REVIEW 4 major objections 4 minor 3 cited by
How Dust Models Shape High-z Galaxy Morphology: Insights from the NewCluster Simulation
T0 review · 4 major / 4 minor · reviewed 2026-08-05 · deepseek-v4-flash
Pith's one-line read A fixed dust ratio biases how simulated galaxies appear at high redshift
desk verdict Well-controlled OTF-vs-fixed dust comparison shows dust treatment biases morphological classifications at high z, but the physical verdict rests on subgrid recipes we can't audit in the abstract. 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
The DTM cavity: a localized depression in the dust-to-metal ratio in galaxy centers caused by intense bulge starbursts, which in the on-the-fly dust model reduces central dust attenuation and brightens the bulge relative to fixed-ratio models. The comparison is carried out with radiative transfer code SKIRT to make mock JWST images, followed by G-M20 morphology classification.
What would settle it
Resolved dust-to-metal ratio or attenuation maps of high-redshift star-forming bulges, from ALMA dust continuum or JWST NIRCam/MIRI observations, could settle it: if the centers of starbursting galaxies show no depression in dust-to-metal ratio relative to their disks, the DTM cavity predicted by the on-the-fly model is not present in real galaxies. A simpler internal check is to rerun the mock images with the dust opacity law or destruction efficiency varied and see whether the late-type fraction shift disappears.
Extended reading notes
Core claim
The central claim is that adopting a fixed dust-to-metal ratio in post-processing changes the apparent morphology of simulated galaxies enough to alter their classification. In NewCluster, the physically evolved dust distribution leaves central regions less dusty relative to metals after bulge starbursts, so stellar light at the center is less attenuated; the same galaxies rendered with a fixed DTM show fainter centers and look more like disks. The G-M20 morphology test then assigns a lower late-type galaxy fraction to the on-the-fly sample, with the difference strongest at high redshift. The paper interprets this as evidence that fixed DTM models fail to capture a key morphological feature.
Load-bearing premise
The on-the-fly dust model's subgrid recipes for dust formation, destruction, and grain opacity accurately represent real dust in starbursting bulges; if these recipes destroy or fail to re-form dust too aggressively, the DTM cavity and the resulting central brightening are artifacts of the model rather than a real feature of galaxies.
Editorial extensions
If this is right
- Mock JWST images from simulations that assume a fixed dust-to-metal ratio will systematically classify high-redshift galaxies as later types than they are.
- The late-type fraction measured in simulations depends on dust modeling choices, not only on star formation and feedback physics.
- Dust evolution needs to be included when rendering simulated galaxies, not only in the hydrodynamic run, to compare morphology with observations.
- The DTM cavity predicts that bulge regions of high-redshift starbursting galaxies should show measurably lower dust-to-metal ratios than their disks.
- At higher redshift, where starbursts are more frequent, the morphology bias from fixed dust ratios should grow.
Reading between the lines
- A natural next step is to test the DTM cavity directly with resolved dust or attenuation observations of high-redshift bulges; a clean detection would support the mechanism, while a flat dust-to-metal ratio in starburst centers would challenge it.
- Re-deriving dust-to-metal ratios from metal maps in older fixed-ratio simulations may recover some of the missing central brightening without rerunning the hydrodynamics.
- If the effect is general, it could also affect observables that depend on central attenuation, such as half-light radii, color gradients, or SED-derived stellar masses, though the paper does not test these.
- The bias may be redshift-dependent in a predictable way, allowing observers to use morphology samples to constrain dust evolution timescales.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper asks whether the choice of dust model changes the apparent morphology of high-redshift galaxies in mock JWST images. Using the NewCluster simulation, the authors post-process the same galaxies with an on-the-fly (OTF) dust model and with a fixed dust-to-metal (DTM) ratio, run SKIRT radiative transfer, and apply the G-M20 morphological classification. They report that OTF models produce brighter centers and more pronounced bulges, lowering the late-type galaxy (LTG) fraction especially at high redshift, and attribute this to a 'DTM cavity'—a localized depression in the dust-to-metal ratio in starbursting bulges. They conclude that fixed-DTM models fail to capture key morphological features. The abstract is clear and the differential design is a strength, but the supplied full text is almost entirely garbled and unreadable, including an embedded reference to an unrelated arXiv paper. Consequently, the derivations, figures, tables, and quantitative results could not be independently checked.
Significance. If the result holds, it is significant: it would demonstrate that dust-evolution subgrid physics changes morphological classifications in a way that matters for JWST-based high-z studies, and it would identify a systematic bias in fixed-DTM mock observations. The internal differential comparison (same galaxies, two dust treatments) is well posed, and the use of SKIRT with a JWST comparison sample is appropriate. However, the interpretation that fixed-DTM models 'fail' depends on the OTF dust recipes faithfully representing dust in starbursting bulges. Because the supplied text is unreadable, the calibration and sensitivity of those recipes cannot be evaluated; this is the main barrier to accepting the paper's central claim.
major comments (4)
- [Full text (passim)] The supplied full text is largely illegible mojibake; equations, figures, and tables cannot be read. An unrelated identifier, 'arXiv:2508.18373v1 [cond-mat.str-el]', appears embedded mid-manuscript, indicating contamination. This is not a trivial typo: it prevents verification of every quantitative claim in the paper. A clean manuscript must be provided before any scientific assessment can be made.
- [Abstract (last sentence)] The statement that 'fixed DTM models fail to capture key morphological features' is stronger than the evidence described. The paper compares one OTF implementation against one fixed-DTM prescription. Without sensitivity tests varying the dust formation/destruction efficiencies and timescales, the failure could be specific to NewCluster's subgrid parameters. The abstract reports no such tests. Please either add robustness tests or soften the claim to state that fixed-DTM models can differ substantially from OTF models.
- [Abstract ('DTM cavity')] The DTM cavity is introduced as the physical mechanism, but the abstract provides no quantitative information (depth, radial extent, redshift dependence) and no direct comparison of the simulated cavity to observational constraints on dust-to-metal ratios in bulges. The causal chain 'intense bulge starburst -> localized DTM depression -> central brightening -> lower LTG fraction' is asserted. If the full text contains the demonstration, it must be made legible; if not, this is a gap in the argument.
- [Abstract, JWST comparison] The claim of a lower LTG fraction at high redshift relative to JWST requires the comparison sample to be matched in stellar mass, redshift, rest-frame wavelength, PSF, and noise. None of these selection/matching criteria are visible in the abstract, and the full text is unreadable. Please state the sample selection and matching explicitly, as the morphology differences could be affected by sample mismatch.
minor comments (4)
- [Abstract] The phrase 'OTF galaxy models exhibit' should be rephrased to 'galaxies in the OTF models exhibit' or similar, for clarity.
- [Abstract] Define 'DTM cavity' at its first use, e.g., 'a depression in the dust-to-metal ratio (hereafter the DTM cavity)'.
- [Full text] Remove the embedded 'arXiv:2508.18373v1 [cond-mat.str-el]' and any other extraneous or corrupted material.
- [Methods (fixed DTM model)] Specify the fixed DTM ratio value and whether it is a constant or metallicity-dependent; the abstract does not indicate which assumption is used.
Circularity Check
No circularity found: OTF-vs-fixed DTM morphology comparison is an internally generated differential prediction checked against external JWST data.
full rationale
The paper's central claim is that on-the-fly (OTF) dust modeling produces brighter centers and lower late-type fractions than fixed DTM models in mock JWST images, and that this is linked to a 'DTM cavity' in the simulated dust field. This is a differential result between two dust prescriptions within one simulation, compared against an external observational benchmark (JWST). The measured morphology indices and G-M20 classifications are post-processing outputs from SKIRT radiative transfer, not quantities fitted to the JWST classifications. The DTM cavity is an interpretation of the simulated dust field produced by the OTF model; while it is a post hoc characterization rather than an independent prediction, that is not circularity in the derivation sense. The abstract does not exhibit any step where a fitted parameter is renamed as a prediction, and no equations or unique citations in the abstract reduce the conclusion to an input assumption. The full text supplied is corrupted beyond reliable reading, so no specific equation-level reduction can be quoted. The remaining concern raised in the skeptical reading—whether the OTF subgrid dust destruction and growth rates are calibrated robustly—is a model-fidelity and validation issue, not a circularity issue. The OTF-vs-fixed comparison is self-contained as a differential statement; its physical interpretation depends on the realism of the dust recipes, but that dependence is not equivalency by construction. Therefore the circularity score is 0.
Assumptions & free parameters
free parameters (2)
- Fixed DTM ratio (reference dust model)
- OTF dust model subgrid parameters (formation and destruction efficiencies, timescales)
assumptions (4)
- domain assumption NewCluster's hydrodynamics, star formation, and feedback recipes produce galaxies whose intrinsic structure is identical across the two image sets, so image differences isolate the dust model.
- domain assumption SKIRT mock images with the adopted dust opacities and scattering properties faithfully approximate what JWST observes.
- domain assumption The G-M20 morphological indices classify late- versus early-type galaxies reliably at high redshift in both mock and real imaging.
- domain assumption Bulge starbursts outpace dust production, causing the DTM depression, rather than being offset by rapid dust growth in dense gas.
invented entities (1)
-
DTM cavity
Cite this review
Pith. "Pith review of How Dust Models Shape High-z Galaxy Morphology: Insights from the NewCluster Simulation." pith.science (2026). https://pith.science/paper/7BDNJ6XZ
@misc{pith2026250818374,
author = {Pith},
title = {Pith review of: How Dust Models Shape High-z Galaxy Morphology: Insights from the NewCluster Simulation},
year = {2026},
howpublished = {\url{https://pith.science/paper/7BDNJ6XZ}},
note = {Machine review of arXiv:2508.18374}
}
abstract
Dust plays a pivotal role in shaping the observed morphology of galaxies. While traditional cosmological simulations often assume a fixed dust-to-gas (DTG) or dust-to-metal (DTM) mass ratio to model dust effects, recent advancements have enabled on-the-fly (OTF) dust modeling that captures the spatial and temporal evolution of dust. In this work, we investigate the impact of dust modeling on galaxy morphology using the NewCluster simulation, which implements a detailed OTF dust model. We generate mock images of NewCluster galaxies under both OTF and fixed DTM models using the radiative transfer code SKIRT, and compare their morphology to JWST observations. We measure morphology indices and use the $G-M_{20}$ test to classify galaxies. We find that the OTF galaxy models exhibit brighter centers and more pronounced bulges than those of the fixed DTM models, resulting in a lower late-type galaxy (LTG) fraction, particularly at high redshifts. This central brightening is linked to a phenomenon we refer to as the DTM cavity, a localized depression in the DTM ratio driven by intense bulge starbursts. Our results highlight the importance of modeling dust evolution in a physically motivated manner, as fixed DTM models fail to capture key morphological features.
Forward citations
Cited by 3 Pith papers
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The COLIBRE-SKIRT pipeline: Calibration-free dust radiative transfer postprocessing for cosmological simulations
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On the Origin of Intracluster Light based on the High-resolution Simulation, NewCluster
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DualSparse-MoE: Coordinating Tensor/Neuron-Level Sparsity with Expert Partition and Reconstruction
DualSparse-MoE cuts about 25% of MoE computation after training using expert partition and static neuron reconstruction, with 0.08-0.28% average accuracy loss and up to 1.41x module speedup.
Reference graph
Works this paper leans on
-
[1]
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thebibliography [1] 20pt to REFERENCES 6pt =0pt \@twocolumntrue 12pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key o...
2017
-
[3]
2025, arXiv e-prints, arXiv:2501.10508, 10.48550/arXiv.2501.10508
Algera , H., Rowland , L., Stefanon , M., et al. 2025, arXiv e-prints, arXiv:2501.10508, 10.48550/arXiv.2501.10508
-
[4]
2020, , 491, 3844, 10.1093/mnras/stz3253
Aoyama , S., Hirashita , H., & Nagamine , K. 2020, , 491, 3844, 10.1093/mnras/stz3253
-
[5]
2017, , 466, 105, 10.1093/mnras/stw3061
Aoyama , S., Hou , K.-C., Shimizu , I., et al. 2017, , 466, 105, 10.1093/mnras/stw3061
-
[6]
Asplund , M., Grevesse , N., Sauval , A. J., & Scott , P. 2009, , 47, 481, 10.1146/annurev.astro.46.060407.145222
arXiv 2009
-
[7]
2004, , 352, 376, 10.1111/j.1365-2966.2004.07883.x
Aubert , D., Pichon , C., & Colombi , S. 2004, , 352, 376, 10.1111/j.1365-2966.2004.07883.x
arXiv 2004
-
[8]
2015, Astronomy and Computing, 12, 33, 10.1016/j.ascom.2015.05.006
Baes , M., & Camps , P. 2015, Astronomy and Computing, 12, 33, 10.1016/j.ascom.2015.05.006
-
[9]
2013, , 432, 2298, 10.1093/mnras/stt589
Bekki , K. 2013, , 432, 2298, 10.1093/mnras/stt589
Show all 98 references
-
[10]
1996, , 117, 393, 10.1051/aas:1996164
Bertin , E., & Arnouts , S. 1996, , 117, 393, 10.1051/aas:1996164
1996 doi
-
[11]
Bluck , A. F. L., Conselice , C. J., Buitrago , F., et al. 2012, , 747, 34, 10.1088/0004-637X/747/1/34
2012 doi
-
[12]
2024, astropy/photutils: 1.13.0, 1.13.0, Zenodo, 10.5281/zenodo.12585239
Bradley, L., Sip o cz, B., Robitaille, T., et al. 2024, astropy/photutils: 1.13.0, 1.13.0, Zenodo, 10.5281/zenodo.12585239
2024 doi
-
[13]
2023, grizli, 1.9.11, Zenodo, 10.5281/zenodo.8370018
Brammer, G. 2023, grizli, 1.9.11, Zenodo, 10.5281/zenodo.8370018
2023 doi
-
[14]
2020, Astronomy and Computing, 31, 100381, 10.1016/j.ascom.2020.100381
Camps , P., & Baes , M. 2020, Astronomy and Computing, 31, 100381, 10.1016/j.ascom.2020.100381
2020
-
[15]
W., Baes , M., et al
Camps , P., Trayford , J. W., Baes , M., et al. 2016, , 462, 1057, 10.1093/mnras/stw1735
2016 doi
- [16]
-
[17]
R., Kere s , D., Sandstrom , K
Choban , C. R., Kere s , D., Sandstrom , K. M., et al. 2024, , 529, 2356, 10.1093/mnras/stae716
2024 doi
-
[18]
Conselice , C. J. 2003, , 147, 1, 10.1086/375001
2003 doi
-
[19]
J., Bershady , M
Conselice , C. J., Bershady , M. A., & Jangren , A. 2000, , 529, 886, 10.1086/308300
2000 doi
-
[20]
J., Rajgor , S., & Myers , R
Conselice , C. J., Rajgor , S., & Myers , R. 2008, , 386, 909, 10.1111/j.1365-2966.2008.13069.x
2008
-
[21]
S., & White , S
Davis , M., Efstathiou , G., Frenk , C. S., & White , S. D. M. 1985, , 292, 371, 10.1086/163168
1985 doi
-
[22]
1959, Handbuch der Physik, 53, 275, 10.1007/978-3-642-45932-0_7
de Vaucouleurs , G. 1959, Handbuch der Physik, 53, 275, 10.1007/978-3-642-45932-0_7
1959 doi
-
[23]
L., Schofield , S
De Vis , P., Gomez , H. L., Schofield , S. P., et al. 2017, , 471, 1743, 10.1093/mnras/stx981
2017 doi
-
[24]
2019, , 623, A5, 10.1051/0004-6361/201834444
De Vis , P., Jones , A., Viaene , S., et al. 2019, , 623, A5, 10.1051/0004-6361/201834444
2019 doi
- [25]
-
[26]
R., & Gunn , J
Dressler , A., Oemler , Jr., A., Butcher , H. R., & Gunn , J. E. 1994, , 430, 107, 10.1086/174386
1994 doi
-
[28]
2024, , 687, A240, 10.1051/0004-6361/202449784
Dubois , Y., Rodr \' guez Montero , F., Guerra , C., et al. 2024, , 687, A240, 10.1051/0004-6361/202449784
2024 doi
- [29]
-
[30]
M., & Efstathiou , G
Fall , S. M., & Efstathiou , G. 1980, , 193, 189, 10.1093/mnras/193.2.189
1980 doi
-
[31]
Federrath , C., & Klessen , R. S. 2012, , 761, 156, 10.1088/0004-637X/761/2/156
2012 doi
-
[32]
J., et al
Ferreira , L., Adams , N., Conselice , C. J., et al. 2022, , 938, L2, 10.3847/2041-8213/ac947c
2022 doi
-
[33]
Finner , K., Faisst , A., Chary , R.-R., & Jee , M. J. 2023, , 953, 102, 10.3847/1538-4357/ace1e6
2023 doi
-
[34]
L., Ragone-Figueroa , C., Taverna , A., et al
Granato , G. L., Ragone-Figueroa , C., Taverna , A., et al. 2021, , 503, 511, 10.1093/mnras/stab362
2021 doi
- [35]
-
[36]
2025 a , , 978, 96, 10.3847/1538-4357/ad98f4
Han , S., Dubois , Y., Lee , J., et al. 2025 a , , 978, 96, 10.3847/1538-4357/ad98f4
2025 doi
-
[37]
K., Dubois , Y., et al
Han , S., Yi , S. K., Dubois , Y., et al. 2025 b , arXiv e-prints, arXiv:2507.06301. 2507.06301
2025
-
[38]
C., Lanz , L., Ashby , M
Hayward , C. C., Lanz , L., Ashby , M. L. N., et al. 2014, , 445, 1598, 10.1093/mnras/stu1843
2014 doi
-
[39]
2015, , 447, 2937, 10.1093/mnras/stu2617
Hirashita , H. 2015, , 447, 2937, 10.1093/mnras/stu2617
2015 doi
-
[40]
2011, , 416, 1340, 10.1111/j.1365-2966.2011.19131.x
Hirashita , H., & Kuo , T.-M. 2011, , 416, 1340, 10.1111/j.1365-2966.2011.19131.x
2011
-
[41]
2019, , 485, 1727, 10.1093/mnras/stz121
Hou , K.-C., Aoyama , S., Hirashita , H., Nagamine , K., & Shimizu , I. 2019, , 485, 1727, 10.1093/mnras/stz121
2019 doi
-
[42]
Hubble , E. P. 1926, , 64, 321, 10.1086/143018
1926 doi
-
[43]
Inoue , A. K. 2003, , 55, 901, 10.1093/pasj/55.5.901
2003 doi
-
[44]
1999, , 125, 439, 10.1086/313278
Iwamoto , K., Brachwitz , F., Nomoto , K., et al. 1999, , 125, 439, 10.1086/313278
1999 doi
-
[45]
K., Yi , S
Jang , J. K., Yi , S. K., Dubois , Y., et al. 2023, , 950, 4, 10.3847/1538-4357/accd68
2023 doi
-
[46]
J., Blakeslee , J
Jee , M. J., Blakeslee , J. P., Sirianni , M., et al. 2007, , 119, 1403, 10.1086/524849
2007 doi
-
[47]
A., Weiner , B
Kassin , S. A., Weiner , B. J., Faber , S. M., et al. 2012, , 758, 106, 10.1088/0004-637X/758/2/106
2012 doi
-
[48]
Kauffmann , G., White , S. D. M., & Guiderdoni , B. 1993, , 264, 201, 10.1093/mnras/264.1.201
1993 doi
-
[49]
J., & Tielens , A
Kemper , F., Vriend , W. J., & Tielens , A. G. G. M. 2004, , 609, 826, 10.1086/421339
2004 doi
-
[50]
2014, , 788, 121, 10.1088/0004-637X/788/2/121
Kimm , T., & Cen , R. 2014, , 788, 121, 10.1088/0004-637X/788/2/121
2014 doi
-
[51]
2006, , 653, 1145, 10.1086/508914
Kobayashi , C., Umeda , H., Nomoto , K., Tominaga , N., & Ohkubo , T. 2006, , 653, 1145, 10.1086/508914
2006 doi
-
[52]
M., Dunkley , J., et al
Komatsu , E., Smith , K. M., Dunkley , J., et al. 2011, , 192, 18, 10.1088/0067-0049/192/2/18
2011 doi
-
[53]
2024, , 968, L15, 10.3847/2041-8213/ad43eb
Kuhn , V., Guo , Y., Martin , A., et al. 2024, , 968, L15, 10.3847/2041-8213/ad43eb
2024 doi
-
[54]
G., Baugh , C
Lacey , C. G., Baugh , C. M., Frenk , C. S., et al. 2016, , 462, 3854, 10.1093/mnras/stw1888
2016 doi
-
[55]
H., Park , C., Hwang , H
Lee , J. H., Park , C., Hwang , H. S., & Kwon , M. 2024, , 966, 113, 10.3847/1538-4357/ad3448
2024 doi
-
[56]
D., et al
Leitherer , C., Schaerer , D., Goldader , J. D., et al. 1999, , 123, 3, 10.1086/313233
1999 doi
-
[57]
K., Willis , J
Leste , O. K., Willis , J. P., Canning , R. E. A., & Rennehan , D. 2024, , 533, 2927, 10.1093/mnras/stae1967
2024 doi
-
[58]
2019, , 490, 1425, 10.1093/mnras/stz2684
Li , Q., Narayanan , D., & Dav \'e , R. 2019, , 490, 1425, 10.1093/mnras/stz2684
2019 doi
-
[59]
M., Primack , J., & Madau , P
Lotz , J. M., Primack , J., & Madau , P. 2004, , 128, 163, 10.1086/421849
2004 doi
-
[60]
M., Davis , M., Faber , S
Lotz , J. M., Davis , M., Faber , S. M., et al. 2008, , 672, 177, 10.1086/523659
2008 doi
- [61]
-
[62]
Martin , G., Kaviraj , S., Devriendt , J. E. G., Dubois , Y., & Pichon , C. 2018, , 480, 2266, 10.1093/mnras/sty1936
2018 doi
-
[64]
R., et al
McCluskey , F., Wetzel , A., Loebman , S. R., et al. 2024, , 527, 6926, 10.1093/mnras/stad3547
2024 doi
-
[65]
C., & Marinacci , F
McKinnon , R., Torrey , P., Vogelsberger , M., Hayward , C. C., & Marinacci , F. 2017, , 468, 1505, 10.1093/mnras/stx467
2017 doi
-
[66]
Min , M., Waters , L. B. F. M., de Koter , A., et al. 2007, , 462, 667, 10.1051/0004-6361:20065436
2007 doi
-
[67]
J., Mao , S., & White , S
Mo , H. J., Mao , S., & White , S. D. M. 1998, , 295, 319, 10.1046/j.1365-8711.1998.01227.x
1998
-
[68]
1996, , 379, 613, 10.1038/379613a0
Moore , B., Katz , N., Lake , G., Dressler , A., & Oemler , A. 1996, , 379, 613, 10.1038/379613a0
1996 doi
-
[69]
C., Gil de Paz , A., Boissier , S., et al
Mu \ n oz-Mateos , J. C., Gil de Paz , A., Boissier , S., et al. 2009, , 701, 1965, 10.1088/0004-637X/701/2/1965
2009 doi
-
[70]
C., et al
Narayanan , D., Dey , A., Hayward , C. C., et al. 2010, , 407, 1701, 10.1111/j.1365-2966.2010.16997.x
2010
-
[71]
Negroponte , J., & White , S. D. M. 1983, , 205, 1009, 10.1093/mnras/205.4.1009
1983 doi
-
[72]
2022, , 513, 1531, 10.1093/mnras/stac695
Popping , G., & P \'e roux , C. 2022, , 513, 1531, 10.1093/mnras/stac695
2022 doi
-
[73]
S., & Galametz , M
Popping , G., Somerville , R. S., & Galametz , M. 2017, , 471, 3152, 10.1093/mnras/stx1545
2017 doi
-
[74]
C., Galliano , F., et al
R \'e my-Ruyer , A., Madden , S. C., Galliano , F., et al. 2014, , 563, A31, 10.1051/0004-6361/201322803
2014 doi
-
[75]
F., Lotz , J
Rodriguez-Gomez , V., Snyder , G. F., Lotz , J. M., et al. 2019, , 483, 4140, 10.1093/mnras/sty3345
2019 doi
-
[77]
1961, The Hubble Atlas of Galaxies
Sandage , A. 1961, The Hubble Atlas of Galaxies
1961
-
[78]
2020, , 899, 85, 10.3847/1538-4357/aba42f
Sazonova , E., Alatalo , K., Lotz , J., et al. 2020, , 899, 85, 10.3847/1538-4357/aba42f
2020 doi
-
[79]
1992, , 96, 269
Schaller , G., Schaerer , D., Meynet , G., & Maeder , A. 1992, , 96, 269
1992
-
[80]
2024, , 32, 2, 10.1007/s00159-024-00151-2
Schneider , R., & Maiolino , R. 2024, , 32, 2, 10.1007/s00159-024-00151-2
2024 doi
- [81]
-
[82]
2007, , 172, 1, 10.1086/516585
Scoville , N., Aussel , H., Brusa , M., et al. 2007, , 172, 1, 10.1086/516585
2007 doi
-
[83]
S., & Dav \'e , R
Somerville , R. S., & Dav \'e , R. 2015, , 53, 51, 10.1146/annurev-astro-082812-140951
2015 doi
-
[84]
S., Gilmore , R
Somerville , R. S., Gilmore , R. C., Primack , J. R., & Dom \' nguez , A. 2012, , 423, 1992, 10.1111/j.1365-2966.2012.20490.x
2012
-
[85]
2019, Monthly Notices of the Royal Astronomical Society, 491, 10.1093/mnras/stz2991
Springer, O., Ofek, E., Weiss, Y., & Merten, J. 2019, Monthly Notices of the Royal Astronomical Society, 491, 10.1093/mnras/stz2991
2019 doi
- [86]
-
[87]
2002, , 385, 337, 10.1051/0004-6361:20011817
Teyssier , R. 2002, , 385, 337, 10.1051/0004-6361:20011817
2002 doi
-
[88]
Thob , A. C. R., Crain , R. A., McCarthy , I. G., et al. 2019, , 485, 972, 10.1093/mnras/stz448
2019 doi
-
[89]
W., Schaye , J., Correa , C., et al
Trayford , J. W., Schaye , J., Correa , C., et al. 2025, arXiv e-prints, arXiv:2505.13056, 10.48550/arXiv.2505.13056
2025 doi
- [90]
-
[91]
2009, , 506, 647, 10.1051/0004-6361/200911787
Tweed , D., Devriendt , J., Blaizot , J., Colombi , S., & Slyz , A. 2009, , 506, 647, 10.1051/0004-6361/200911787
2009 doi
-
[92]
Valentino , F., Brammer , G., Gould , K. M. L., et al. 2023, , 947, 20, 10.3847/1538-4357/acbefa
2023 doi
- [93]
-
[94]
C., Abel , T., Croft , R
van den Bosch , F. C., Abel , T., Croft , R. A. C., Hernquist , L., & White , S. D. M. 2002, , 576, 21, 10.1086/341619
2002 doi
-
[95]
2017, , 608, A9, 10.1051/0004-6361/201731586
Ventou , E., Contini , T., Bouch \'e , N., et al. 2017, , 608, A9, 10.1051/0004-6361/201731586
2017 doi
-
[96]
2024, , 973, L29, 10.3847/2041-8213/ad772d
Wang , B., Peng , Y., Cappellari , M., Gao , H., & Mo , H. 2024, , 973, L29, 10.3847/2041-8213/ad772d
2024 doi
- [97]
-
[98]
White , S. D. M., & Rees , M. J. 1978, , 183, 341, 10.1093/mnras/183.3.341
1978 doi
-
[99]
Yan , H., Lazarian , A., & Draine , B. T. 2004, , 616, 895, 10.1086/425111
2004 doi
-
[100]
2023, , 954, 113, 10.3847/1538-4357/ace7b5
Yao , Y., Song , J., Kong , X., et al. 2023, , 954, 113, 10.3847/1538-4357/ace7b5
2023 doi
-
[101]
2013, , 560, A26, 10.1051/0004-6361/201321413
Zafar , T., & Watson , D. 2013, , 560, A26, 10.1051/0004-6361/201321413
2013 doi
-
[102]
2014, , 562, A76, 10.1051/0004-6361/201322989
Zhukovska , S. 2014, , 562, A76, 10.1051/0004-6361/201322989
2014 doi
Reviewed August 5, 2026 · model on record in the stance chip above.
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