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

T0 review · 3 major / 2 minor · reviewed 2026-05-18 · grok-4.3

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Pith's one-line read Galaxy clusters show stellar mass growth by a factor of 2.5 over the past 7 billion years after accounting for halo mass increase.

desk verdict This ACT DR5 paper gives the first SMF measurements for these SZ clusters at 0.2<z<0.8 and reports a 2.5x rise in stellar mass fraction after halo correction, but the low-mass completeness in DECaLS DR10 at higher redshift is the part that needs the most scrutiny. read the letter →

arxiv 2511.00975 v2 pith:IVRATQJ4 submitted 2025-11-02 astro-ph.GA astro-ph.CO

Damien C. Ragavan , Unnikrishnan Sureshkumar , Matt Hilton , John P. Hughes , Kavilan Moodley , Tony Mroczkowski , Bruce Partridge , Maria Salatino
show 3 more authors
Cristóbal Sifón Eve M. Vavagiakis Edward J. Wollack
This is my paper · ORCID
classification astro-ph.GAastro-ph.CO
keywords galaxyclustersstellarmassfunctionevolutionSunyaev-Zel'dovicheffectclusterassemblycosmicstarformationhistory
checked against Cost.FunctionalEquationFoundation.DimensionForcing
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

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.

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.

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.

Watch

Extended reading notes

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.

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.

Editorial extensions

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.

Reading between the lines

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.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

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 · score 0.0 of 10

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.

Assumptions & free parameters 2 free parameters · 2 assumptions · 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.
assumptions (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.

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Cite this review

Pith. "Pith review of The Atacama Cosmology Telescope: stellar mass growth in massive galaxy clusters from DR5 over the past 7 billion years." pith.science (2026). https://pith.science/paper/IVRATQJ4

@misc{pith2026251100975,
  author       = {Pith},
  title        = {Pith review of: The Atacama Cosmology Telescope: stellar mass growth in massive galaxy clusters from DR5 over the past 7 billion years},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/IVRATQJ4}},
  note         = {Machine review of arXiv:2511.00975}
}
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.

Figures

Figures reproduced from arXiv: 2511.00975 by the authors.

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 displayed.… view at source ↗
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 range for thi… view at source ↗
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 Schechter mo… view at source ↗
Figures from the paper (7 more)
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 e…
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…
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 value…
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]
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 o…
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 …
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 li…

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Lean theorems connected to this paper

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

  • IndisputableMonolith/Cost/FunctionalEquation.lean washburn_uniqueness_aczel unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    We construct redshift- and cluster mass-binned composite cluster stellar mass functions (SMFs), down to M_* = 10^{9.5} M_⊙ … fit a single Schechter function … Schechter+Gaussian model … power-law relation … cluster stellar mass fractions … grown by a factor of 3.3 since z=0.8

  • IndisputableMonolith/Foundation/DimensionForcing.lean alexander_duality_circle_linking unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    The low-mass slope (α) … characteristic stellar mass (M*) … evolution … independent of cluster mass above M_200m ≈ 3×10^{14} M_⊙

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Works this paper leans on

139 extracted references · 139 canonical work pages · cited by 1 Pith paper

  1. [1]

    Aguena, S

    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

    work page doi:10.48550/arxiv.2507.21459 2025

  2. [2]

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

    work page doi:10.3847/1538-4365/ac00b3 2021

  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

    work page doi:10.1093/mnras/stab1956 2021

  4. [4]

    MNRAS , author =

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

    work page doi:10.1093/mnras/stab1036 2021

  5. [5]

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

    work page 1974

  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

    work page Pith review arXiv doi:10.48550/arxiv.1009.2755 2010

  7. [7]

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

    work page doi:10.1111/j.1365-2966.2010.16856.x 2010

  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

    work page doi:10.1051/0004-6361/201424102 2014

Show all 139 references
  1. [9]

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

    2016 doi

  2. [10]

    W., Piffaretti R., B \"o hringer H., Croston J

    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

    2010 doi

  3. [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

    2017 doi

  4. [12]

    K., Glazebrook K., Driver S

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

    2008 doi

  5. [13]

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

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

    2012 doi

  6. [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

    2017 doi

  7. [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

    2006 doi

  8. [16]

    H., Hearin A

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

    2019 doi

  9. [17]

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

    2009 doi

  10. [18]

    F., McIntosh D

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

    2003

  11. [19]

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

    2000 doi

  12. [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

    2019 doi

  13. [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

    2013 doi

  14. [22]

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

    1995 doi

  15. [23]

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

    1999 doi

  16. [24]

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

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

    2003 doi

  17. [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

    2005 doi

  18. [26]

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

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

    2015 doi

  19. [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

    2016

  20. [28]

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

    2022 doi

  21. [29]

    G., Benson A

    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

    2006 doi

  22. [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

    2008 doi

  23. [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

    2011 doi

  24. [32]

    J., Lubin L

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

    2000 doi

  25. [33]

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

    2003 doi

  26. [34]

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

    2006 doi

  27. [35]

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

    2015 doi

  28. [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

    2013 doi

  29. [37]

    C., Kinney A

    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

    2000 doi

  30. [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

    2002 doi

  31. [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

    2019 doi

  32. [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

    2025 doi

  33. [41]

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

    2003 doi

  34. [42]

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

    2018 doi

  35. [43]

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

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

    2020 doi

  36. [44]

    G., Baugh C

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

    2000 doi

  37. [45]

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

    2001

  38. [46]

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

    1989 doi

  39. [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

    2009 doi

  40. [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

    1996 doi

  41. [49]

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

    2017 doi

  42. [50]

    R., Gal R., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18596.x , 414, 2771

    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

    2011 doi

  43. [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

    2003 doi

  44. [52]

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

    2019 doi

  45. [53]

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

    2005 doi

  46. [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

    2023 doi

  47. [55]

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

    1986

  48. [56]

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

    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

    2023 doi arXiv

  49. [57]

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

    2017 doi

  50. [58]

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

    2025 doi

  51. [59]

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

    2015 doi

  52. [60]

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

    2004 doi

  53. [61]

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

    2006 doi

  54. [62]

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

    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

    2013 doi

  55. [63]

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

    2015 doi

  56. [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

    2021 doi

  57. [65]

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

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

    1992 doi

  58. [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

    1972 doi

  59. [67]

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

    2018 doi

  60. [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

    2005 doi

  61. [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

    2016 doi

  62. [70]

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

    2013 doi

  63. [71]

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

    2018 doi

  64. [72]

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

    2021 doi

  65. [73]

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

    2008 doi

  66. [74]

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

    2013 doi

  67. [75]

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

    2019 doi

  68. [76]

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

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

    2007 doi

  69. [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

    2008 doi

  70. [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

    2007 doi

  71. [79]

    C., 2023, PhD thesis, KwaZulu Natal U

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

    2023

  72. [80]

    V., Vikhlinin A

    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

    2018 doi

  73. [81]

    Kroupa P., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04022.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.322..231K 322, 231

    2001 doi

  74. [82]

    W., Mykytyn D., 2016a, The Tractor: Probabilistic astronomical source detection and measurement , Astrophysics Source Code Library, record ascl:1604.008

    Lang D., Hogg D. W., Mykytyn D., 2016a, The Tractor: Probabilistic astronomical source detection and measurement , Astrophysics Source Code Library, record ascl:1604.008

  75. [83]

    W., Schlegel D

    Lang D., Hogg D. W., Schlegel D. J., 2016b, @doi [ ] 10.3847/0004-6256/151/2/36 , https://ui.adsabs.harvard.edu/abs/2016AJ....151...36L 151, 36

    doi

  76. [84]

    B., Tinsley B

    Larson R. B., Tinsley B. M., Caldwell C. N., 1980, @doi [ ] 10.1086/157917 , https://ui.adsabs.harvard.edu/abs/1980ApJ...237..692L 237, 692

    1980 doi

  77. [85]

    Lewis I., et al., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05558.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.334..673L 334, 673

    2002 doi

  78. [86]

    Li C., White S. D. M., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15268.x , 398, 2177

    2009 doi

  79. [87]

    Lidman C., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21984.x , 427, 550

    2012 doi

  80. [88]

    J., Stanford S

    Lin Y.-T., Mohr J. J., Stanford S. A., 2004, @doi [ ] 10.1086/421714 , 610, 745

    2004 doi

  81. [89]

    P., Miller C

    Lin Y.-T., Ostriker J. P., Miller C. J., 2010, @doi [ ] 10.1088/0004-637X/715/2/1486 , https://ui.adsabs.harvard.edu/abs/2010ApJ...715.1486L 715, 1486

    2010 doi

  82. [90]

    H., Bode P., Eisenhardt P

    Lin Y.-T., Brodwin M., Gonzalez A. H., Bode P., Eisenhardt P. R. M., Stanford S. A., Vikhlinin A., 2013, @doi [ ] 10.1088/0004-637X/771/1/61 , 771, 61

    2013 doi

  83. [91]

    Longhetti M., Saracco P., 2009, @doi [ ] 10.1111/j.1365-2966.2008.14375.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.394..774L 394, 774

    2009 doi

  84. [92]

    L., Gonzalez A

    Mancone C. L., Gonzalez A. H., Brodwin M., Stanford S. A., Eisenhardt P. R. M., Stern D., Jones C., 2010, @doi [ ] 10.1088/0004-637X/720/1/284 , https://ui.adsabs.harvard.edu/abs/2010ApJ...720..284M 720, 284

    2010 doi

  85. [93]

    Maraston C., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09270.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.362..799M 362, 799

    2005 doi

  86. [94]

    G., F \"o rster Schreiber N

    Marchesini D., van Dokkum P. G., F \"o rster Schreiber N. M., Franx M., Labb \'e I., Wuyts S., 2009, @doi [ ] 10.1088/0004-637X/701/2/1765 , https://ui.adsabs.harvard.edu/abs/2009ApJ...701.1765M 701, 1765

    2009 doi

  87. [95]

    Marriage T., Atacama Cosmology Telescope Team 2009, in American Astronomical Society Meeting Abstracts \#214. p. 313.04

    2009

  88. [96]

    H., Guo Y., Hertzberg J., Katz N., Mo H

    McIntosh D. H., Guo Y., Hertzberg J., Katz N., Mo H. J., Van Den Bosch F. C., Yang X., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13531.x , 388, 1537

    2008 doi

  89. [97]

    J., McLure R

    McLeod D. J., McLure R. J., Dunlop J. S., Cullen F., Carnall A. C., Duncan K., 2021, @doi [ ] 10.1093/mnras/stab731 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.4413M 503, 4413

    2021 doi

  90. [98]

    Mortlock A., et al., 2014, @doi [ ] 10.1093/mnras/stu2403 , 447, 2

    2014 doi

  91. [99]

    P., Naab T., White S

    Moster B. P., Naab T., White S. D. M., 2012, @doi [ ] 10.1093/mnras/sts261 , 428, 3121

    2012 doi

  92. [100]

    Mroczkowski T., et al., 2019, @doi [ ] 10.1007/s11214-019-0581-2 , https://ui.adsabs.harvard.edu/abs/2019SSRv..215...17M 215, 17

    2019 doi

  93. [101]

    I., Iani E., Kokorev V., van Mierlo S

    Navarro-Carrera R., Rinaldi P., Caputi K. I., Iani E., Kokorev V., van Mierlo S. E., 2024, @doi [ ] 10.3847/1538-4357/ad0df6 , 961, 207

    2024 doi

  94. [102]

    Peng Y.-j., et al., 2010, @doi [ ] 10.1088/0004-637X/721/1/193 , https://ui.adsabs.harvard.edu/abs/2010ApJ...721..193P 721, 193

    2010 doi

  95. [103]

    Pillepich A., et al., 2018, @doi [ ] 10.1093/mnras/stx2656 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473.4077P 473, 4077

    2018 doi

  96. [104]

    R., 1995, @doi [ ] 10.1086/175245 , https://ui.adsabs.harvard.edu/abs/1995ApJ...440...28P 440, 28

    Postman M., Lauer T. R., 1995, @doi [ ] 10.1086/175245 , https://ui.adsabs.harvard.edu/abs/1995ApJ...440...28P 440, 28

    1995 doi

  97. [105]

    Pozzetti L., et al., 2010, @doi [ ] 10.1051/0004-6361/200913020 , https://ui.adsabs.harvard.edu/abs/2010A&A...523A..13P 523, A13

    2010 doi

  98. [106]

    H., Schechter P., 1974, @doi [ ] 10.1086/152650 , https://ui.adsabs.harvard.edu/abs/1974ApJ...187..425P 187, 425

    Press W. H., Schechter P., 1974, @doi [ ] 10.1086/152650 , https://ui.adsabs.harvard.edu/abs/1974ApJ...187..425P 187, 425

    1974 doi

  99. [107]

    L., Ferraro M

    Ragone-Figueroa C., Granato G. L., Ferraro M. E., Murante G., Biffi V., Borgani S., Planelles S., Rasia E., 2018, @doi [ ] 10.1093/mnras/sty1639 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479.1125R 479, 1125

    2018 doi

  100. [108]

    S., Mihos J

    Rudick C. S., Mihos J. C., McBride C. K., 2011, @doi [ ] 10.1088/0004-637X/732/1/48 , 732, 48

    2011 doi

  101. [109]

    Rudnick G., et al., 2009, @doi [ ] 10.1088/0004-637X/700/2/1559 , 700, 1559

    2009 doi

  102. [110]

    E., 1955, @doi [ ] 10.1086/145971 , https://ui.adsabs.harvard.edu/abs/1955ApJ...121..161S 121, 161

    Salpeter E. E., 1955, @doi [ ] 10.1086/145971 , https://ui.adsabs.harvard.edu/abs/1955ApJ...121..161S 121, 161

    1955 doi

  103. [111]

    Salvato M., et al., 2011, @doi [ ] 10.1088/0004-637X/742/2/61 , https://ui.adsabs.harvard.edu/abs/2011ApJ...742...61S 742, 61

    2011 doi

  104. [112]

    Santini P., et al., 2022, @doi [ ] 10.3847/1538-4357/ac9a48 , 940, 135

    2022 doi

  105. [113]

    Schechter P., 1976, @doi [ ] 10.1086/154079 , https://ui.adsabs.harvard.edu/abs/1976ApJ...203..297S 203, 297

    1976 doi

  106. [114]

    Scoville N., et al., 2007, @doi [ ] 10.1086/516585 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172....1S 172, 1

    2007 doi

  107. [115]

    S., Cunha C

    Sheldon E. S., Cunha C. E., Mandelbaum R., Brinkmann J., Weaver B. A., 2012, @doi [ ] 10.1088/0067-0049/201/2/32 , https://ui.adsabs.harvard.edu/abs/2012ApJS..201...32S 201, 32

    2012 doi

  108. [116]

    Song M., et al., 2016, @doi [ ] 10.3847/0004-637X/825/1/5 , https://ui.adsabs.harvard.edu/abs/2016ApJ...825....5S 825, 5

    2016 doi

  109. [117]

    Springel V., Di Matteo T., Hernquist L., 2005a, @doi [ ] 10.1111/j.1365-2966.2005.09238.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.361..776S 361, 776

    2005 doi

  110. [118]

    Springel V., et al., 2005b, @doi [ ] 10.1038/nature03597 , https://ui.adsabs.harvard.edu/abs/2005Natur.435..629S 435, 629

    doi

  111. [119]

    A., et al., 2003, @doi [ ] 10.1038/nature01976 , https://ui.adsabs.harvard.edu/abs/2003Natur.425..264S 425, 264

    Stevens J. A., et al., 2003, @doi [ ] 10.1038/nature01976 , https://ui.adsabs.harvard.edu/abs/2003Natur.425..264S 425, 264

    2003 doi

  112. [120]

    A., Zel'dovich Y

    Sunyaev R. A., Zel'dovich Y. B., 1970, @doi [Astrophysics and Space Science] 10.1007/BF00653471 , https://ui.adsabs.harvard.edu/abs/1970Ap&SS...7....3S 7, 3

    1970 doi

  113. [121]

    J., et al., 2016, @doi [ ] 10.3847/1538-4365/227/2/21 , 227, 21

    Thornton R. J., et al., 2016, @doi [ ] 10.3847/1538-4365/227/2/21 , 227, 21

    2016 doi

  114. [122]

    R., et al., 2014, @doi [ ] 10.1088/0004-637X/783/2/85 , 783, 85

    Tomczak A. R., et al., 2014, @doi [ ] 10.1088/0004-637X/783/2/85 , 783, 85

    2014 doi

  115. [123]

    A., et al., 2004, @doi [ ] 10.1086/423264 , 613, 898

    Tremonti C. A., et al., 2004, @doi [ ] 10.1086/423264 , 613, 898

    2004 doi

  116. [124]

    der Burg van van der Burg R. F. J., et al., 2013, @doi [ ] 10.1051/0004-6361/201321237 , https://ui.adsabs.harvard.edu/abs/2013A&A...557A..15V 557, A15

    2013 doi

  117. [125]

    der Burg van van der Burg R. F. J., Hoekstra H., Muzzin A., Sif \'o n C., Balogh M. L., McGee S. L., 2015, @doi [ ] 10.1051/0004-6361/201425460 , https://ui.adsabs.harvard.edu/abs/2015A&A...577A..19V 577, A19

    2015 doi

  118. [126]

    der Burg van van der Burg R. F. J., McGee S., Aussel H., Dahle H., Arnaud M., Pratt G. W., Muzzin A., 2018, @doi [ ] 10.1051/0004-6361/201833572 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A.140V 618, A140

    2018 doi

  119. [127]

    der Burg van van der Burg R. F. J., et al., 2020, @doi [ ] 10.1051/0004-6361/202037754 , https://ui.adsabs.harvard.edu/abs/2020A&A...638A.112V 638, A112

    2020 doi

  120. [128]

    Vehtari A., Gelman A., Simpson D., Carpenter B., B \"u rkner P.-C., 2021, Bayesian analysis, 16, 667

    2021

  121. [129]

    N., Kauffmann G., White S

    Von der Linden A., Best P. N., Kauffmann G., White S. D. M., 2007, @doi [ ] 10.1111/j.1365-2966.2007.11940.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.379..867V 379, 867

    2007 doi

  122. [130]

    Vulcani B., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2010.17904.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412..246V 412, 246

    2011 doi

  123. [131]

    Vulcani B., et al., 2013, @doi [ ] 10.1051/0004-6361/201118388 , https://ui.adsabs.harvard.edu/abs/2013A&A...550A..58V 550, A58

    2013 doi

  124. [132]

    R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    Weaver J. R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    2023 doi

  125. [133]

    L., Han J

    Wen Z. L., Han J. L., 2015, @doi [ ] 10.1093/mnras/stu2722 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.448....2W 448, 2

    2015 doi

  126. [134]

    R., Tinker J

    Wetzel A. R., Tinker J. L., Conroy C., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21188.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.424..232W 424, 232

    2012 doi

  127. [135]

    White S. D. M., Rees M. J., 1978, @doi [ ] 10.1093/mnras/183.3.341 , https://ui.adsabs.harvard.edu/abs/1978MNRAS.183..341W 183, 341

    1978 doi

  128. [136]

    L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    Wright E. L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    2010 doi

  129. [137]

    H., Driver S

    Wright A. H., Driver S. P., Robotham A. S. G., 2018, @doi [ ] 10.1093/mnras/sty2136 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.3491W 480, 3491

    2018 doi

  130. [138]

    Zhou S., et al., 2025, @doi [ ] 10.1051/0004-6361/202452889 , https://ui.adsabs.harvard.edu/abs/2025A&A...697A..97Z 697, A97

    2025 doi

  131. [139]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed May 18, 2026 · model on record in the stance chip above.