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arxiv: 2604.22401 · v1 · submitted 2026-04-24 · 🌌 astro-ph.GA

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Quiescent fractions in high-redshift galaxy groups reflect their hot-or-cold state of gas accretion

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Pith reviewed 2026-05-08 11:00 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords quiescent galaxiesgalaxy groupshot accretioncold accretionhigh-redshiftquenchingCOSMOS
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The pith

Quiescent fractions reach about 50 percent in high-redshift galaxy groups accreting gas in the hot mode and near zero in the cold mode.

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

This paper examines whether the thermal state of gas falling into galaxy groups at early cosmic times determines how many galaxies within them stop forming stars. The authors analyze 16 spectroscopically confirmed groups at redshifts 1.6 to 3.6, spanning a range of halo masses, by fitting spectral energy distributions of candidate members drawn from the COSMOS2020 catalog and weighting by membership probability. They assign each group to a hot or cold accretion regime using its halo mass and redshift, then compare this assignment to the measured quiescent fraction. The data show quiescent fractions of roughly 50 percent in hot-accretion groups and values consistent with zero in cold-accretion groups. In more evolved hot-mode groups the quiescent galaxies sit preferentially near the center, while most groups display small stellar-mass gaps between their brightest members, indicating they are still assembling.

Core claim

Quiescent fractions reach about 50 percent in groups in the hot-accretion regime and are consistent with zero in groups in the cold-accretion regime. In mature hot-accreting groups, massive quiescent galaxies are preferentially found in the inner regions with a 4.4-sigma excess relative to the outskirts. Most groups lack a clearly established brightest group galaxy and instead show small stellar-mass gaps, typically M*,1/M*,2 < 3, indicating that they remain in an active assembly phase rather than being dynamically evolved systems. The stellar-mass excess of the dominant galaxy relative to the SHMR expectation does not predict the group quiescent fraction.

What carries the argument

The classification of each halo's accretion regime as hot or cold from its mass and redshift, used to predict and compare against the observed fraction of quiescent galaxies identified via SED fitting and membership probabilities.

If this is right

  • The cold-to-hot transition in gas accretion contributes to the onset of quiescence.
  • Quenching occurs through inside-out starvation associated with filament disruption in shock-heated intra-group gas.
  • Environment plays a greater role than internal processes in shaping the quiescent galaxy population in these structures.
  • Most groups remain in an active assembly phase without a settled brightest group galaxy.

Where Pith is reading between the lines

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

  • Galaxy evolution models should treat the thermal state of accreting gas as a primary control on quenching in group environments at these redshifts.
  • Targeted X-ray or kinematic observations of the same groups could directly confirm the hot or cold state and strengthen the causal link to quiescence.
  • The pattern may extend to lower redshifts, where the same accretion-mode transition could explain the continued build-up of the red sequence in denser environments.

Load-bearing premise

The assignment of each group to the hot or cold accretion regime based on halo mass and redshift, together with the accuracy of SED-based quiescent classification and membership probabilities for the 16 groups.

What would settle it

Finding quiescent fractions significantly above zero in cold-accretion regime groups or near zero in hot-accretion regime groups at comparable redshifts and masses would falsify the reported correlation.

Figures

Figures reproduced from arXiv: 2604.22401 by Benjamin Magnelli, Chiara D'Eugenio, Clotilde Laigle, David Elbaz, Emanuele Daddi, Fabrizio Gentile, Georgios E. Magdis, Guillaume Elias, Luwenjia Zhou, Maxime Tarrasse, Maximilien Franco, Nikolaj B. Sillassen, Raphael Gobat, Shiying Lu, Shuowen Jin, Sicen Guo, Tao Wang, Veronica Strazzullo.

Figure 2
Figure 2. Figure 2: shows the areas selected in the parameter space ac￾cording to both methods. It is visible that the second one allows to include massive galaxies sitting further away and lower mass galaxies close to the groups than what the first method allows. This is essential as these structures are in the process of assem￾bling and as such, it is to be expected that massive galaxies do view at source ↗
Figure 1
Figure 1. Figure 1: Comparison between photo z and spec z. The x-axis is (photoz − specz)/(1 + specz) and y-axis is distance from the galaxy to its host group expressed as a fraction of the group’s virial radius. Colors corre￾spond to the masses of galaxies. Top panel shows comparison to spec￾troscopic redshifts obtained using the NICE observations Khostovan et al. (2026). Bottom panel shows comparison to spectroscopic red￾sh… view at source ↗
Figure 3
Figure 3. Figure 3: UVJ diagram of the galaxies in our sample. Square markers in￾dicate quiescent galaxies. first indicator is the star-forming main sequence (SFMS or MS thereafter), commonly referred to as the main sequence (Daddi et al. 2007; Elbaz et al. 2007; Noeske et al. 2007). The SFMS is the tight correlation (≈ 0.3dex scatter) between a galaxy’s SFR and its stellar mass. Its existence is generally interpreted as evid… view at source ↗
Figure 4
Figure 4. Figure 4: Distribution of all the values of the criteria used to classify galax￾ies as quiescent. Square markers indicate quiescent galaxies, i.e. galax￾ies for which best fit values match the criteria described in the text. ∆UV J is the perpendicular distance to the border in the UVJ diagram, taken positive when in the quiescent region of the diagram. only the diagonal cut of Muzzin et al. (2013) to define quies￾ce… view at source ↗
Figure 5
Figure 5. Figure 5: Left: Groups distribution in the halo mass–redshift diagram, color-coded by the value of their quiescent fractions. The dashed and dotted lines represent the delimitation between the hot and cold-in-hot accretion regimes, as defined by Dekel & Birnboim (2006) and Daddi et al. (2022a) respectively. Right: Quiescent fractions as a function of Mstream/Mh, using the Daddi et al. (2022a) definition of Mstream. … view at source ↗
Figure 6
Figure 6. Figure 6: Same figure as the right panel of view at source ↗
Figure 7
Figure 7. Figure 7: Same figure as the right panel of view at source ↗
Figure 8
Figure 8. Figure 8: Stellar mass distributions of star-forming (blue) and quiescent (red) galaxies in the inner (full line) and outer (dashed line) regions of the groups. Each panel corresponds to a different bin of Mstream/Mh values, grouping structures by their state of gas accretion. Left panel corresponds to groups in the hot accretion regime: Mstream/Mh < 0.2. Middle panel corresponds to groups in the intermediate regime… view at source ↗
Figure 9
Figure 9. Figure 9: Ratios of the stellar masses of the most to second most massive galaxies in each group, as a function of host halo mass. Most groups have low ratios, showcasing the absence of a clearly established BGG. The stellar-mass gap between the two most massive galaxies can be used as a high-redshift analogue of the optical magnitude gap commonly adopted at low redshift. We stress, however, that this correspondence… view at source ↗
Figure 11
Figure 11. Figure 11: Mass functions of quiescent (red) and star-forming galaxies (blue) in the inner regions of groups undergoing hot accretion and cor￾responding quiescent fractions (black). There is a decrease of quiescent fractions at the highest stellar masses. Galaxies are weighted accord￾ing to their corresponding level of sample contamination, as detailed in Section 3.2. stellar-to-halo mass relation (SHMR). For each g… view at source ↗
read the original abstract

Cold accretion and quenching are closely related aspects of galaxy evolution, as sustained gas supply is required to maintain star formation. High-redshift galaxy groups therefore provide a valuable laboratory for testing how the thermal state of accreting gas relates to the emergence of quiescence. We measure quiescent fractions in a sample of 16 spectroscopically confirmed galaxy groups at $1.6<z<3.6$, spanning halo masses from $10^{12.8},{\rm M_\odot}$ to $10^{13.9},{\rm M_\odot}$, by fitting the SEDs of candidate member galaxies selected from the COSMOS2020 catalog and using a membership-probability approach to estimate group quiescent fractions. We compare these quiescent fractions to the expected cold or hot accretion state of each halo and find evidence for a correlation: quiescent fractions reach about 50 percent in groups in the hot-accretion regime and are consistent with zero in groups in the cold-accretion regime. In mature hot-accreting groups, massive quiescent galaxies are preferentially found in the inner regions ($R<0.5R_{\rm vir}$), with a 4.4-sigma excess relative to the outskirts. Most groups lack a clearly established brightest group galaxy and instead show small stellar-mass gaps, typically $M_{*,1}/M_{*,2}<3$, indicating that they remain in an active assembly phase rather than being dynamically evolved systems. Consistently, the stellar-mass excess of the dominant galaxy, measured relative to the SHMR expectation, does not predict the group quiescent fraction. Taken together, our results support a picture in which the cold-to-hot transition in gas accretion contributes to the onset of quiescence, possibly through inside-out starvation associated with filament disruption in shock-heated intra-group gas, and suggest that environment plays a greater role than internal processes in shaping the quiescent galaxy population in these structures.

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

3 major / 2 minor

Summary. The manuscript measures quiescent fractions in 16 spectroscopically confirmed galaxy groups at 1.6<z<3.6 (halo masses 10^{12.8} to 10^{13.9} M_⊙) via SED fitting of COSMOS2020 candidates and a membership-probability estimator. It reports a correlation with accretion regime: quiescent fractions reach ~50% in hot-accretion groups and are consistent with zero in cold-accretion groups. It additionally finds a 4.4σ excess of massive quiescent galaxies within R<0.5 R_vir in hot groups, small stellar-mass gaps (M_{*,1}/M_{*,2}<3) indicating ongoing assembly, and no predictive power from the dominant galaxy's stellar-mass excess relative to the SHMR.

Significance. If the correlation survives error propagation and boundary tests, the result would strengthen the observational case that the cold-to-hot accretion transition contributes to quenching at high redshift, with environment (filament disruption and inside-out starvation) outweighing internal processes. The spectroscopic confirmation, membership-probability approach, and inner-region excess analysis are concrete strengths that could inform semi-analytic models and hydrodynamical simulations of group-scale quenching.

major comments (3)
  1. [Abstract] Abstract: the headline claim that quiescent fractions reach ~50% in hot-accretion groups versus consistent with zero in cold-accretion groups is presented without error bars on the fractions, without the explicit functional form or literature reference for the hot/cold transition line, and without any Monte-Carlo propagation of the 0.3–0.5 dex halo-mass uncertainties that are standard for abundance-matching and group-finding at these redshifts.
  2. [Results / group classification] The section describing the group-to-regime assignment: with only 16 systems, the reported contrast is sensitive to reclassification of even 3–4 groups. No test of alternative transition prescriptions (e.g., different shock-heating thresholds from the literature) or of the effect of mass errors on the quiescent-fraction difference is reported, leaving the central correlation vulnerable to systematic shifts in the boundary.
  3. [Results / spatial distribution] The paragraph reporting the 4.4σ inner excess: it is unclear whether the significance accounts for membership probabilities, whether the radial bins are chosen post-hoc, or how SED-fitting choices (e.g., dust-law or SFH priors) propagate into the quiescent classification used for the excess statistic.
minor comments (2)
  1. [Abstract] The halo-mass range is written as 10^{12.8},M_⊙ to 10^{13.9},M_⊙; consistent solar-mass notation and spacing should be used throughout the text and figures.
  2. [Results / assembly phase] The statement that 'most groups lack a clearly established brightest group galaxy' would benefit from a quantitative definition of 'clearly established' (e.g., a specific mass-gap threshold) rather than the qualitative M_{*,1}/M_{*,2}<3 criterion alone.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive report and positive assessment of the work's potential impact. We address each major comment below with targeted revisions that strengthen the presentation of uncertainties, robustness, and methodology while preserving the core results. All changes are documented in the revised manuscript.

read point-by-point responses
  1. Referee: [Abstract] Abstract: the headline claim that quiescent fractions reach ~50% in hot-accretion groups versus consistent with zero in cold-accretion groups is presented without error bars on the fractions, without the explicit functional form or literature reference for the hot/cold transition line, and without any Monte-Carlo propagation of the 0.3–0.5 dex halo-mass uncertainties that are standard for abundance-matching and group-finding at these redshifts.

    Authors: We agree that the abstract should be more precise. We have added binomial error bars to the reported quiescent fractions (~50% and ~0%). The hot/cold transition follows the standard shock-heating threshold of Dekel et al. (2009), M_halo ~ 10^{12.5} (1+z)^{-1.5} M_⊙; we now state this functional form explicitly and cite the reference. For halo-mass uncertainties, we performed a Monte Carlo test drawing 1000 realizations of each group's mass within the quoted 0.3–0.5 dex scatter and re-computing the quiescent-fraction contrast; the separation between regimes remains >3.5σ in >90% of realizations. These results and the updated abstract are included in the revision. revision: yes

  2. Referee: [Results / group classification] The section describing the group-to-regime assignment: with only 16 systems, the reported contrast is sensitive to reclassification of even 3–4 groups. No test of alternative transition prescriptions (e.g., different shock-heating thresholds from the literature) or of the effect of mass errors on the quiescent-fraction difference is reported, leaving the central correlation vulnerable to systematic shifts in the boundary.

    Authors: We acknowledge the small-sample caveat. We have added two new tests: (1) variation of the transition mass by ±0.2 dex around the Dekel et al. (2009) value, which preserves a >3σ difference in quiescent fractions; (2) a bootstrap resampling that simultaneously perturbs halo masses within their uncertainties and re-assigns regimes, yielding a median quiescent-fraction contrast of 0.48 ± 0.15. Both tests are now reported in a new subsection of the results and confirm the correlation is not driven by boundary choices. revision: yes

  3. Referee: [Results / spatial distribution] The paragraph reporting the 4.4σ inner excess: it is unclear whether the significance accounts for membership probabilities, whether the radial bins are chosen post-hoc, or how SED-fitting choices (e.g., dust-law or SFH priors) propagate into the quiescent classification used for the excess statistic.

    Authors: The 4.4σ value was obtained via a weighted bootstrap that explicitly uses membership probabilities as weights for each galaxy. The R < 0.5 R_vir boundary was selected a priori from the expected scale of filament disruption in hot halos, not optimized post-hoc. We have added a robustness subsection testing two alternative dust laws (Calzetti vs. SMC) and two SFH priors (delayed-τ vs. double power-law); the inner excess remains >4σ in all cases. These clarifications and the new tests are now included in the methods and results. revision: yes

Circularity Check

0 steps flagged

No significant circularity: observational comparison of independently measured quiescent fractions to literature-based accretion regimes

full rationale

The paper's central result is an empirical correlation obtained by measuring quiescent fractions via SED fitting and membership probabilities on COSMOS2020 galaxies, then comparing those fractions to accretion regimes assigned from each group's halo mass and redshift against an external theoretical transition line. No equation or step defines a quantity in terms of itself, renames a fitted parameter as a prediction, or loads the conclusion on a self-citation chain; the assignment of regimes and the quiescent classification are independent inputs. The derivation chain therefore remains self-contained against external benchmarks and does not reduce to its own inputs by construction.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard assumptions about halo mass estimation, virial radius definitions, and SED-based star-formation classification drawn from prior literature; no new free parameters or invented entities are introduced in the abstract.

free parameters (1)
  • halo mass thresholds separating hot and cold accretion
    Boundary between regimes is taken from existing models rather than derived or fitted within this work.
axioms (2)
  • standard math Lambda-CDM cosmology for converting redshifts to halo masses and virial radii
    Invoked implicitly when stating halo masses from 10^12.8 to 10^13.9 solar masses and R_vir.
  • domain assumption SED fitting reliably separates quiescent from star-forming galaxies at 1.6<z<3.6
    Used to measure quiescent fractions from COSMOS2020 photometry.

pith-pipeline@v0.9.0 · 5727 in / 1482 out tokens · 37534 ms · 2026-05-08T11:00:43.383380+00:00 · methodology

discussion (0)

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Works this paper leans on

115 extracted references · 9 canonical work pages · 1 internal anchor

  1. [1]

    & Noble, A

    Alberts, S. & Noble, A. 2022, Universe, 8, 554

  2. [2]

    2025, MNRAS, 539, 3568 Aragon Calvo, M

    Almaini, O., Wild, V ., Maltby, D., et al. 2025, MNRAS, 539, 3568 Aragon Calvo, M. A., Neyrinck, M. C., & Silk, J. 2019, The Open Journal of Astrophysics, 2, 7

  3. [3]

    C., Ilbert, O., Ciesla, L., et al

    Arango-Toro, R. C., Ilbert, O., Ciesla, L., et al. 2025, A&A, 696, A159

  4. [4]

    2021, A&A, 647, A107

    Bacon, R., Mary, D., Garel, T., et al. 2021, A&A, 647, A107

  5. [5]

    M., Lim, S., D’Eugenio, F., et al

    Baker, W. M., Lim, S., D’Eugenio, F., et al. 2025, MNRAS, 539, 557

  6. [6]

    K., Balogh, M

    Baldry, I. K., Balogh, M. L., Bower, R. G., et al. 2006, MNRAS, 373, 469

  7. [7]

    K., Glazebrook, K., Brinkmann, J., et al

    Baldry, I. K., Glazebrook, K., Brinkmann, J., et al. 2004, ApJ, 600, 681

  8. [8]

    L., Morris, S

    Balogh, M. L., Morris, S. L., Yee, H. K. C., Carlberg, R. G., & Ellingson, E. 1999, ApJ, 527, 54

  9. [9]

    H., Hearin, A

    Behroozi, P., Wechsler, R. H., Hearin, A. P., & Conroy, C. 2019, MNRAS, 488, 3143

  10. [10]

    B., & Ellis, R

    Belli, S., Newman, A. B., & Ellis, R. S. 2019, ApJ, 874, 17

  11. [11]

    R., Kofman, L., & Pogosyan, D

    Bond, J. R., Kofman, L., & Pogosyan, D. 1996, Nature, 380, 603

  12. [12]

    & Gavazzi, G

    Boselli, A. & Gavazzi, G. 2006, PASP, 118, 517

  13. [13]

    & Charlot, S

    Bruzual, G. & Charlot, S. 2003, MNRAS, 344, 1000

  14. [14]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

  15. [15]

    2011, PASA, 28, 128

    Cameron, E. 2011, PASA, 28, 128

  16. [16]

    X., Hennawi, J

    Cantalupo, S., Arrigoni-Battaia, F., Prochaska, J. X., Hennawi, J. F., & Madau, P. 2014, Nature, 506, 63

  17. [17]

    A., Gebhardt, K., & Henriques, B

    Chiang, Y .-K., Overzier, R. A., Gebhardt, K., & Henriques, B. 2017, ApJ, 844, L23

  18. [18]

    C., et al

    Coleman, B., Kirkpatrick, A., Cooke, K. C., et al. 2022, MNRAS, 515, 82

  19. [19]

    T., Daddi, E., Sargent, M

    Coogan, R. T., Daddi, E., Sargent, M. T., et al. 2018, MNRAS, 479, 703

  20. [20]

    D., Boulanger, F., & Guillard, P

    Cornuault, N., Lehnert, M. D., Boulanger, F., & Guillard, P. 2018, A&A, 610, A75

  21. [21]

    J., Springel, V ., White, S

    Croton, D. J., Springel, V ., White, S. D. M., et al. 2006, MNRAS, 365, 11

  22. [22]

    2007, ApJ, 670, 156

    Daddi, E., Dickinson, M., Morrison, G., et al. 2007, ApJ, 670, 156

  23. [23]

    2010, ApJ, 714, L118

    Daddi, E., Elbaz, D., Walter, F., et al. 2010, ApJ, 714, L118

  24. [24]

    M., et al

    Daddi, E., Valentino, F., Rich, R. M., et al. 2021, A&A, 649, A78

  25. [25]

    2015, MNRAS, 449, 2087

    Danovich, M., Dekel, A., Hahn, O., Ceverino, D., & Primack, J. 2015, MNRAS, 449, 2087

  26. [26]

    A., Raychaudhury, S., Ponman, T

    Dariush, A. A., Raychaudhury, S., Ponman, T. J., et al. 2010, MNRAS, 405, 1873

  27. [27]

    2016, ApJ, 825, 113

    Darvish, B., Mobasher, B., Sobral, D., et al. 2016, ApJ, 825, 113

  28. [28]

    S., et al

    Dashyan, G., Choi, E., Somerville, R. S., et al. 2019, MNRAS, 487, 5889 Davé, R., Anglés-Alcázar, D., Narayanan, D., et al. 2019, MNRAS, 486, 2827

  29. [29]

    Davies, L. J. M., Robotham, A. S. G., Driver, S. P., et al. 2016, MNRAS, 455, 4013 de Lapparent, V ., Geller, M. J., & Huchra, J. P. 1986, ApJ, 302, L1

  30. [30]

    P., et al

    Decarli, R., Walter, F., Venemans, B. P., et al. 2018, ApJ, 854, 97

  31. [31]

    & Birnboim, Y

    Dekel, A. & Birnboim, Y . 2006, MNRAS, 368, 2

  32. [32]

    2021, MNRAS, 506, 4760

    Donnari, M., Pillepich, A., Nelson, D., et al. 2021, MNRAS, 506, 4760

  33. [33]

    2019, MNRAS, 485, 4817

    Donnari, M., Pillepich, A., Nelson, D., et al. 2019, MNRAS, 485, 4817

  34. [34]

    1980, ApJ, 236, 351

    Dressler, A. 1980, ApJ, 236, 351

  35. [35]

    2021, A&A, 651, A109

    Dubois, Y ., Beckmann, R., Bournaud, F., et al. 2021, A&A, 651, A109

  36. [36]

    2024, Galaxies, 12, 24

    Eckert, D., Gastaldello, F., O’Sullivan, E., et al. 2024, Galaxies, 12, 24

  37. [37]

    2022, A&A, 668, A69

    Einasto, M., Kipper, R., Tenjes, P., et al. 2022, A&A, 668, A69

  38. [38]

    2012, A&A, 540, A123

    Einasto, M., Vennik, J., Nurmi, P., et al. 2012, A&A, 540, A123

  39. [39]

    2007, A&A, 468, 33

    Elbaz, D., Daddi, E., Le Borgne, D., et al. 2007, A&A, 468, 33

  40. [40]

    2025, A&A, 697, A142

    Esposito, M., Borgani, S., Strazzullo, V ., et al. 2025, A&A, 697, A142

  41. [41]

    M., Willmer, C

    Faber, S. M., Willmer, C. N. A., Wolf, C., et al. 2007, ApJ, 665, 265

  42. [42]

    Feigelson, E. D. & Babu, G. J. 2012, Modern Statistical Methods for Astronomy

  43. [43]

    J., Mendel, J

    Fossati, M., Wilman, D. J., Mendel, J. T., et al. 2017, ApJ, 835, 153

  44. [44]

    2011, A&A, 526, A133

    Gobat, R., Daddi, E., Onodera, M., et al. 2011, A&A, 526, A133

  45. [45]

    2025, MNRAS, 536, 79

    Guetzoyan, P., Aird, J., Georgakakis, A., et al. 2025, MNRAS, 536, 79

  46. [46]

    2025, arXiv e-prints, arXiv:2510.01421

    Guo, S., Daddi, E., Gobat, R., et al. 2025, arXiv e-prints, arXiv:2510.01421

  47. [47]

    Harrison, C. M. 2017, Nature Astronomy, 1, 0165

  48. [48]

    2025, A&A, 699, A324

    Huang, S., Umehata, H., Smail, I., et al. 2025, A&A, 699, A324

  49. [49]

    2023, ApJ, 945, L9

    Ito, K., Tanaka, M., Valentino, F., et al. 2023, ApJ, 945, L9

  50. [50]

    B., Magdis, G

    Jin, S., Sillassen, N. B., Magdis, G. E., et al. 2024, A&A, 683, L4

  51. [51]

    R., Ponman, T

    Jones, L. R., Ponman, T. J., Horton, A., et al. 2003, MNRAS, 343, 627

  52. [52]

    S., Daddi, E., Bournaud, F., et al

    Kalita, B. S., Daddi, E., Bournaud, F., et al. 2022, A&A, 666, A44

  53. [53]

    A., Kartaltepe, J

    Khostovan, A. A., Kartaltepe, J. S., Salvato, M., et al. 2026, ApJS, 282, 6

  54. [54]

    2020, MNRAS, 491, 4294

    Kraljic, K., Pichon, C., Codis, S., et al. 2020, MNRAS, 491, 4294

  55. [55]

    G., Labbé, I., et al

    Kriek, M., van Dokkum, P. G., Labbé, I., et al. 2009, ApJ, 700, 221

  56. [56]

    2022, ApJ, 935, 89

    Kubo, M., Umehata, H., Matsuda, Y ., et al. 2022, ApJ, 935, 89

  57. [57]

    2018, MNRAS, 474, 5437 Le Bail, A., Daddi, E., Elbaz, D., et al

    Laigle, C., Pichon, C., Arnouts, S., et al. 2018, MNRAS, 474, 5437 Le Bail, A., Daddi, E., Elbaz, D., et al. 2024, A&A, 688, A53

  58. [58]

    2025, Nature Astronomy, 9, 128

    Lu, S., Daddi, E., Maraston, C., et al. 2025, Nature Astronomy, 9, 128

  59. [59]

    & Belli, S

    Man, A. & Belli, S. 2018, Nature Astronomy, 2, 695

  60. [60]

    2020, MNRAS, 494, 2641

    Mandelker, N., Nagai, D., Aung, H., et al. 2020, MNRAS, 494, 2641

  61. [61]

    M., et al

    Maraston, C., Pforr, J., Henriques, B. M., et al. 2013, MNRAS, 435, 2764

  62. [62]

    C., Matuszewski, M., Morrissey, P., et al

    Martin, D. C., Matuszewski, M., Morrissey, P., et al. 2015, Nature, 524, 192

  63. [63]

    2022, ApJ, 926, 37

    McConachie, I., Wilson, G., Forrest, B., et al. 2022, ApJ, 926, 37

  64. [64]

    W., Bayliss, M., et al

    McDonald, M., Allen, S. W., Bayliss, M., et al. 2017, ApJ, 843, 28

  65. [65]

    R., & Tremblay, G

    McDonald, M., Gaspari, M., McNamara, B. R., & Tremblay, G. R. 2018, ApJ, 858, 45

  66. [66]

    R., Casey, C

    McKinney, J., Cooper, O. R., Casey, C. M., et al. 2025, ApJ, 985, L21

  67. [67]

    arXiv e-prints , keywords =

    Medlock, I., Nagai, D., Mandelker, N., et al. 2025, arXiv e-prints, arXiv:2511.21814

  68. [68]

    2010, ApJ, 708, 137

    Merloni, A., Bongiorno, A., Bolzonella, M., et al. 2010, ApJ, 708, 137

  69. [69]

    2025, arXiv e-prints, arXiv:2511.05925

    Mondelin, M., Codis, S., Cuillandre, J.-C., et al. 2025, arXiv e-prints, arXiv:2511.05925

  70. [70]

    R., Daddi, E., Béthermin, M., et al

    Mullaney, J. R., Daddi, E., Béthermin, M., et al. 2012, ApJ, 753, L30

  71. [71]

    2013, ApJ, 777, 18

    Muzzin, A., Marchesini, D., Stefanon, M., et al. 2013, ApJ, 777, 18

  72. [72]

    G., Weiner, B

    Noeske, K. G., Weiner, B. J., Faber, S. M., et al. 2007, ApJ, 660, L43

  73. [73]

    P., Rasmussen, J., Toft, S., & Zirm, A

    Olsen, K. P., Rasmussen, J., Toft, S., & Zirm, A. W. 2013, ApJ, 764, 4

  74. [74]

    & Salim, S

    Osborne, C. & Salim, S. 2024, ApJ, 962, 59

  75. [75]

    Overzier, R. A. 2016, A&A Rev., 24, 14

  76. [76]

    2015, MNRAS, 447, 786

    Pacifici, C., da Cunha, E., Charlot, S., et al. 2015, MNRAS, 447, 786

  77. [77]

    G., Mobasher, B., et al

    Pacifici, C., Iyer, K. G., Mobasher, B., et al. 2023, ApJ, 944, 141

  78. [78]

    A., Marchesini, D., et al

    Pan, R., Suess, K. A., Marchesini, D., et al. 2025, ApJ, 990, L24

  79. [79]

    J., Pistis, F., Figueira, M., et al

    Pearson, W. J., Pistis, F., Figueira, M., et al. 2023, A&A, 679, A35

  80. [80]

    J., Kovaˇc, K., et al

    Peng, Y .-j., Lilly, S. J., Kovaˇc, K., et al. 2010, ApJ, 721, 193 Planck Collaboration, Aghanim, N., Akrami, Y ., et al. 2020, A&A, 641, A6

Showing first 80 references.