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arxiv: 2511.00975 · v2 · submitted 2025-11-02 · 🌌 astro-ph.GA · astro-ph.CO

The Atacama Cosmology Telescope: stellar mass growth in massive galaxy clusters from DR5 over the past 7 billion years

Pith reviewed 2026-05-18 01:32 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.CO
keywords galaxy clustersstellar mass functiongalaxy evolutionSunyaev-Zel'dovich effectcluster assemblycosmic star formation history
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0 comments X p. Extension

The pith

Galaxy clusters show stellar mass growth by a factor of 2.5 over the past 7 billion years after accounting for halo mass increase.

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

The paper measures the evolution of stellar mass in galaxies within massive clusters from redshift 0.8 to 0.2 using Sunyaev-Zel'dovich selected samples from the Atacama Cosmology Telescope. It constructs composite stellar mass functions down to 10^9.5 solar masses from deep DECaLS photometry and finds that the fraction of cluster mass in stars grows by a factor of 2.5 once the expected growth from increasing halo mass is removed. Most of this change occurs below redshift 0.55, while the high-mass end of the galaxy population appears largely in place by z approximately 0.8. A reader would care because the result points to late-time assembly processes such as mergers or accretion shaping the galaxies that live in dense cluster environments.

Core claim

In a sample of 568 SZ-selected clusters above 2.9 times 10^14 solar masses at 0.2 less than z less than 0.8, the composite stellar mass functions show marginal evolution in the characteristic mass M-star at higher redshifts but clear growth at lower redshifts. The low-mass slope steepens below z equals 0.55. After subtracting the contribution from halo mass growth, the stellar mass fraction locked in galaxies more massive than 10^9.5 solar masses increases by a factor of 2.5 across the interval.

What carries the argument

Redshift- and mass-binned composite cluster stellar mass functions built from DECaLS DR10 photometry, which track the distribution of galaxy stellar masses within the clusters.

If this is right

  • The bulk of the massive galaxy population inside clusters is already assembled by redshift approximately 0.8.
  • Late-time processes such as mergers or accretion drive most of the additional stellar mass growth at lower redshifts.
  • The low-mass end of the galaxy population becomes more abundant in clusters as redshift decreases.
  • Stellar mass growth in clusters proceeds independently of the dark matter halo mass growth rate.

Where Pith is reading between the lines

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

  • The measured growth rate supplies a concrete target for hydrodynamical simulations of cluster galaxy formation to reproduce.
  • Extending the same analysis to lower stellar mass limits with future surveys could reveal whether the growth trend continues or saturates.
  • The result links to broader questions of how environment affects the shutdown of star formation in galaxies.

Load-bearing premise

The photometry and sample selection capture the full galaxy population inside the clusters without major incompleteness or bias down to stellar masses of 10^9.5 solar masses.

What would settle it

Deeper or independent photometry of the same clusters that yields a stellar mass fraction growth factor significantly different from 2.5 after halo mass correction would falsify the central result.

Figures

Figures reproduced from arXiv: 2511.00975 by Bruce Partridge, Crist\'obal Sif\'on, Damien C. Ragavan, Edward J. Wollack, Eve M. Vavagiakis, John P. Hughes, Kavilan Moodley, Maria Salatino, Matt Hilton, Tony Mroczkowski, Unnikrishnan Sureshkumar.

Figure 1
Figure 1. Figure 1: The distribution of log cluster mass (log10 [𝑀200m/M⊙ ]) with red￾shift for the ACT DR5 cluster sample (shown as grey circles), and the cluster sample selected in this work (show as light blue triangles). Our cluster sample has been selected based on the optical depth in DECaLS DR10 (see Section 3.5. The redshift (Top panel) and cluster mass (Right panel) normalised dis￾tributions for each sample are also … view at source ↗
Figure 2
Figure 2. Figure 2: A mass-limited sample obtained for a galaxy field (RA = 45◦ .0; Dec = −51◦ .0) in DECaLS DR10 that also has DES coverage. This galaxy sample is used to gauge a consistent stellar mass depth in DECaLS DR10. Blue points represent all galaxies within the field region. The orange points in the shaded area show the galaxies above the stellar mass limit (log10 [𝑀∗/M⊙ ] = 9.5) and within our selected redshift ran… view at source ↗
Figure 4
Figure 4. Figure 4: The best-fit composite cluster SMFs for 2 redshift bins, ⟨𝑧⟩ = 0.325 and ⟨𝑧⟩ = 0.625. Black circles represent the SMF for all cluster galaxies in the redshift bin. Blue diamonds and red squares represent the SMF of cluster galaxies in the low- and high-mass cluster mass subsets, respectively. Error bars show the 1𝜎 uncertainties calculated using bootstrap resampling. A solid line shows a best-fit single Sc… view at source ↗
Figure 5
Figure 5. Figure 5: The single Schechter models to the 12 total redshift binned com￾posite SMFs. Each model has been normalised by a common log stellar mass, log10 [𝑀∗/M⊙ ] = 10.75, in order to emphasise the evolution of the low-mass slope. The colour bar is used to represents the model evolution with redshift. 5.2 The Schechter+Gaussian model Although we do find a single Schechter function to be an adequate fit to our compos… view at source ↗
Figure 6
Figure 6. Figure 6: The evolution of the characteristic stellar mass (𝑀∗ = log10 [𝑀∗ ∗ /M⊙ ]) and low-mass slope (𝛼) with redshift for each of the 12 redshift bins, which are represented by black circles. The results from previous field (shown as orange markers) and cluster studies (shown as light blue markers) are also included. 𝑀∗ and 𝛼 values from the cluster simulation study by Ahad et al. (2021) are represented by magent… view at source ↗
Figure 7
Figure 7. Figure 7: The composite cluster SMFs for two redshift bins (⟨𝑧⟩ = 0.375 and ⟨𝑧⟩ = 0.475), modelled with a Schechter+Gaussian function. The excess in stellar mass at the high-mass end, above the Schechter function, is appropriately described by the Gaussian model. Parameter values for the best-fit Schechter+Gaussian model are presented in [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: The evolution of the Schechter+Gaussian model parameters: 𝑀MG = log10 [𝑀¯ MG,∗/M⊙ ] and 𝜎MG, with redshift. Error bars represent the 1𝜎 uncertainties estimated from parameter posterior distributions obtained from MCMC sampling [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The scaling relationship between cluster stellar mass (𝑀 cg ∗ ) and cluster mass (𝑀200m), represented in log-scale, for all 12 redshift bins. The solid red line represents the power-law fit (given by Eqn. 10), with the shaded region showing 1𝜎 scatter. Time evolution of the slope of the power-law fit (𝑏) shows that the 𝑀 cg ∗ -𝑀200m relation does not evolve significantly since 𝑧 = 0.8. The absence of the f… view at source ↗
Figure 10
Figure 10. Figure 10: The evolution of the power-law slope (𝑏), represented as black triangles, with redshift for each of the 12 redshift bins. Magenta squares represent the predicted slope values from the Hydrangea simulated clusters at 𝑧 ∼ 0.6 and 𝑧 ∼ 1.0, from Ahad et al. 2021. for the total cluster sample, the low-cluster-mass and high-cluster￾mass subset [PITH_FULL_IMAGE:figures/full_fig_p014_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: The average cluster stellar mass fraction ( 𝑓 cg ∗ ) represented as a function of redshift and lookback time (in Gyr) is shown for the entire cluster sample (black circles joined by a solid line), the low-cluster-mass subset (blue diamonds joined by a dashed-dotted line), and the high-cluster-mass subset (red squares joined by a dashed line). Shaded regions represent 1𝜎 scatter for each sample. 𝑓 cg ∗ is … view at source ↗
read the original abstract

We probe the stellar mass growth in a sample of 568 Sunyaev-Zel'dovich (SZ) selected galaxy clusters with masses greater than $2.9 \times 10^{14} \mathrm{M_{\odot}}$ and redshifts in the range $0.2 < z < 0.8$, drawn from the fifth data release of the Atacama Cosmology Telescope (ACT DR5). By utilising deep photometry from the tenth data release of the Dark Energy Camera Legacy Survey (DECaLS DR10), we construct redshift- and cluster mass-binned composite cluster stellar mass functions (SMFs), down to $M_* = 10^{9.5} \mathrm{M_{\odot}}$. This work presents the first analysis of the cluster SMF for this cluster sample at this epoch. We find that the characteristic stellar mass ($M^*$) of the cluster SMF evolves marginally from $0.55 \leq z < 0.8$, with most of the measurable growth occurring at $ 0.2 < z < 0.55$. This suggests that most of the massive galaxy population in clusters ($M_* \gtrsim 10^{10.75} \mathrm{M_{\odot}}$) is largely established by $z \sim 0.8$, with subsequent evolution driven by late-time assembly processes. The low-mass slope ($\alpha$) of the composite cluster SMF is flat at high-$z$ ($z \sim 0.8$) but steepens at $z < 0.55$, suggesting an abundance of massive galaxies in high-$z$ clusters compared to low-$z$ clusters. We measure the evolution of cluster stellar mass fractions contained within galaxies with $M_* > 10^{9.5} \mathrm{M_{\odot}}$ between $ 0.2 < z < 0.8$, and find evidence of significant growth, by a factor of $2.5$, after accounting for the growth in cluster halo mass over this epoch.

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 paper analyzes stellar mass growth in 568 SZ-selected galaxy clusters (M > 2.9e14 M_sun) from ACT DR5 at 0.2 < z < 0.8 using DECaLS DR10 photometry. It constructs redshift- and mass-binned composite cluster stellar mass functions (SMFs) down to M_* = 10^{9.5} M_sun, reports marginal evolution in the characteristic mass M* (mostly below z=0.55), a steepening low-mass slope at low z, and a factor of 2.5 growth in the stellar mass fraction within galaxies above 10^{9.5} M_sun after correcting for halo mass growth over the epoch.

Significance. If robust, the result provides a direct observational constraint on the assembly of the galaxy population in massive clusters over the past ~7 Gyr, indicating that the high-mass end is largely in place by z~0.8 while low-mass galaxies continue to build up. The use of a large, uniformly selected SZ cluster sample combined with public deep photometry is a strength for reproducibility.

major comments (3)
  1. [Abstract / SMF methods] Abstract and SMF construction section: the reported factor-of-2.5 growth in stellar mass fraction is obtained by integrating the composite SMF above 10^{9.5} M_sun; however, no quantitative completeness curves, recovery fractions, or redshift-dependent validation of background subtraction and membership cuts are provided. This leaves open the possibility that DECaLS DR10 depth plus color/photo-z selection undercounts low-mass galaxies more severely at 0.55 < z < 0.8 than at lower z, which would artificially suppress the high-z SMF and inflate the growth factor.
  2. [Results on stellar mass fractions] Abstract and results section on stellar mass fractions: the halo-mass correction that converts the observed stellar mass growth into the quoted factor of 2.5 is not described (e.g., which mass-observable relation or simulation-based scaling is adopted, and how uncertainties in that scaling propagate). Because the central claim is the excess growth beyond halo-mass scaling, this step is load-bearing.
  3. [Abstract / Error analysis] Abstract: no details are given on error propagation (Poisson, cosmic variance, photometric redshift uncertainties, or field-to-cluster subtraction residuals) for the binned composite SMFs or the integrated stellar mass fractions. Without these, the statistical significance of the reported evolution cannot be evaluated.
minor comments (2)
  1. [Sample selection] Clarify the exact definition of the cluster mass threshold (2.9e14 M_sun) and whether it is redshift-dependent or fixed in the sample selection.
  2. [Results] Add a table or figure showing the number of clusters and galaxies per redshift/mass bin to allow readers to assess the robustness of the composite SMFs.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive comments that highlight areas where additional detail will improve clarity and robustness. We address each major comment below and have revised the paper accordingly to incorporate the requested information and validations.

read point-by-point responses
  1. Referee: [Abstract / SMF methods] Abstract and SMF construction section: the reported factor-of-2.5 growth in stellar mass fraction is obtained by integrating the composite SMF above 10^{9.5} M_sun; however, no quantitative completeness curves, recovery fractions, or redshift-dependent validation of background subtraction and membership cuts are provided. This leaves open the possibility that DECaLS DR10 depth plus color/photo-z selection undercounts low-mass galaxies more severely at 0.55 < z < 0.8 than at lower z, which would artificially suppress the high-z SMF and inflate the growth factor.

    Authors: We thank the referee for identifying this important point regarding potential systematics. While our original analysis incorporated basic checks on membership using photometric redshifts and background subtraction via random fields, we agree that quantitative completeness information was insufficiently detailed. In the revised manuscript we have added Section 3.3 and a new Figure 4 that present completeness curves obtained by injecting mock galaxies with realistic SEDs and magnitudes into the DECaLS DR10 imaging and recovering them with our exact color and photo-z selection pipeline. These curves show recovery fractions of ~85% at z~0.3 and ~78% at z~0.7 for M_*=10^{9.5} M_sun, with the modest redshift dependence folded into the error budget. We also include explicit tests of background subtraction residuals and membership cut stability. After applying these corrections the integrated stellar mass growth factor remains 2.4-2.6, confirming that differential incompleteness does not drive the result. The abstract has been updated to reference this validation. revision: yes

  2. Referee: [Results on stellar mass fractions] Abstract and results section on stellar mass fractions: the halo-mass correction that converts the observed stellar mass growth into the quoted factor of 2.5 is not described (e.g., which mass-observable relation or simulation-based scaling is adopted, and how uncertainties in that scaling propagate). Because the central claim is the excess growth beyond halo-mass scaling, this step is load-bearing.

    Authors: We apologize for the brevity of the original description of this central step. In the revised Section 4.2 we now fully specify the halo-mass correction: we adopt the mean mass accretion history for halos of M_200~3e14 M_sun from the Millennium Simulation (as parameterized by Fakhouri et al. 2010) and scale the observed stellar mass by the ratio of expected halo mass at the mean redshift of each bin while holding number density fixed. Uncertainties are propagated via Monte Carlo sampling of the mass-observable relation parameters (including 0.15 dex intrinsic scatter) and re-deriving the growth factor 1000 times; the resulting 68% interval is 2.1-2.9. We also compare against an alternative scaling drawn from the IllustrisTNG hydrodynamical simulations and find consistent results. These additions make the procedure fully reproducible and demonstrate that the reported factor of 2.5 is robust to reasonable variations in the adopted scaling. revision: yes

  3. Referee: [Abstract / Error analysis] Abstract: no details are given on error propagation (Poisson, cosmic variance, photometric redshift uncertainties, or field-to-cluster subtraction residuals) for the binned composite SMFs or the integrated stellar mass fractions. Without these, the statistical significance of the reported evolution cannot be evaluated.

    Authors: We agree that a transparent error budget is required to assess the significance of the reported evolution. We have added Appendix A that details the full error propagation. For each SMF bin the total uncertainty combines Poisson counting errors, cosmic variance estimated from 100 jackknife resamplings of the survey footprint, photometric redshift uncertainties propagated through the membership probability weights, and background subtraction residuals measured from the variance across 500 random off-cluster pointings. For the integrated stellar mass fractions we additionally perform bootstrap resampling over the 568 clusters to capture sample variance. With these errors included, the factor-of-2.5 growth in stellar mass fraction is significant at approximately 3 sigma. The abstract has been revised to note that the evolution is robust after accounting for all quantified uncertainties. revision: yes

Circularity Check

0 steps flagged

No significant circularity; results from direct empirical measurements on public survey data

full rationale

The derivation chain consists of constructing composite stellar mass functions directly from DECaLS DR10 photometry for ACT DR5 clusters, integrating above a fixed mass threshold, and comparing redshift bins after a separate halo-mass correction. No step reduces by construction to a fitted parameter renamed as a prediction, no self-citation supplies a load-bearing uniqueness theorem or ansatz, and the central growth factor is an observable integral over independently measured galaxy counts rather than an internal consistency relation. The analysis is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

Abstract-only review limits visibility into exact assumptions; the work rests on standard domain assumptions about SZ mass proxies and photometric completeness that are not detailed here.

free parameters (2)
  • Cluster mass threshold
    Defines the sample of massive clusters used for the analysis.
  • Stellar mass completeness limit
    Sets the lower bound for constructing the SMFs.
axioms (2)
  • domain assumption SZ-selected clusters provide a mass-limited sample with reliable halo mass estimates across the redshift range
    Underpins the sample selection and the correction for halo mass growth.
  • domain assumption DECaLS DR10 photometry yields complete galaxy catalogs down to M_* = 10^{9.5} M_⊙ in the cluster fields
    Required for the reported SMF construction and low-mass slope measurements.

pith-pipeline@v0.9.0 · 5974 in / 1587 out tokens · 41255 ms · 2026-05-18T01:32:31.126662+00:00 · methodology

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Works this paper leans on

139 extracted references · 139 canonical work pages · 8 internal anchors

  1. [1]

    arXiv:2507.21459

    ACTDESHSC Collaboration et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2507.21459 , https://ui.adsabs.harvard.edu/abs/2025arXiv250721459A p. arXiv:2507.21459

  2. [2]

    Abbott T. M. C., et al., 2021, @doi [ ] 10.3847/1538-4365/ac00b3 , 255, 20

  3. [3]

    J., Bowler R

    Adams N. J., Bowler R. A. A., Jarvis M. J., Häußler B., Lagos C. D. P., 2021, @doi [ ] 10.1093/mnras/stab1956 , 506, 4933

  4. [4]

    L., Bahé Y

    Ahad S. L., Bahé Y. M., Hoekstra H., van der Burg R. F. J., Muzzin A., 2021, @doi [ ] 10.1093/mnras/stab1036 , 504, 1999

  5. [5]

    Akaike H., 1974, IEEE Transactions on Automatic Control, https://ui.adsabs.harvard.edu/abs/1974ITAC...19..716A 19, 716

  6. [6]

    Error estimation in astronomy: A guide

    Andrae R., 2010, @doi [arXiv e-prints] 10.48550/arXiv.1009.2755 , https://ui.adsabs.harvard.edu/abs/2010arXiv1009.2755A p. arXiv:1009.2755

  7. [7]

    Andreon S., 2010, @doi [ ] 10.1111/j.1365-2966.2010.16856.x , 407, 263

  8. [8]

    Annunziatella M., et al., 2014, @doi [ ] 10.1051/0004-6361/201424102 , https://ui.adsabs.harvard.edu/abs/2014A&A...571A..80A 571, A80

  9. [9]

    Annunziatella M., et al., 2016, @doi [ ] 10.1051/0004-6361/201527399 , https://ui.adsabs.harvard.edu/abs/2016A&A...585A.160A 585, A160

  10. [10]

    W., Piffaretti, R., et al

    Arnaud M., Pratt G. W., Piffaretti R., B \"o hringer H., Croston J. H., Pointecouteau E., 2010, @doi [ ] 10.1051/0004-6361/200913416 , https://ui.adsabs.harvard.edu/abs/2010A&A...517A..92A 517, A92

  11. [11]

    M., et al., 2017, @doi [ ] 10.1093/mnras/stx1403 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4186B 470, 4186

    Bah \'e Y. M., et al., 2017, @doi [ ] 10.1093/mnras/stx1403 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4186B 470, 4186

  12. [12]

    , keywords =

    Baldry I. K., Glazebrook K., Driver S. P., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13348.x , 388, 945

  13. [13]

    Individual analysis of CEMP-s and CEMP-s/r with asymptotic giant branch models

    Baldry I. K., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20340.x , 421, 621

  14. [14]

    L., et al., 2017, @doi [ ] 10.1093/mnras/stx1370 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4168B 470, 4168

    Balogh M. L., et al., 2017, @doi [ ] 10.1093/mnras/stx1370 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4168B 470, 4168

  15. [15]

    M., 2006, @doi [Reports on Progress in Physics] 10.1088/0034-4885/69/12/R02 , https://ui.adsabs.harvard.edu/abs/2006RPPh...69.3101B 69, 3101

    Baugh C. M., 2006, @doi [Reports on Progress in Physics] 10.1088/0034-4885/69/12/R02 , https://ui.adsabs.harvard.edu/abs/2006RPPh...69.3101B 69, 3101

  16. [16]

    H., Hearin A

    Behroozi P., Wechsler R. H., Hearin A. P., Conroy C., 2019, @doi [ ] 10.1093/mnras/stz1182 , 488, 3143

  17. [17]

    Bekki K., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15431.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.399.2221B 399, 2221

  18. [18]

    F., McIntosh D

    Bell E. F., McIntosh D. H., Katz N., Weinberg M. D., 2003, , 149, 289

  19. [19]

    Ben \' tez N., 2000, @doi [ ] 10.1086/308947 , https://ui.adsabs.harvard.edu/abs/2000ApJ...536..571B 536, 571

  20. [20]

    J., Margalef-Bentabol B., Duncan K., 2019, @doi [ ] 10.1093/mnras/stz866 , 486, 3805

    Bhatawdekar R., Conselice C. J., Margalef-Bentabol B., Duncan K., 2019, @doi [ ] 10.1093/mnras/stz866 , 486, 3805

  21. [21]

    Bhattacharya S., Habib S., Heitmann K., Vikhlinin A., 2013, @doi [ ] 10.1088/0004-637X/766/1/32 , https://ui.adsabs.harvard.edu/abs/2013ApJ...766...32B 766, 32

  22. [22]

    Binney J., Tabor G., 1995, @doi [ ] 10.1093/mnras/276.2.663 , 276, 663

  23. [23]

    Birkinshaw M., 1999, @doi [ ] 10.1016/S0370-1573(98)00080-5 , https://ui.adsabs.harvard.edu/abs/1999PhR...310...97B 310, 97

  24. [24]

    R., Hogg, D

    Blanton M. R., et al., 2003, @doi [ ] 10.1086/375776 , 592, 819

  25. [25]

    R., Eisenstein, D., Hogg, D

    Blanton M. R., Eisenstein D., Hogg D. W., Schlegel D. J., Brinkmann J., 2005, @doi [ ] 10.1086/422897 , https://ui.adsabs.harvard.edu/abs/2005ApJ...629..143B 629, 143

  26. [26]

    E., Stalder, B., de Haan, T., et al

    Bleem L. E., et al., 2015, @doi [ ] 10.1088/0067-0049/216/2/27 , 216, 27

  27. [27]

    D., et al., 2016, in American Astronomical Society Meeting Abstracts \#228

    Blum R. D., et al., 2016, in American Astronomical Society Meeting Abstracts \#228. p. 317.01

  28. [28]

    Borghi N., Moresco M., Cimatti A., Huchet A., Quai S., Pozzetti L., 2022, @doi [ ] 10.3847/1538-4357/ac3240 , 927, 164

  29. [29]

    , keywords =

    Bower R. G., Benson A. J., Malbon R., Helly J. C., Frenk C. S., Baugh C. M., Cole S., Lacey C. G., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10519.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.370..645B 370, 645

  30. [30]

    B., van Dokkum, P

    Brammer G. B., van Dokkum P. G., Coppi P., 2008, @doi [ ] 10.1086/591786 , https://ui.adsabs.harvard.edu/abs/2008ApJ...686.1503B 686, 1503

  31. [31]

    B., et al., 2011, @doi [ ] 10.1088/0004-637X/739/1/24 , https://ui.adsabs.harvard.edu/abs/2011ApJ...739...24B 739, 24

    Brammer G. B., et al., 2011, @doi [ ] 10.1088/0004-637X/739/1/24 , https://ui.adsabs.harvard.edu/abs/2011ApJ...739...24B 739, 24

  32. [32]

    J., Lubin L

    Brunner R. J., Lubin L. M., 2000, @doi [ ] 10.1086/316849 , 120, 2851

  33. [33]

    Bruzual G., Charlot S., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06897.x , 344, 1000

  34. [34]

    Bundy K., et al., 2006, @doi [ ] 10.1086/507456 , https://ui.adsabs.harvard.edu/abs/2006ApJ...651..120B 651, 120

  35. [35]

    Burke C., Hilton M., Collins C., 2015, @doi [ ] 10.1093/mnras/stv450 , 449, 2353

  36. [36]

    M., Vulcani B., Fasano G., 2013, @doi [ ] 10.1093/mnras/stt667 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.432.3141C 432, 3141

    Calvi R., Poggianti B. M., Vulcani B., Fasano G., 2013, @doi [ ] 10.1093/mnras/stt667 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.432.3141C 432, 3141

  37. [37]

    The Dust Content and Opacity of Actively Star-Forming Galaxies

    Calzetti D., Armus L., Bohlin R. C., Kinney A. L., Koornneef J., Storchi-Bergmann T., 2000, @doi [ ] 10.1086/308692 , https://ui.adsabs.harvard.edu/abs/2000ApJ...533..682C 533, 682

  38. [38]

    E., Holder, G

    Carlstrom J. E., Holder G. P., Reese E. D., 2002, @doi [ ] 10.1146/annurev.astro.40.060401.093803 , https://ui.adsabs.harvard.edu/abs/2002ARA&A..40..643C 40, 643

  39. [39]

    C., et al., 2019, @doi [ ] 10.1093/mnras/stz2544 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490..417C 490, 417

    Carnall A. C., et al., 2019, @doi [ ] 10.1093/mnras/stz2544 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490..417C 490, 417

  40. [40]

    Cedr \'e s B., et al., 2025, @doi [ ] 10.1051/0004-6361/202452898 , https://ui.adsabs.harvard.edu/abs/2025A&A...696A..85C 696, A85

  41. [41]

    Chabrier G., 2003, @doi [ ] 10.1086/376392 , https://ui.adsabs.harvard.edu/abs/2003PASP..115..763C 115, 763

  42. [42]

    Chiu I., et al., 2018, @doi [ ] 10.1093/mnras/sty1284 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.3072C 478, 3072

  43. [43]

    L., 2020, @doi [ ] 10.1093/mnras/staa3267 , 500, 590

    Cleland C., McGee S. L., 2020, @doi [ ] 10.1093/mnras/staa3267 , 500, 590

  44. [44]

    , keywords =

    Cole S., Lacey C. G., Baugh C. M., Frenk C. S., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03879.x , 319, 168

  45. [45]

    Cole S., et al., 2001, , 326, 255

  46. [46]

    Colless M., 1989, @doi [ ] 10.1093/mnras/237.3.799 , 237, 799

  47. [47]

    E., White M., 2009, @doi [ ] 10.1088/0004-637X/699/1/486 , https://ui.adsabs.harvard.edu/abs/2009ApJ...699..486C 699, 486

    Conroy C., Gunn J. E., White M., 2009, @doi [ ] 10.1088/0004-637X/699/1/486 , https://ui.adsabs.harvard.edu/abs/2009ApJ...699..486C 699, 486

  48. [48]

    L., Songaila A., Hu E

    Cowie L. L., Songaila A., Hu E. M., Cohen J. G., 1996, @doi [ ] 10.1086/118058 , https://ui.adsabs.harvard.edu/abs/1996AJ....112..839C 112, 839

  49. [49]

    Davidzon I., et al., 2017, @doi [ ] 10.1051/0004-6361/201730419 , https://ui.adsabs.harvard.edu/abs/2017A&A...605A..70D 605, A70

  50. [50]

    , keywords =

    De Filippis E., Paolillo M., Longo G., La Barbera F., de Carvalho R. R., Gal R., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18596.x , 414, 2771

  51. [51]

    De Propris R., et al., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06510.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.342..725D 342, 725

  52. [52]

    Dey A., et al., 2019, @doi [ ] 10.3847/1538-3881/ab089d , https://ui.adsabs.harvard.edu/abs/2019AJ....157..168D 157, 168

  53. [53]

    Drory N., Salvato M., Gabasch A., Bender R., Hopp U., Feulner G., Pannella M., 2005, @doi [ ] 10.1086/428044 , 619, L131

  54. [54]

    H., et al., 2023, @doi [ ] 10.1093/mnras/stad3751 , 527, 8598

    Edward A. H., et al., 2023, @doi [ ] 10.1093/mnras/stad3751 , 527, 8598

  55. [55]

    Efron B., Tibshirani R., 1986, Statistical Science, pp 54--75

  56. [56]

    Overview of the JWST Advanced Deep Extragalactic Survey (JADES)

    Eisenstein D. J., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2306.02465 , https://ui.adsabs.harvard.edu/abs/2023arXiv230602465E p. arXiv:2306.02465

  57. [57]

    Etherington J., et al., 2017, @doi [ ] 10.1093/mnras/stw3069 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466..228E 466, 228

  58. [58]

    Euclid Collaboration et al., 2025, @doi [ ] 10.1051/0004-6361/202450810 , https://ui.adsabs.harvard.edu/abs/2025A&A...697A...1E 697, A1

  59. [59]

    Flaugher B., et al., 2015, @doi [ ] 10.1088/0004-6256/150/5/150 , 150, 150

  60. [60]

    Fontana A., et al., 2004, @doi [ ] 10.1051/0004-6361:20035626 , https://ui.adsabs.harvard.edu/abs/2004A&A...424...23F 424, 23

  61. [61]

    Fontana A., et al., 2006, @doi [ ] 10.1051/0004-6361:20065475 , https://ui.adsabs.harvard.edu/abs/2006A&A...459..745F 459, 745

  62. [62]

    W., Lang, D., & Goodman, J

    Foreman-Mackey D., Hogg D. W., Lang D., Goodman J., 2013, @doi [ ] 10.1086/670067 , https://ui.adsabs.harvard.edu/abs/2013PASP..125..306F 125, 306

  63. [63]

    Furlong M., et al., 2015, @doi [ ] 10.1093/mnras/stv852 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.4486F 450, 4486

  64. [64]

    E., et al., 2021, @doi [ ] 10.1093/mnras/stab065 , 502, 2419

    Furnell K. E., et al., 2021, @doi [ ] 10.1093/mnras/stab065 , 502, 2419

  65. [65]

    Gelman, D

    Gelman A., Rubin D. B., 1992, @doi [Statistical Science] 10.1214/ss/1177011136 , https://ui.adsabs.harvard.edu/abs/1992StaSc...7..457G 7, 457

  66. [66]

    E., & Gott, J

    Gunn J. E., Gott J. Richard I., 1972, @doi [ ] 10.1086/151605 , https://ui.adsabs.harvard.edu/abs/1972ApJ...176....1G 176, 1

  67. [67]

    Guo H., Yang X., Lu Y., 2018, @doi [ ] 10.3847/1538-4357/aabc56 , 858, 30

  68. [68]

    M., McKay T

    Hansen S. M., McKay T. A., Wechsler R. H., Annis J., Sheldon E. S., Kimball A., 2005, @doi [ ] 10.1086/444554 , 633, 122

  69. [69]

    W., et al., 2016, @doi [Journal of Low Temperature Physics] 10.1007/s10909-016-1575-z , https://ui.adsabs.harvard.edu/abs/2016JLTP..184..772H 184, 772

    Henderson S. W., et al., 2016, @doi [Journal of Low Temperature Physics] 10.1007/s10909-016-1575-z , https://ui.adsabs.harvard.edu/abs/2016JLTP..184..772H 184, 772

  70. [70]

    Hilton M., et al., 2013, @doi [ ] 10.1093/mnras/stt1535 , 435, 3469

  71. [71]

    Hilton M., et al., 2018, @doi [ ] 10.3847/1538-4365/aaa6cb , 235, 20

  72. [72]

    Hilton M., et al., 2021, @doi [ ] 10.3847/1538-4365/abd023 , 253, 3

  73. [73]

    Ilbert O., et al., 2008, @doi [ ] 10.1088/0004-637X/690/2/1236 , 690, 1236

  74. [74]

    Ilbert O., et al., 2013, @doi [ ] 10.1051/0004-6361/201321100 , https://ui.adsabs.harvard.edu/abs/2013A&A...556A..55I 556, A55

  75. [75]

    Ivezi \'c Z ., et al., 2019, @doi [ ] 10.3847/1538-4357/ab042c , https://ui.adsabs.harvard.edu/abs/2019ApJ...873..111I 873, 111

  76. [76]

    D., et al., 2007, @doi [ ] 10.1086/522960 , 173, 392

    Johnson B. D., et al., 2007, @doi [ ] 10.1086/522960 , 173, 392

  77. [77]

    S., 2008, @doi [ ] 10.1086/526544 , https://ui.adsabs.harvard.edu/abs/2008ApJ...672L.103K 672, L103

    Kawata D., Mulchaey J. S., 2008, @doi [ ] 10.1086/526544 , https://ui.adsabs.harvard.edu/abs/2008ApJ...672L.103K 672, L103

  78. [78]

    C., 2007, @doi [ ] 10.1086/519947 , https://ui.adsabs.harvard.edu/abs/2007ApJ...665.1489K 665, 1489

    Kelly B. C., 2007, @doi [ ] 10.1086/519947 , https://ui.adsabs.harvard.edu/abs/2007ApJ...665.1489K 665, 1489

  79. [79]

    C., 2023, PhD thesis, KwaZulu Natal U

    Kesebonye K. C., 2023, PhD thesis, KwaZulu Natal U

  80. [80]

    Stellar mass -- halo mass relation and star formation efficiency in high-mass halos

    Kravtsov A. V., Vikhlinin A. A., Meshcheryakov A. V., 2018, @doi [Astronomy Letters] 10.1134/S1063773717120015 , https://ui.adsabs.harvard.edu/abs/2018AstL...44....8K 44, 8

Showing first 80 references.