REVIEW 3 major objections 2 minor 99 references
The Thermodynamic and Kinematic Evolution of Circumgalactic Gas around $z=1$ in the IllustrisTNG model
T0 review · 3 major / 2 minor · reviewed 2026-05-08 · grok-4.3
Pith's one-line read Circumgalactic gas evolves into distinct cold and warm-hot phases within 500 million years regardless of initial position.
desk verdict TNG tracer study gives 500 Myr CGM phase separation and 400 Myr kinematic decorrelation at z=1, but the numbers are set by the simulation's subgrid feedback and mixing. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
Monte Carlo tracer particles that follow the gas parcels in a Lagrangian manner to record changes in their temperature, density, and velocity over time.
What would settle it
Observations that find kinematic properties of circumgalactic gas remain correlated with their starting conditions for much longer than 400 million years, or that show no clear separation into cold inner and warm-hot outer phases, would falsify the central result.
Extended reading notes
Core claim
Gas in the circumgalactic medium mixes between different temperature and density phases quickly and within approximately 500 million years evolves into distinct cold (around 10,000 K) and warm-hot (around 300,000 K) phases at small and large distances from the galaxy, respectively, regardless of its initial distance from the galaxy center. This is largely driven by feedback from the galaxy, which heats and ejects cold gas that had previously cooled and accreted toward and occasionally into the galaxy from the outer regions.
Load-bearing premise
The simulation's treatment of gas cooling, mixing, and feedback from the galaxy accurately reflects real physical processes.
Editorial extensions
If this is right
- Autocorrelations of kinematic quantities take approximately 400 million years to fully decorrelate from initial values.
- Gas associated with O VI remains in its narrow temperature-density range hundreds of millions of years longer than gas associated with Mg II or C IV.
- Observations of different ions can therefore sample circumgalactic gas at different points in its evolutionary cycle even when the gas occupies the same location.
Reading between the lines
- Surveys that measure multiple ions at once may be able to separate recently processed gas from older gas in the same halo.
- Galaxy formation models will need to incorporate this rapid phase separation when calculating how much fresh gas reaches the central galaxy.
- The fact that final phase depends little on starting radius suggests feedback mixes the entire circumgalactic region on timescales shorter than a typical orbital period.
Signed reviews
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript analyzes the short-timescale thermodynamic and kinematic evolution of CGM gas at z=1 using Monte Carlo tracer particles in a high-cadence (~2 Myr) subregion of the TNG100 simulation. It follows gas around six galaxies in 10^{11.5}-10^{12} M_⊙ halos and reports that, independent of initial halo-centric radius, the gas mixes rapidly and separates within ~500 Myr into cold (T≈10^4 K) phases at small radii and warm-hot (T≈10^{5.5} K) phases at large radii, driven by galactic feedback that heats and ejects previously accreted cold gas. Kinematic autocorrelations decorrelate on ~400 Myr timescales, and ion-associated phases (O VI-like) persist longer than Mg II-like or C IV-like phases.
Significance. If the central results hold, the work is significant for constraining the multiphase structure and dynamical processing of the CGM on observationally relevant timescales. The Lagrangian high-cadence tracer approach is a strength, enabling direct measurement of mixing, ejection, and phase persistence without circularity in the reported quantities. The finding that different ions probe distinct evolutionary states even when cospatial has direct implications for absorption-line studies.
major comments (3)
- [Methods and Results] The central claim that CGM gas reaches distinct cold/warm-hot phases within ≈500 Myr independent of initial radius rests on the specific subgrid cooling, star formation, wind, and AGN prescriptions plus the Monte Carlo tracer advection in TNG. No resolution variations, feedback-parameter sweeps, or tracer-convergence tests at the ~2 Myr cadence are reported, so it is unclear whether the decorrelation and phase-separation timescales are robust or set by numerical mixing and wind-launching efficiency.
- [Results] The sample comprises only six galaxies in a narrow halo-mass range (10^{11.5}-10^{12} M_⊙). The assertion that the radial phase separation occurs 'regardless of its initial (z=1) halo-centric radius' therefore lacks statistical power; a larger sample or explicit variation across halo mass and environment is needed to support the generality of the result within the model.
- [Results] The phase definitions (cold T≈10^4 K, warm-hot T≈10^{5.5} K, and narrow bins for O VI-, Mg II-, and C IV-like gas) are load-bearing for the ion-persistence and mixing claims, yet no sensitivity tests to bin boundaries or to the precise temperature-density cuts are provided.
minor comments (2)
- [Abstract and Results] The abstract states that autocorrelations 'take ≈400 Myr to fully decorrelate,' but the precise definition of 'fully decorrelate' (e.g., dropping below a threshold or reaching noise level) and the exact kinematic quantities used should be stated explicitly in the main text.
- [Figures] Figure captions and axis labels for the autocorrelation functions and phase-evolution plots should include the number of tracer particles per galaxy and the precise time sampling to allow readers to assess numerical robustness.
Simulated Author's Rebuttal
We thank the referee for their positive evaluation of the work's significance and the Lagrangian tracer approach. We address each major comment below with clarifications and indicate revisions to the manuscript where they strengthen the presentation without altering the core findings.
read point-by-point responses
-
Referee: [Methods and Results] The central claim that CGM gas reaches distinct cold/warm-hot phases within ≈500 Myr independent of initial radius rests on the specific subgrid cooling, star formation, wind, and AGN prescriptions plus the Monte Carlo tracer advection in TNG. No resolution variations, feedback-parameter sweeps, or tracer-convergence tests at the ~2 Myr cadence are reported, so it is unclear whether the decorrelation and phase-separation timescales are robust or set by numerical mixing and wind-launching efficiency.
Authors: We agree that the reported timescales are specific to the IllustrisTNG subgrid model and the Monte Carlo tracer implementation in the high-cadence TNG100 subregion. The ~2 Myr cadence was selected to resolve short-term evolution while the tracer particles minimize artificial mixing compared to Eulerian methods. Explicit resolution or feedback-parameter variations were not performed because the study utilizes an existing high-output-frequency subregion rather than new runs. In the revised manuscript we will add an expanded discussion of model limitations, potential numerical influences on mixing rates, and the fact that the results characterize behavior within this widely used simulation framework. revision: partial
-
Referee: [Results] The sample comprises only six galaxies in a narrow halo-mass range (10^{11.5}-10^{12} M_⊙). The assertion that the radial phase separation occurs 'regardless of its initial (z=1) halo-centric radius' therefore lacks statistical power; a larger sample or explicit variation across halo mass and environment is needed to support the generality of the result within the model.
Authors: The sample of six galaxies in the stated mass range is indeed limited and was chosen to permit the computationally expensive high time cadence required for Lagrangian tracking of individual gas parcels. The statement that phase separation occurs independent of initial radius refers to the consistent behavior seen across the tracked particles in these systems. We will revise the text to qualify this claim explicitly as applying to the galaxies studied here, to avoid implying broader statistical generality, and to note that extending the sample would require additional high-cadence simulation outputs. revision: yes
-
Referee: [Results] The phase definitions (cold T≈10^4 K, warm-hot T≈10^{5.5} K, and narrow bins for O VI-, Mg II-, and C IV-like gas) are load-bearing for the ion-persistence and mixing claims, yet no sensitivity tests to bin boundaries or to the precise temperature-density cuts are provided.
Authors: The temperature and density ranges follow standard literature conventions for multiphase CGM gas and common ions. While we did not include explicit sensitivity tests in the original analysis, the main conclusions on rapid mixing and differential ion-phase lifetimes arise from the overall thermodynamic trajectories rather than the precise edges of the bins. In the revised manuscript we will add a short justification of the adopted cuts together with a brief demonstration that the reported timescales are insensitive to modest shifts in the boundaries. revision: partial
Circularity Check
No circularity: all results are direct measurements from simulation snapshots and tracer histories
full rationale
The paper analyzes CGM gas evolution by following Monte Carlo tracers forward in time within the existing TNG100 simulation at ~2 Myr cadence. Reported quantities (phase separation into cold/warm-hot components within ~500 Myr independent of initial radius, kinematic autocorrelation decorrelation on ~400 Myr, ion-specific phase persistence times) are computed directly from the snapshot data and tracer particle histories. No equations, fitted parameters, or self-citations are used to define or predict these outputs in terms of themselves; the analysis contains no self-definitional steps, no 'predictions' that reduce to input fits, and no load-bearing uniqueness theorems or ansatzes imported from prior author work. The central claims are empirical measurements within the model, not tautological derivations.
Assumptions & free parameters
free parameters (2)
- halo mass range
- time cadence =
2 Myr
assumptions (1)
- domain assumption IllustrisTNG subgrid physics and numerical resolution sufficiently capture CGM mixing, cooling, and feedback on Myr timescales
Cite this review
Pith. "Pith review of The Thermodynamic and Kinematic Evolution of Circumgalactic Gas around $z=1$ in the IllustrisTNG model." pith.science (2026). https://pith.science/paper/2604.24836
@misc{pith2026260424836,
author = {Pith},
title = {Pith review of: The Thermodynamic and Kinematic Evolution of Circumgalactic Gas around $z=1$ in the IllustrisTNG model},
year = {2026},
howpublished = {\url{https://pith.science/paper/2604.24836}},
note = {Machine review of arXiv:2604.24836}
}
abstract
The circumgalactic medium (CGM) is known to contain multiphase gas in various stages of evolution and interaction with the galaxy. In order to characterize its detailed behavior on short timescales, we use a subregion of the TNG100 cosmological simulation to study the evolution of the $z=1$ CGM around six galaxies in $10^{11.5}-10^{12}$ $M_{\odot}$ halos at a high time cadence of $\approx2$ Myr. We use Monte Carlo tracer particles to follow this CGM gas forward in time in a Lagrangian way and determine how its thermodynamic and kinematic properties change. We find that CGM gas mixes between different temperature and density phases quickly and within $\approx500$ Myr evolves into distinct cold ($T\approx10^4$ $\rm{K}$) and warm-hot ($T\approx10^{5.5}$ $\rm{K}$) phases at small and large distances from the galaxy, respectively, regardless of its initial ($z=1$) halo-centric radius. This is largely driven by feedback from the galaxy, which heats and ejects cold gas that had previously cooled and accreted toward and occasionally into the galaxy from the outer CGM. We see signatures of this process in autocorrelations of kinematic quantities, which take $\approx400$ Myr to fully decorrelate from their initial values, suggesting a timescale over which feedback disrupts and reprocesses CGM gas. We also examine gas in narrow temperature and density ranges associated with commonly observed ions and find that gas that is O VI-like stays in its phase for hundreds of Myr longer than gas that is Mg II-like or C IV-like, suggesting that CGM observations of different species could probe gas in different evolutionary states, even if the gas is cospatial.
Figures
Figures from the paper (8 more)
Reference graph
Works this paper leans on
-
[1]
Anand, A., Nelson, D., & Kauffmann, G. 2021, MNRAS, 504, 65, doi: 10.1093/mnras/stab871
-
[2]
2016, MNRAS, 462, 4157, doi: 10.1093/mnras/stw1930 Astropy Collaboration, Robitaille, T
Armillotta, L., Fraternali, F., & Marinacci, F. 2016, MNRAS, 462, 4157, doi: 10.1093/mnras/stw1930
-
[3]
Barbani, F., Pascale, R., Marinacci, F., et al. 2023, MNRAS, 524, 4091, doi: 10.1093/mnras/stad2152
-
[4]
S., Sharma P., Dutta A., Nath B
Bisht, M. S., Sharma, P., Dutta, A., & Nath, B. B. 2025, MNRAS, 542, 1573, doi: 10.1093/mnras/staf1319 Bouch´ e, N., Hohensee, W., Vargas, R., et al. 2012, MNRAS, 426, 801, doi: 10.1111/j.1365-2966.2012.21114.x Bouch´ e, N. F., Wendt, M., Zabl, J., et al. 2025, A&A, 694, A67, doi: 10.1051/0004-6361/202451093
-
[5]
Statistical Properties of X‐Ray Clusters: Analytic and Numerical Comparisons
Bryan, G. L., & Norman, M. L. 1998, ApJ, 495, 80, doi: 10.1086/305262
-
[6]
Wind from a starburst galaxy nucleus
Chevalier, R. A., & Clegg, A. W. 1985, Nature, 317, 44, doi: 10.1038/317044a0
-
[7]
P., Sharma , P., & Quataert , E
Choudhury, P. P., Sharma, P., & Quataert, E. 2019, MNRAS, 488, 3195, doi: 10.1093/mnras/stz1857
-
[8]
Cooper, T. J., Rudie, G. C., Chen, H.-W., et al. 2021, MNRAS, 508, 4359, doi: 10.1093/mnras/stab2869
Show all 99 references
-
[9]
2021, ApJ, 918, 83, doi: 10.3847/1538-4357/ac0e8e
Das, S., Mathur, S., Gupta, A., & Krongold, Y. 2021, ApJ, 918, 83, doi: 10.3847/1538-4357/ac0e8e
2021 doi
-
[10]
2019, ApJL, 882, L23, doi: 10.3847/2041-8213/ab3b09 Dav´ e, R., Angl´ es-Alc´ azar, D., Narayanan, D., et al
Das, S., Mathur, S., Nicastro, F., & Krongold, Y. 2019, ApJL, 882, L23, doi: 10.3847/2041-8213/ab3b09 Dav´ e, R., Angl´ es-Alc´ azar, D., Narayanan, D., et al. 2019, MNRAS, 486, 2827, doi: 10.1093/mnras/stz937
2019 doi
-
[11]
F., Genel, S., et al
DeFelippis, D., Bouch´ e, N. F., Genel, S., et al. 2021, ApJ, 923, 56, doi: 10.3847/1538-4357/ac2cbf
2021 doi
-
[12]
L., & Fall, S
DeFelippis, D., Genel, S., Bryan, G. L., & Fall, S. M. 2017, ApJ, 841, 16, doi: 10.3847/1538-4357/aa6dfc
2017 doi
-
[13]
L., et al
DeFelippis, D., Genel, S., Bryan, G. L., et al. 2020, ApJ, 895, 17, doi: 10.3847/1538-4357/ab8a4a 20
2020 doi
-
[14]
S., Sharma, P., et al
Dutta, A., Bisht, M. S., Sharma, P., et al. 2024, MNRAS, 531, 5117, doi: 10.1093/mnras/stae977
2024 doi
-
[15]
2022, MNRAS, 510, 3561, doi: 10.1093/mnras/stab3653
Dutta, A., Sharma, P., & Nelson, D. 2022, MNRAS, 510, 3561, doi: 10.1093/mnras/stab3653
2022 doi
-
[16]
2020, MNRAS, 499, 5022, doi: 10.1093/mnras/staa3147
Dutta, R., Fumagalli, M., Fossati, M., et al. 2020, MNRAS, 499, 5022, doi: 10.1093/mnras/staa3147
2020 doi
-
[17]
Faerman, Y., Sternberg, A., & McKee, C. F. 2017, ApJ, 835, 52, doi: 10.3847/1538-4357/835/1/52 —. 2020, ApJ, 893, 82, doi: 10.3847/1538-4357/ab7ffc Faucher-Gigu` ere, C.-A., & Oh, S. P. 2023, ARA&A, 61, 131, doi: 10.1146/annurev-astro-052920-125203
2017 doi
-
[18]
2017a, MNRAS, 470, L39, doi: 10.1093/mnrasl/slx072
Fielding, D., Quataert, E., Martizzi, D., & Faucher-Gigu` ere, C.-A. 2017a, MNRAS, 470, L39, doi: 10.1093/mnrasl/slx072
-
[19]
Fielding, D., Quataert, E., McCourt, M., & Thompson, T. A. 2017b, MNRAS, 466, 3810, doi: 10.1093/mnras/stw3326
-
[20]
B., & Bryan, G
Fielding, D. B., & Bryan, G. L. 2022, ApJ, 924, 82, doi: 10.3847/1538-4357/ac2f41
2022 doi
-
[21]
B., Tonnesen, S., DeFelippis, D., et al
Fielding, D. B., Tonnesen, S., DeFelippis, D., et al. 2020, ApJ, 903, 32, doi: 10.3847/1538-4357/abbc6d
2020 doi
-
[22]
C., Emami, R., Somerville, R
Forbes, J. C., Emami, R., Somerville, R. S., et al. 2023, ApJ, 948, 107, doi: 10.3847/1538-4357/acb53e
2023 doi
-
[23]
2013, MNRAS, 435, 1426, doi: 10.1093/mnras/stt1383
Genel, S., Vogelsberger, M., Nelson, D., et al. 2013, MNRAS, 435, 1426, doi: 10.1093/mnras/stt1383
2013 doi
-
[24]
2024, MNRAS, 531, 3445, doi: 10.1093/mnras/stae1345
Ghosh, R., Dutta, A., & Sharma, P. 2024, MNRAS, 531, 3445, doi: 10.1093/mnras/stae1345
2024 doi
-
[25]
Grand, R. J. J., van de Voort, F., Zjupa, J., et al. 2019, MNRAS, 490, 4786, doi: 10.1093/mnras/stz2928
2019 doi
-
[26]
Gronke, M., & Oh, S. P. 2018, MNRAS, 480, L111, doi: 10.1093/mnrasl/sly131
2018 doi
-
[27]
2020, MNRAS, 494, 3581, doi: 10.1093/mnras/staa902
Hafen, Z., Faucher-Gigu` ere, C.-A., Angl´ es-Alc´ azar, D., et al. 2020, MNRAS, 494, 3581, doi: 10.1093/mnras/staa902
2020 doi
-
[28]
H., Martin, C
Ho, S. H., Martin, C. L., Kacprzak, G. G., & Churchill, C. W. 2017, ApJ, 835, 267, doi: 10.3847/1538-4357/835/2/267
2017 doi
-
[29]
H., Martin, C
Ho, S. H., Martin, C. L., & Turner, M. L. 2019, ApJ, 875, 54, doi: 10.3847/1538-4357/ab0ec2
2019 doi
-
[30]
J., Miller, M
Hodges-Kluck, E. J., Miller, M. J., & Bregman, J. N. 2016, ApJ, 822, 21, doi: 10.3847/0004-637X/822/1/21
2016 doi
-
[31]
2022, MNRAS, 509, 6091, doi: 10.1093/mnras/stab3363
Huang, S., Katz, N., Cottle, J., et al. 2022, MNRAS, 509, 6091, doi: 10.1093/mnras/stab3363
2022 doi
-
[32]
Fielding, D. B. 2024, ApJ, 972, 148, doi: 10.3847/1538-4357/ad5965
2024 doi
-
[33]
B., Smith, B
Hummels, C. B., Smith, B. D., Hopkins, P. F., et al. 2019, ApJ, 882, 156, doi: 10.3847/1538-4357/ab378f
2019 doi
-
[34]
Hunter, J. D. 2007, Computing in Science Engineering, 9, 90, doi: 10.1109/MCSE.2007.55
2007 doi
-
[35]
P., & Masterson, P
Ji, S., Oh, S. P., & Masterson, P. 2019, MNRAS, 487, 737, doi: 10.1093/mnras/stz1248
2019 doi
-
[36]
W., Kruijssen, J
Keller, B. W., Kruijssen, J. M. D., & Wadsley, J. W. 2020, MNRAS, 493, 2149, doi: 10.1093/mnras/staa380
2020 doi
-
[37]
J., Jenkins, A., Deason, A., et al
Kelly, A. J., Jenkins, A., Deason, A., et al. 2022, MNRAS, 514, 3113, doi: 10.1093/mnras/stac1019
2022 doi
-
[38]
Kim, C.-G., Kim, J.-G., Gong, M., & Ostriker, E. C. 2023, ApJ, 946, 3, doi: 10.3847/1538-4357/acbd3a
2023 doi
-
[39]
Kwak, K., & Shelton, R. L. 2010, ApJ, 719, 523, doi: 10.1088/0004-637X/719/1/523
2010 doi
-
[40]
2020, ApJ, 897, 97, doi: 10.3847/1538-4357/ab989a
Lan, T.-W. 2020, ApJ, 897, 97, doi: 10.3847/1538-4357/ab989a
2020 doi
-
[41]
J., & Remming, I
Liang, C. J., & Remming, I. 2020, MNRAS, 491, 5056, doi: 10.1093/mnras/stz3403
2020 doi
-
[42]
L., Li, Y., Li, M., & Fielding, D
Lochhaas, C., Bryan, G. L., Li, Y., Li, M., & Fielding, D. 2020, MNRAS, 493, 1461, doi: 10.1093/mnras/staa358
2020 doi
-
[43]
S., et al
Lochhaas, C., Tumlinson, J., Peeples, M. S., et al. 2023, ApJ, 948, 43, doi: 10.3847/1538-4357/acbb06
2023 doi
-
[44]
2010, MNRAS, 404, 1464, doi: 10.1111/j.1365-2966.2010.16352.x
Marinacci, F., Binney, J., Fraternali, F., et al. 2010, MNRAS, 404, 1464, doi: 10.1111/j.1365-2966.2010.16352.x
2010 doi
-
[45]
2011, MNRAS, 415, 1534, doi: 10.1111/j.1365-2966.2011.18810.x
Marinacci, F., Fraternali, F., Nipoti, C., et al. 2011, MNRAS, 415, 1534, doi: 10.1111/j.1365-2966.2011.18810.x
2011 doi
-
[46]
2019, MNRAS, 489, 4233, doi: 10.1093/mnras/stz2391
Springel, V. 2019, MNRAS, 489, 4233, doi: 10.1093/mnras/stz2391
2019 doi
-
[47]
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
2018 doi
-
[48]
2024, MNRAS, 527, 5093, doi: 10.1093/mnras/stad3497
Gupta, A. 2024, MNRAS, 527, 5093, doi: 10.1093/mnras/stad3497
2024 doi
-
[49]
McCourt, M., Sharma, P., Quataert, E., & Parrish, I. J. 2012, MNRAS, 419, 3319, doi: 10.1111/j.1365-2966.2011.19972.x
2012 doi
-
[50]
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
2018 doi
-
[51]
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
2018 doi
-
[52]
2020, MNRAS, 498, 2391, doi: 10.1093/mnras/staa2419
Nelson, D., Sharma, P., Pillepich, A., et al. 2020, MNRAS, 498, 2391, doi: 10.1093/mnras/staa2419
2020 doi
-
[53]
M., Churchill, C
Nielsen, N. M., Churchill, C. W., & Kacprzak, G. G. 2013a, ApJ, 776, 115, doi: 10.1088/0004-637X/776/2/115
-
[54]
Murphy, M. T. 2013b, ApJ, 776, 114, doi: 10.1088/0004-637X/776/2/114
-
[55]
M., Churchill, C
Nielsen, N. M., Churchill, C. W., Kacprzak, G. G., Murphy, M. T., & Evans, J. L. 2015, ApJ, 812, 83, doi: 10.1088/0004-637X/812/1/83 21
2015 doi
-
[56]
Oppenheimer, B. D. 2018, MNRAS, 480, 2963, doi: 10.1093/mnras/sty1918
2018 doi
-
[57]
D., Segers, M., Schaye, J., Richings, A
Oppenheimer, B. D., Segers, M., Schaye, J., Richings, A. J., & Crain, R. A. 2018, MNRAS, 474, 4740, doi: 10.1093/mnras/stx2967
2018 doi
-
[58]
B., Bryan, G
Pandya, V., Fielding, D. B., Bryan, G. L., et al. 2023, ApJ, 956, 118, doi: 10.3847/1538-4357/acf3ea
2023 doi
-
[59]
S., Corlies, L., Tumlinson, J., et al
Peeples, M. S., Corlies, L., Tumlinson, J., et al. 2019, ApJ, 873, 129, doi: 10.3847/1538-4357/ab0654
2019 doi
-
[60]
Perez, F., & Granger, B. E. 2007, Computing in Science Engineering, 9, 21, doi: 10.1109/MCSE.2007.53 P´ eroux, C., Nelson, D., van de Voort, F., et al. 2020, MNRAS, 499, 2462, doi: 10.1093/mnras/staa2888
2007 doi
-
[61]
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
-
[62]
2018b, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656 Planck Collaboration, Ade, P
Pillepich, A., Springel, V., Nelson, D., et al. 2018b, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830
2016 doi
-
[63]
2015, ApJ, 811, 108, doi: 10.1088/0004-637X/811/2/108
Prasad, D., Sharma, P., & Babul, A. 2015, ApJ, 811, 108, doi: 10.1088/0004-637X/811/2/108
2015 doi
-
[64]
C., et al
Qu, Z., Chen, H.-W., Rudie, G. C., et al. 2022, MNRAS, 516, 4882, doi: 10.1093/mnras/stac2528 —. 2023, MNRAS, 524, 512, doi: 10.1093/mnras/stad1886
2022 doi
-
[65]
2024, MNRAS, 528, 3320, doi: 10.1093/mnras/stae237
Ramesh, R., & Nelson, D. 2024, MNRAS, 528, 3320, doi: 10.1093/mnras/stae237
2024 doi
-
[66]
2026, arXiv e-prints, arXiv:2602.23416, doi: 10.48550/arXiv.2602.23416
Ramesh, R., Nelson, D., Fielding, D., & Br¨ uggen, M. 2026, arXiv e-prints, arXiv:2602.23416, doi: 10.48550/arXiv.2602.23416
2026 doi
-
[67]
2023, MNRAS, 522, 1843, doi: 10.1093/mnras/stad1104
Rathjen, T.-E., Naab, T., Walch, S., et al. 2023, MNRAS, 522, 1843, doi: 10.1093/mnras/stad1104
2023 doi
-
[68]
C., Steidel, C
Rudie, G. C., Steidel, C. C., Trainor, R. F., et al. 2012, ApJ, 750, 67, doi: 10.1088/0004-637X/750/1/67
2012 doi
-
[69]
C., Nath, B
Sarkar, K. C., Nath, B. B., Sharma, P., & Shchekinov, Y. 2015, MNRAS, 448, 328, doi: 10.1093/mnras/stu2760
2015 doi
-
[70]
A., Bower, R
Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521, doi: 10.1093/mnras/stu2058
2015 doi
-
[71]
E., & Mao, S
Schneider, E. E., & Mao, S. A. 2024, ApJ, 966, 37, doi: 10.3847/1538-4357/ad2e8a
2024 doi
-
[72]
E., & Robertson, B
Schneider, E. E., & Robertson, B. E. 2018, ApJ, 860, 135, doi: 10.3847/1538-4357/aac329
2018 doi
-
[73]
F., Zabl, J., et al
Schroetter, I., Bouch´ e, N. F., Zabl, J., et al. 2021, MNRAS, 506, 1355, doi: 10.1093/mnras/stab1447
2021 doi
-
[74]
2025, MNRAS, 541, 2471, doi: 10.1093/mnras/staf1066
Shah, H., van de Voort, F., Seta, A., & Federrath, C. 2025, MNRAS, 541, 2471, doi: 10.1093/mnras/staf1066
2025 doi
-
[75]
J., & Quataert, E
Sharma, P., McCourt, M., Parrish, I. J., & Quataert, E. 2012, MNRAS, 427, 1219, doi: 10.1111/j.1365-2966.2012.22050.x
2012 doi
-
[76]
2019, MNRAS, 484, 2632, doi: 10.1093/mnras/stz098
Shimizu, I., Todoroki, K., Yajima, H., & Nagamine, K. 2019, MNRAS, 484, 2632, doi: 10.1093/mnras/stz098
2019 doi
-
[77]
C., Fielding, D
Smith, M. C., Fielding, D. B., Bryan, G. L., et al. 2024, MNRAS, 527, 1216, doi: 10.1093/mnras/stad3168
2024 doi
-
[78]
Sobacchi, E., & Sormani, M. C. 2019, MNRAS, 486, 205, doi: 10.1093/mnras/stz792
2019 doi
-
[79]
Klessen, R. S. 2018, MNRAS, 481, 3370, doi: 10.1093/mnras/sty2500
2018 doi
-
[80]
2024, A&A, 691, A259, doi: 10.1051/0004-6361/202450544
Sparre, M., Pfrommer, C., & Puchwein, E. 2024, A&A, 691, A259, doi: 10.1051/0004-6361/202450544
2024 doi
-
[81]
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
2010 doi
-
[82]
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
2003 doi
-
[83]
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
2018 doi
-
[84]
2024, MNRAS, 530, 1711, doi: 10.1093/mnras/stae824
Stern, J., Fielding, D., Hafen, Z., et al. 2024, MNRAS, 530, 1711, doi: 10.1093/mnras/stae824
2024 doi
-
[85]
R., et al
Strawn, C., Roca-F` abrega, S., Primack, J. R., et al. 2024, ApJ, 962, 29, doi: 10.3847/1538-4357/ad12cb
2024 doi
-
[86]
2019, MNRAS, 483, 4040, doi: 10.1093/mnras/sty3402
Hernquist, L. 2019, MNRAS, 483, 4040, doi: 10.1093/mnras/sty3402
2019 doi
-
[87]
K., Wilde, M
Tchernyshyov, K., Werk, J. K., Wilde, M. C., et al. 2023, ApJ, 949, 41, doi: 10.3847/1538-4357/acc86a
2023 doi
-
[88]
A., Bell, E
Terrazas, B. A., Bell, E. F., Pillepich, A., et al. 2020, MNRAS, 493, 1888, doi: 10.1093/mnras/staa374
2020 doi
-
[89]
A., Quataert, E., Zhang, D., & Weinberg, D
Thompson, T. A., Quataert, E., Zhang, D., & Weinberg, D. H. 2016, MNRAS, 455, 1830, doi: 10.1093/mnras/stv2428
2016 doi
-
[90]
S., & Werk, J
Tumlinson, J., Peeples, M. S., & Werk, J. K. 2017, ARA&A, 55, 389, doi: 10.1146/annurev-astro-091916-055240 ¨Ubler, H., Naab, T., Oser, L., et al. 2014, MNRAS, 443, 2092, doi: 10.1093/mnras/stu1275 van der Walt, S., Colbert, S. C., & Varoquaux, G. 2011, Computing in Science En...
2017 doi
-
[91]
R., & Wibking, B
Vijayan, A., Krumholz, M. R., & Wibking, B. D. 2024, MNRAS, 527, 10095, doi: 10.1093/mnras/stad3816 —. 2025, MNRAS, 539, 1706, doi: 10.1093/mnras/staf136
2024 doi
-
[92]
M., Meece, G., Li, Y., et al
Voit, G. M., Meece, G., Li, Y., et al. 2017, ApJ, 845, 80, doi: 10.3847/1538-4357/aa7d04
2017 doi
-
[93]
M., Pandya, V., Fielding, D
Voit, G. M., Pandya, V., Fielding, D. B., et al. 2024, ApJ, 976, 150, doi: 10.3847/1538-4357/ad81d6
2024 doi
-
[94]
2015, MNRAS, 454, 238, doi: 10.1093/mnras/stv1975
Walch, S., Girichidis, P., Naab, T., et al. 2015, MNRAS, 454, 238, doi: 10.1093/mnras/stv1975
2015 doi
-
[95]
2020, ApJS, 248, 32, doi: 10.3847/1538-4365/ab908c
Weinberger, R., Springel, V., & Pakmor, R. 2020, ApJS, 248, 32, doi: 10.3847/1538-4365/ab908c
2020 doi
-
[96]
2017, MNRAS, 465, 3291, doi: 10.1093/mnras/stw2944 22
Weinberger, R., Springel, V., Hernquist, L., et al. 2017, MNRAS, 465, 3291, doi: 10.1093/mnras/stw2944 22
2017 doi
-
[97]
K., Prochaska, J
Werk, J. K., Prochaska, J. X., Tumlinson, J., et al. 2014, ApJ, 792, 8, doi: 10.1088/0004-637X/792/1/8
2014 doi
-
[98]
K., Prochaska, J
Werk, J. K., Prochaska, J. X., Cantalupo, S., et al. 2016, ApJ, 833, 54, doi: 10.3847/1538-4357/833/1/54
2016 doi
-
[99]
F., Schroetter, I., et al
Zabl, J., Bouch´ e, N. F., Schroetter, I., et al. 2019, MNRAS, 485, 1961, doi: 10.1093/mnras/stz392
2019 doi
Reviewed May 8, 2026 · model on record in the stance chip above.
Discussion (0). Continue with ORCID to comment.