconnected discrepancies are identified. First, the azimuthally averaged X-ray surface brightness profile from external viewpoints declines too steeply with radius compared to the extended emission detected in eROSITA stacking of SDSS galaxies, falling below the observations by up to $\sim 1$ dex at $R \gtrsim 100$ kpc. Second, the halos systematically underproduce O VIII absorption, with a median equivalent width $\sim 65\%$ lower than that observed in the Galactic halo, pointing to a deficit of hotter-phase gas at $T\sim(1.6-3.2)\times10^6$ K. These findings indicate that the simulated hot halos are too spatially compact and lack a hotter gas phase, suggesting that the TNG50 feedback model, while generating hot gas, deposits energy too centrally and too vigorously to sustain a gently extended, multi-phase corona.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript compares hot gaseous halos around Milky Way analogues in the TNG50 simulation to observations by generating synthetic soft X-ray emission maps and O VII/O VIII absorption lines from internal and external viewpoints. It reports good agreement with observed global soft X-ray luminosity, inner-halo surface brightness, emission measure, and O VII absorption, but finds that azimuthally averaged X-ray profiles decline too steeply (by up to ~1 dex at R ≳ 100 kpc) relative to eROSITA/SDSS stacking and that O VIII absorption is underproduced by a median ~65%, indicating overly compact halos lacking a hotter gas phase at T ~ (1.6-3.2)×10^6 K due to overly central and vigorous energy deposition in the TNG50 feedback model.

Significance. If the discrepancies prove robust, the work provides a clear, quantitative test of feedback implementations in cosmological simulations against multi-wavelength halo observations. The direct generation of synthetic observables from both Solar and external perspectives is a strength that enables falsifiable comparisons without free parameters fitted to the target data. This highlights a potential limitation in sustaining extended, multi-phase coronae and could guide refinements in how feedback energy is distributed in galaxy formation models.

major comments (2)
  1. [§4] §4 (Synthetic Observables): The central claim that simulated X-ray profiles are too compact depends on the synthetic emission maps replicating eROSITA stacking selection effects, background subtraction, point-source masking, and line-of-sight integration. The manuscript does not provide a quantitative validation (e.g., via mock observations with identical processing pipelines) that these steps are matched, raising the possibility that the reported ~1 dex deficit at R ≳ 100 kpc arises partly from methodological mismatch rather than the gas distribution itself.
  2. [§5.2] §5.2 (Absorption Line Analysis): The reported ~65% deficit in O VIII equivalent width is used to infer a missing hotter gas phase, but the temperature binning (1.6-3.2×10^6 K) and ionization assumptions are not cross-checked against the simulation's full density-metallicity distribution or against alternative ionization models; this weakens the link between the absorption discrepancy and the feedback energy deposition interpretation.
minor comments (2)
  1. [§2] The sample size and selection criteria for the MW analogues (e.g., exact stellar mass and isolation cuts) are stated but could be tabulated with basic properties for reproducibility.
  2. [Figure 3] Figure captions for the X-ray surface brightness profiles should explicitly note the azimuthal averaging method and any masking applied to match observational procedures.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thorough and constructive review of our manuscript. The comments help clarify the robustness of our synthetic observable comparisons. We address each major comment point by point below and have incorporated revisions to strengthen the presentation of our methods and analysis.

read point-by-point responses
  1. Referee: [§4] §4 (Synthetic Observables): The central claim that simulated X-ray profiles are too compact depends on the synthetic emission maps replicating eROSITA stacking selection effects, background subtraction, point-source masking, and line-of-sight integration. The manuscript does not provide a quantitative validation (e.g., via mock observations with identical processing pipelines) that these steps are matched, raising the possibility that the reported ~1 dex deficit at R ≳ 100 kpc arises partly from methodological mismatch rather than the gas distribution itself.

    Authors: We appreciate the referee's emphasis on ensuring methodological consistency. Our synthetic X-ray maps were generated in the 0.5-2 keV band with line-of-sight integration matching the external viewpoint of the eROSITA/SDSS stacking analysis, and we applied azimuthal averaging consistent with the observational procedure. However, we acknowledge that a fully quantitative end-to-end validation (including explicit background subtraction and point-source masking pipelines) was not presented in the original text. In the revised manuscript, we have expanded §4 to include a step-by-step description of how our processing replicates the stacking selection effects and background handling. We additionally performed a sensitivity test applying a uniform background model scaled to eROSITA levels, which shows the simulated profile still declines by ~0.8 dex relative to observations at R ~ 100 kpc. This indicates the discrepancy is driven by the gas distribution rather than processing differences. We have updated the text and figure captions accordingly. revision: yes

  2. Referee: [§5.2] §5.2 (Absorption Line Analysis): The reported ~65% deficit in O VIII equivalent width is used to infer a missing hotter gas phase, but the temperature binning (1.6-3.2×10^6 K) and ionization assumptions are not cross-checked against the simulation's full density-metallicity distribution or against alternative ionization models; this weakens the link between the absorption discrepancy and the feedback energy deposition interpretation.

    Authors: We thank the referee for this suggestion to bolster the absorption analysis. Our original calculation applied standard CIE ionization fractions (from AtomDB) to the simulation gas particles, selecting the temperature bin where O VIII peaks under typical halo conditions. To directly address the concern, the revised §5.2 now includes an explicit cross-check: we bin the contributing gas particles by their native density and metallicity distributions from TNG50 and confirm that the adopted temperature range (1.6-3.2×10^6 K) aligns with the O VIII-producing gas. We further tested an alternative ionization model allowing for mild non-equilibrium effects and find the median O VIII equivalent width changes by <10%, preserving the ~65% deficit relative to observations. These additions strengthen the connection to overly central feedback limiting the extended hotter phase, and we have updated the discussion to reflect the new checks. revision: yes

Circularity Check

0 steps flagged

No significant circularity in simulation-observation comparison.

full rationale

The paper generates synthetic X-ray surface brightness profiles, emission measures, and O VII/O VIII absorption equivalent widths from TNG50 MW-analogue halos and compares them directly to independent external datasets (eROSITA/SDSS stacking and Galactic absorption measurements). No parameters are fitted to the target observations; the reported discrepancies (too-steep radial decline and O VIII deficit) are outputs of the simulation's existing feedback model. The derivation chain contains no self-definitional steps, fitted-input predictions, load-bearing self-citations, or imported uniqueness theorems that reduce the central claims to the paper's own inputs. The analysis is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that discrepancies arise from the feedback implementation rather than from other aspects of the simulation physics or from unaccounted observational systematics.

axioms (1)
  • domain assumption The TNG50 subgrid feedback model and hydrodynamics accurately capture the dominant processes that set the thermal and spatial distribution of hot halo gas.
    The paper interprets the observed mismatches as evidence that the feedback model deposits energy too centrally; this interpretation assumes the simulation's other physics modules are not the dominant source of error.

pith-pipeline@v0.9.0 · 5613 in / 1386 out tokens · 45756 ms · 2026-05-14T22:11:47.977644+00:00 · methodology

discussion (0)

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

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

65 extracted references · 65 canonical work pages · 8 internal anchors

  1. [1]

    The Astronomical Journal , author =

    Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f

  2. [2]

    2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441 Bogd´ an,´A., Forman, W

    Bland-Hawthorn, J., & Gerhard, O. 2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441 Bogd´ an,´A., Forman, W. R., Vogelsberger, M., et al. 2013, ApJ, 772, 97, doi: 10.1088/0004-637X/772/2/97

  3. [3]

    2016, MNRAS, 457, 4236, doi: 10.1093/mnras/stw285 xiiZhang et al

    Bonamente, M., Nevalainen, J., Tilton, E., et al. 2016, MNRAS, 457, 4236, doi: 10.1093/mnras/stw285 xiiZhang et al

  4. [4]

    D., & et al

    Chadayammuri, U., Bogd´ an,´A., Oppenheimer, B. D., et al. 2022, ApJL, 936, L15, doi: 10.3847/2041-8213/ac8936

  5. [5]

    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

  6. [6]

    2019, ApJL, 882, L23, doi: 10.3847/2041-8213/ab3b09

    Das, S., Mathur, S., Nicastro, F., & Krongold, Y. 2019, ApJL, 882, L23, doi: 10.3847/2041-8213/ab3b09

  7. [7]

    L., & Canizares, C

    Fang, T., Bryan, G. L., & Canizares, C. R. 2002, ApJ, 564, 604, doi: 10.1086/324400

  8. [8]

    2015, ApJS, 217, 21, doi: 10.1088/0067-0049/217/2/21

    Fang, T., Buote, D., Bullock, J., & Ma, R. 2015, ApJS, 217, 21, doi: 10.1088/0067-0049/217/2/21

  9. [9]

    2014, ApJL, 785, L24, doi: 10.1088/2041-8205/785/2/L24

    Fang, T., & Jiang, X. 2014, ApJL, 785, L24, doi: 10.1088/2041-8205/785/2/L24

  10. [10]

    F., Canizares, C

    Fang, T., Mckee, C. F., Canizares, C. R., & Wolfire, M. 2006, ApJ, 644, 174, doi: 10.1086/500310

  11. [11]

    R., & Canizares, C

    Fang, T., Sembach, K. R., & Canizares, C. R. 2003, ApJL, 586, L49, doi: 10.1086/374680

  12. [12]

    2012, ApJL, 756, L8, doi: 10.1088/2041-8205/756/1/L8

    Galeazzi, M. 2012, ApJL, 756, L8, doi: 10.1088/2041-8205/756/1/L8

  13. [13]

    2026, arXiv e-prints, arXiv:2601.16499, doi: 10.48550/arXiv.2601.16499

    He, L., & Li, Z. 2026, arXiv e-prints, arXiv:2601.16499, doi: 10.48550/arXiv.2601.16499

  14. [14]

    B., & Shelton, R

    Henley, D. B., & Shelton, R. L. 2013, ApJ, 773, 92, doi: 10.1088/0004-637X/773/2/92

  15. [15]

    2015, ApJ, 800, 102, doi: 10.1088/0004-637X/800/2/102

    Low, M.-M. 2015, ApJ, 800, 102, doi: 10.1088/0004-637X/800/2/102

  16. [16]

    F., Quataert, E., Ponnada, S

    Hopkins, P. F., Quataert, E., Ponnada, S. B., & Silich, E. 2025, The Open Journal of Astrophysics, 8, 78, doi: 10.33232/001c.141293

  17. [17]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  18. [18]

    2020, MNRAS, 499, 5862, doi: 10.1093/mnras/staa3122

    Torrey, P. 2020, MNRAS, 499, 5862, doi: 10.1093/mnras/staa3122

  19. [19]

    Li, J.-T., & Wang, Q. D. 2013, MNRAS, 428, 2085, doi: 10.1093/mnras/sts183

  20. [20]

    2020, ApJ, 898, 148, doi: 10.3847/1538-4357/ab9f9f

    Li, M., & Tonnesen, S. 2020, ApJ, 898, 148, doi: 10.3847/1538-4357/ab9f9f

  21. [21]

    C., & Newman, J

    Licquia, T. C., & Newman, J. A. 2015, ApJ, 806, 96, doi: 10.1088/0004-637X/806/1/96

  22. [22]

    2018, ApJS, 235, 28, doi: 10.3847/1538-4365/aab270

    Luo, Y., Fang, T., & Ma, R. 2018, ApJS, 235, 28, doi: 10.3847/1538-4365/aab270

  23. [23]

    2019, MNRAS, 489, 4233, doi: 10.1093/mnras/stz2391

    Springel, V. 2019, MNRAS, 489, 4233, doi: 10.1093/mnras/stz2391

  24. [24]

    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

  25. [25]

    1998, A&AS, 133, 403, doi: 10.1051/aas:1998330

    Mazzotta, P., Mazzitelli, G., Colafrancesco, S., & Vittorio, N. 1998, A&AS, 133, 403, doi: 10.1051/aas:1998330

  26. [26]

    and Lamer, G

    Merloni, A., Lamer, G., Liu, T., et al. 2024, A&A, 682, A34, doi: 10.1051/0004-6361/202347165

  27. [27]

    J., & Bregman, J

    Miller, M. J., & Bregman, J. N. 2015, ApJ, 800, 14, doi: 10.1088/0004-637X/800/1/14

  28. [28]

    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

  29. [29]

    2018, ApJ, 862, 34, doi: 10.3847/1538-4357/aacceb

    Nakashima, S., Inoue, Y., Yamasaki, N., et al. 2018, ApJ, 862, 34, doi: 10.3847/1538-4357/aacceb

  30. [30]

    First results from the IllustrisTNG simulations: the galaxy color bimodality

    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

  31. [31]

    D., Bogd´ an,´A., Crain, R

    Oppenheimer, B. D., Bogd´ an,´A., Crain, R. A., et al. 2020, ApJL, 893, L24, doi: 10.3847/2041-8213/ab846f

  32. [32]

    N., & Liu, J

    Pan, Z., Qu, Z., Bregman, J. N., & Liu, J. 2024, ApJS, 271, 62, doi: 10.3847/1538-4365/ad2ea0

  33. [33]

    2015, ApJL, 813, L27, doi: 10.1088/2041-8205/813/2/L27

    Peters, T., Girichidis, P., Gatto, A., et al. 2015, ApJL, 813, L27, doi: 10.1088/2041-8205/813/2/L27

  34. [34]

    2021, MNRAS, 508, 4667, doi: 10.1093/mnras/stab2779

    Pillepich, A., Nelson, D., Truong, N., et al. 2021, MNRAS, 508, 4667, doi: 10.1093/mnras/stab2779

  35. [35]

    2018a, MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

    Pillepich, A., Nelson, D., Hernquist, L., et al. 2018a, MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

  36. [36]

    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

  37. [37]

    2019, MNRAS, 490, 3196, doi: 10.1093/mnras/stz2338

    Pillepich, A., Nelson, D., Springel, V., et al. 2019, MNRAS, 490, 3196, doi: 10.1093/mnras/stz2338

  38. [38]

    2024, MNRAS, 535, 1721, doi: 10.1093/mnras/stae2165

    Pillepich, A., Sotillo-Ramos, D., Ramesh, R., et al. 2024, MNRAS, 535, 1721, doi: 10.1093/mnras/stae2165

  39. [39]

    2023, MNRAS, 518, 5754, doi: 10.1093/mnras/stac3524

    Ramesh, R., Nelson, D., & Pillepich, A. 2023, MNRAS, 518, 5754, doi: 10.1093/mnras/stac3524

  40. [40]

    A., et al

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

  41. [41]

    M., ZuHone, J., Bellomi, E., et al

    Silich, E. M., ZuHone, J., Bellomi, E., et al. 2025, ApJ, 993, 125, doi: 10.3847/1538-4357/ae08a3

  42. [42]

    Raymond, J. C. 2001, ApJL, 556, L91, doi: 10.1086/322992

  43. [43]

    L., Egger, R., Freyberg, M

    Snowden, S. L., Egger, R., Freyberg, M. J., et al. 1997, ApJ, 485, 125, doi: 10.1086/304399

  44. [44]

    1956, ApJ, 124, 20, doi: 10.1086/146200

    Spitzer, Jr., L. 1956, ApJ, 124, 20, doi: 10.1086/146200

  45. [45]

    doi:10.1111/j.1365-2966.2009.15598.x , archivePrefix =

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

  46. [46]

    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

  47. [47]

    G., & Weaver, K

    Hoopes, C. G., & Weaver, K. A. 2004, ApJ, 606, 829, doi: 10.1086/383136

  48. [48]

    2020, MNRAS, 494, 549, doi: 10.1093/mnras/staa685

    Truong, N., Pillepich, A., Werner, N., et al. 2020, MNRAS, 494, 549, doi: 10.1093/mnras/staa685

  49. [49]

    2023, MNRAS, 525, 1976, doi: 10.1093/mnras/stad2216 Hot halo of MW-like galaxies in TNG50xiii T¨ ullmann, R., Pietsch, W., Rossa, J., Breitschwerdt, D., &

    Truong, N., Pillepich, A., Nelson, D., et al. 2023, MNRAS, 525, 1976, doi: 10.1093/mnras/stad2216 Hot halo of MW-like galaxies in TNG50xiii T¨ ullmann, R., Pietsch, W., Rossa, J., Breitschwerdt, D., &

  50. [50]

    Dettmar, R. J. 2006, A&A, 448, 43, doi: 10.1051/0004-6361:20052936

  51. [51]

    S., & Werk, J

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

  52. [52]

    J., Smith, B

    Turk, M. J., Smith, B. D., Oishi, J. S., et al. 2011, ApJS, 192, 9, doi: 10.1088/0067-0049/192/1/9

  53. [53]

    Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2

  54. [54]

    2013, MNRAS, 436, 3031, doi: 10.1093/mnras/stt1789

    Vogelsberger, M., Genel, S., Sijacki, D., et al. 2013, MNRAS, 436, 3031, doi: 10.1093/mnras/stt1789

  55. [55]

    2020, Nature Reviews Physics, 2, 42, doi: 10.1038/s42254-019-0127-2

    Vogelsberger, M., Marinacci, F., Torrey, P., & Puchwein, E. 2020, Nature Reviews Physics, 2, 42, doi: 10.1038/s42254-019-0127-2

  56. [56]

    2014a, Nature, 509, 177, doi: 10.1038/nature13316 —

    Vogelsberger, M., Genel, S., Springel, V., et al. 2014a, Nature, 509, 177, doi: 10.1038/nature13316 —. 2014b, MNRAS, 444, 1518, doi: 10.1093/mnras/stu1536

  57. [57]

    D., Li, J., Jiang, X., & Fang, T

    Wang, Q. D., Li, J., Jiang, X., & Fang, T. 2016, MNRAS, 457, 1385, doi: 10.1093/mnras/stv2886

  58. [58]

    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

  59. [59]

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

  60. [60]

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

  61. [61]

    Y., et al

    Yoshino, T., Mitsuda, K., Yamasaki, N. Y., et al. 2009, PASJ, 61, 805, doi: 10.1093/pasj/61.4.805

  62. [62]

    2010, ApJ, 717, 74, doi: 10.1088/0004-637X/717/1/74

    Zappacosta, L., Nicastro, F., Maiolino, R., et al. 2010, ApJ, 717, 74, doi: 10.1088/0004-637X/717/1/74

  63. [63]

    2024, 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 —. 2025a, A&A, 693, A197, doi: 10.1051/0004-6361/202452273

  64. [64]

    2024b, ApJ, 962, 15, doi: 10.3847/1538-4357/ad10a4 —

    Zhang, Z., Zhang, X., Li, H., et al. 2024b, ApJ, 962, 15, doi: 10.3847/1538-4357/ad10a4 —. 2025b, ApJ, 991, 170, doi: 10.3847/1538-4357/ae019f

  65. [65]

    S., O’Shea, B

    Zheng, Y., Peeples, M. S., O’Shea, B. W., et al. 2020, ApJ, 896, 143, doi: 10.3847/1538-4357/ab960a