Pith. sign in

REVIEW 3 major objections 7 minor 1 cited by

Explaining JWST counts with galaxy formation models

T0 review · 3 major / 7 minor · reviewed 2026-08-08 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read GALFORM reproduces the JWST near-infrared galaxy counts and traces the break at $m_{AB}\sim 21$ to observer-frame effects: the luminosity-function knee, the comoving volume element, and the $k$-correction.

desk verdict A useful and mostly sound decomposition of the JWST count break, but the 'no early-Universe constraints' warning rests on an unvalidated model n(z). read the letter →

arxiv 2502.04702 v1 pith:GIU35VMP submitted 2025-02-07 astro-ph.GA

Giorgio Manzoni , Tom Broadhurst , Jeremy Lim , Tao Liu , George Smoot , Carlton M. Baugh , Scott Tompkins , Rogier Windhorst
show 13 more authors
Simon Driver Timothy Carleton Brenda Frye Leo Fung Jiashuo Zhang Seth H. Cohen Christopher J. Conselice Norman A. Grogin Rolf A. Jansen Anton M. Koekemoer Rafael Ortiz III Norbert Pirzkal Christopher N. A. Willmer
This is my paper · ORCID
classification astro-ph.GA
keywords galaxynumbercountsJWSTNIRCamGALFORMsemi-analyticalmodelluminosityfunctionk-correctionPEARLSsurveyformationnear-infrared
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

This paper argues that the sharp bend seen in JWST's near-infrared galaxy number counts at apparent magnitude $m_{AB}\sim 21$ does not require new physics. The GALFORM semi-analytical galaxy-formation model, calibrated on local and moderate-redshift observations, reproduces the PEARLS counts across the NIRCam filters from 0.9 to 4.4 microns without any retuning, including the fact that the break is sharper at longer wavelengths. Using the model, the authors trace the break to three ordinary ingredients: the intrinsic knee in the rest-frame luminosity function, the growth of the comoving volume element with redshift, and the redshift-dependent $k$-correction, whose frequency part sets how strongly the break appears in each filter. The practical upshot is that, down to the PEARLS limit of $m_{AB}\sim 28$, the counts are dominated by galaxies at $z\lesssim 2$, so the faint counts alone cannot constrain early-universe physics or the nature of dark matter.

What carries the argument

The carrying device is the decomposition of the $k$-correction into a redshift part, $K(z)=-2.5\log_{10}(1+z)$, and a frequency part, $K(\nu,\nu_0)=-2.5\log_{10}(L_\nu/L_{\nu_0})$, applied to GALFORM's rest-frame luminosity functions to convert them into observer-frame apparent magnitudes. The argument also relies on the Monte Carlo merger-tree version of GALFORM, built on the extended Press-Schechter formalism, which lets the authors check convergence in the predicted counts, and on the bulge-to-total stellar mass ratio ($B/T$) as a morphology proxy. This machinery is what separates intrinsic galaxy evolution from frame-shift effects and isolates the compression of the luminosity functions that sets the knee.

What would settle it

Measure secure photometric or spectroscopic redshifts for galaxies in the PEARLS fields down to $m_{AB}\sim 28$ and compare the resulting redshift distribution with GALFORM's prediction shown in Figure 3. If galaxies just below the knee turn out to be predominantly at $z>2$, or if the mean redshift rises steeply toward the survey limit, the claim that faint counts are dominated by low-redshift galaxies would be contradicted.

Watch

Extended reading notes

Core claim

The central claim is that the double power-law shape of the near-infrared galaxy counts, with a knee at $m_{AB}\sim 21$ that becomes more pronounced from F090W to F444W, is produced by standard galaxy-formation physics and observer-frame projection rather than by any exotic process. The paper shows that GALFORM's predicted counts match the PEARLS data and its fits well, with only a small offset at the faint end of F444W, and that the slope changes are reproduced in every NIRCam filter. It then deconstructs the counts into rest-frame luminosity functions and demonstrates that the break arises from the combination of the break in the luminosity function, the change in comoving volume per solid angle with redshift, and the $k$-correction; in particular, the frequency part of the $k$-correction, $K(\nu,\nu_0)$, compresses the observer-frame luminosity functions in a way that makes the break stronger at longer wavelengths. In the model, bulge-dominated galaxies populate the bright side of the break and disk-dominated galaxies the faint side, with a characteristic stellar mass of roughly $10^{10}\,M_\odot$, and the mean redshift of the contributing galaxies stays below $z\sim 2$ up to $m_{AB}\sim 28$. The authors therefore conclude that the faint end of the number counts is not a useful probe of the early universe.

Load-bearing premise

The reasoning stands on GALFORM's predicted redshift distribution of faint galaxies: the paper shows the model's $n(z)$ but does not compare it with observed photometric or spectroscopic redshift distributions, so if the model puts too few faint galaxies at high redshift or misplaces them in apparent magnitude, the conclusion that $z<2$ galaxies drive the counts would be a model artifact rather than a property of the universe.

Editorial extensions

If this is right

  • The observed knee in the JWST near-infrared counts is a success for existing semi-analytical galaxy-formation models, not evidence for new physics.
  • Faint number counts down to $m_{AB}\sim 28$ cannot, by themselves, constrain high-redshift galaxy populations, dark matter models, or early-universe physics.
  • The wavelength dependence of the break follows from the sign and redshift evolution of the frequency part of the $k$-correction: positive at short wavelengths and negative at long wavelengths.
  • The break marks a population transition: bulge-dominated galaxies dominate brighter than the knee and disk-dominated galaxies dominate fainter, with a characteristic stellar mass near $10^{10}\,M_\odot$.
  • The shape of the counts is set mainly by galaxies with $z\lesssim 2$, so deeper surveys are needed before faint counts can probe higher redshifts.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A direct test would compare GALFORM's predicted redshift distribution with photometric or spectroscopic redshifts in the PEARLS fields; this can be done without waiting for new surveys.
  • The same decomposition should apply to future deep near-infrared surveys, such as those planned for Roman, predicting where the break moves as filters and depth change.
  • If the low-redshift dominance holds, searches for extreme high-redshift galaxies should rely on photometric-redshift selection or other statistics rather than total-number-count excesses.
  • The claim that faint counts do not constrain dark matter models could be tested by running GALFORM variants with altered dark-matter power spectra and checking whether count predictions change only below the PEARLS magnitude limit.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 7 minor

Summary. The paper uses the GALFORM semi-analytical galaxy formation model to reproduce the JWST PEARLS near-infrared number counts in the NIRCam filters from 0.9 to 4.4 um. It claims that the observed break at m_AB~21 is a combination of the intrinsic break in the rest-frame luminosity function, the redshift-dependent comoving volume element, and the frequency-dependent part of the k-correction, with the k-correction modulating the strength of the break across filters. Using model outputs, the paper further concludes that the counts up to the PEARLS limit m_AB~28 are mainly driven by galaxies with z<2, so the faint counts cannot strongly constrain early-universe physics. The authors also decompose the counts by bulge-to-total mass ratio and stellar mass to identify the populations dominating different apparent magnitude ranges.

Significance. If the conclusions hold, the paper provides a valuable and physically transparent explanation for a prominent JWST-observed feature, showing that standard galaxy formation physics can account for the counts without invoking new physics. The internal decomposition into rest-frame luminosity functions, volume effects, and k-corrections is a useful pedagogical and interpretive framework, and the appendix convincingly demonstrates that the frequency part of the k-correction changes the break strength with filter. A notable strength is that GALFORM's parameters were calibrated to independent data, so the prediction is not fitted to the PEARLS counts. However, the central claims rest on a visually assessed model-data comparison and on a model-predicted redshift distribution that is not validated against observations.

major comments (3)
  1. [Sec. 3.1, Fig. 1] The claimed agreement between GALFORM and the PEARLS counts is presented only visually. The grey data points are shown without error bars, and no quantitative measure such as chi-square, residuals, or a scatter statistic is provided. The text states the model reproduces the counts 'quite accurately' with a 'small offset' in the F444W faint end, but the significance and possible origin of this offset are not assessed. Because the conclusion that no new physics is needed depends directly on this agreement, a quantitative comparison is required.
  2. [Sec. 3.2, Figs. 2, 3, 6] The claim that the counts up to m_AB~28 are mainly driven by z<2 galaxies, and the associated conclusion that faint counts cannot constrain early-universe physics, rests on the model's predicted redshift distribution n(z). This n(z) is never compared with observed photometric or spectroscopic redshift distributions in the JWIDF or El Gordo parallel fields, nor with other JWST surveys. If the model underproduces or misplaces high-redshift galaxies in apparent magnitude, the low-redshift dominance could be a model artifact rather than a property of the universe. A comparison of the predicted apparent-magnitude-binned n(z) with available observational data, or at least a quantitative estimate of the maximum z>2 contribution at m_AB<28, is needed to support the early-Universe claim.
  3. [Sec. 2.1 and Sec. 3.1] The paper states that Monte Carlo merger trees are used to 'thoroughly investigate the convergence of the counts' and that the timestep can be chosen to ensure convergence at high redshift, but no convergence tests are shown. The predicted faint-end counts and the low-mass galaxy population are central to the analysis, particularly for the F444W offset and the claimed z<2 dominance. The authors should demonstrate convergence of the number counts with respect to halo mass resolution and timestep, or state where such tests are reported.
minor comments (7)
  1. [Sec. 4] Typo: 'mAM' should be 'm_AB' (or 'mAB'). In the same section, 'ranging from 0.7 um to 4.4 um' is inconsistent with the abstract's '0.9 um'; the NIRCam filters used begin at F090W, so the stated range should be consistent.
  2. [Fig. 1] The grey data points have no plotted error bars. If observational uncertainties are available from Windhorst et al. (2023), they should be shown to support the visual model-data comparison.
  3. [Sec. 3.2] The term 'compression of the luminosity functions' is used to explain the wavelength dependence of the break but is not precisely defined. A formal definition or a quantitative measure of the spread in apparent magnitude of the observer-frame LFs would improve clarity.
  4. [Sec. 3.6, Eqs. (4) and (7)] The notation uses lowercase k for the flux correction factor and uppercase K for the magnitude correction. Please clarify this distinction explicitly, as the two symbols appear together in the derivation.
  5. [Sec. 2.2] The phrase 'Windhorst et al. checked' should be 'Windhorst et al. (2023) checked' for citation clarity.
  6. [Fig. Sets 1-3] The paper refers to online Figure Sets 1, 2, and 3 for the remaining filters, but these are not included in the arXiv version. Please ensure they are accessible to readers, for example as supplementary material, or include at least a representative subset in the main text.
  7. [Sec. 3.1] The phrase 'This also excludes the possibility of blaming new physics for this clear feature' is too strong. A model's success shows consistency with standard physics but does not logically exclude all alternative models; a softer phrasing such as 'renders new physics unnecessary' would be more appropriate.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the GALFORM parameters were calibrated to independent constraints, the PEARLS counts are an external prediction, and the explanatory decomposition follows from standard distance and k-correction relations.

full rationale

The derivation chain is self-contained. GALFORM's adjustable parameters were calibrated to a set of primary observational constraints that does not include the PEARLS NIRCam number counts: the paper lists optical bJ and near-infrared K-band luminosity functions at z=0, rest-frame K-band luminosity functions at z=0.5, 1 and 3, submillimeter and far-infrared counts, and rest-frame far-UV luminosity functions at z=3 and 6. The orange model curves in Fig. 1 are predictions, not fits, because the PEARLS counts were not among the calibration constraints. The explanatory decomposition in Fig. 2 is an arithmetic rearrangement of the model outputs rather than a new fitted relation: number counts are obtained by integrating the model luminosity functions over redshift after applying the distance modulus and k-correction (Eqs. 5 and 6), and the paper explicitly separates the calibrated luminosity-function break from the redshift-dependent volume element and redshift-dependent k-correction. The claim that the counts are dominated by z<2 objects up to m_AB~28 is an emergent model prediction (Fig. 3), not an input; whether or not that prediction is well validated by observed redshift distributions is a correctness concern, not circularity. The self-citations that appear (e.g., Cowley et al. 2018 for earlier GALFORM count predictions and Windhorst et al. 2023 as the source of the observational counts) are used as background and as an external observational benchmark, respectively, and neither carries the central argument alone.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

No new free parameters are introduced in this paper. The central claim depends on the GALFORM calibration parameters, Planck cosmology, and model SEDs, all inherited from prior work. The paper introduces no new entities.

free parameters (3)
  • Supernova feedback parameters V_SN and gamma_SN = Values were calibrated in Lacey et al. (2016) and are not quoted in this paper.
    These control the efficiency of supernova feedback and set the faint-end slope and break of the luminosity function, which is one of the three causes of the counts break.
  • AGN feedback efficiency parameters = Values were calibrated in Lacey et al. (2016) and are not quoted in this paper.
    These set the bright end of the luminosity function, which determines the bright slope of the counts and the location of the break.
  • Dust attenuation and SED parameters = Values were calibrated in Lacey et al. (2016) and are not quoted in this paper.
    The wavelength dependence of the k-correction, and therefore the stronger break at longer wavelengths, depends on the rest-frame SEDs and dust attenuation in the model.
assumptions (4)
  • domain assumption Planck cosmology with standard Omega_m and Omega_Lambda is assumed.
    Invoked in Section 3.2 when computing the comoving volume element and distance moduli.
  • domain assumption GALFORM's calibrated physical prescriptions accurately describe galaxy formation and evolution.
    All predictions and the LF decomposition are produced by GALFORM, whose parameters were calibrated by hand to external constraints as described in Section 2.1.
  • domain assumption Monte Carlo merger trees built from Extended Press-Schechter theory are adequate for number counts.
    Section 2.1 argues that convergence can be checked with this approach, but the counts still inherit any inaccuracies of the EPS merger rates.
  • domain assumption The SEDs from the stellar population synthesis and dust model accurately represent real galaxy SEDs for k-corrections.
    The frequency part of the k-correction, the driver of the wavelength-dependent compression in Section 3.6, is computed from model SEDs that are compared only indirectly to observations.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Explaining JWST counts with galaxy formation models." pith.science (2026). https://pith.science/paper/GIU35VMP

@misc{pith2026250204702,
  author       = {Pith},
  title        = {Pith review of: Explaining JWST counts with galaxy formation models},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GIU35VMP}},
  note         = {Machine review of arXiv:2502.04702}
}
read the original abstract

A distinct power-law break is apparent m_AB approximately 21 in the deep Near-Infrared PEARLS-JWST galaxy counts. The break becomes more pronounced at longer wavelengths, with the counts slope flattening smoothly with apparent magnitude in the shortest band used at 0.9 microns, trending towards an increasingly broken slope by the longest wavelength passband of JWST NIRCam, 4.4 microns. This behaviour is remarkably well predicted by the GALFORM semi-analytical model of galaxy formation. We use the model to diagnose the origin of this behaviour. We find that the features that are responsible for the break are: 1) the inherent break in the luminosity function; 2) the change in the volume element with redshift and 3) the redshift-dependent nature of the k-correction. We study the contribution to these effects by early and late-type galaxies, using as a proxy for morphology the bulge-to-total stellar mass ratio. We find that the way in which ellipticals populate the bright end of the luminosity function while spirals dominate the faint end is preserved in the galaxy number counts, with a characteristic stellar mass at the break of approximately 10^10 M_sun. We also find that the shape of the number counts is mainly driven by galaxies with relatively low redshift (z < 2) for the PEARLS observational limit of m_AB < 28. We give a comprehensive description of why the galaxy number counts in the near-infrared PEARLS-JWST observation look the way they do and which population of galaxies is dominant at each apparent magnitude.

Figures

Figures reproduced from arXiv: 2502.04702 by the authors.

Figure 1
Figure 1. Number counts predicted using GALFORM (orange lines) together with the data collected in Windhorst et al. (2023) (grey dots) and the respective double power-law fits (blue lines). In the left panel, we plot the counts for the shortest wavelength filter used by Windhorst et al. 2023, which is the NIRCam F090W, while in the right panel, we show the longest wavelength counts, F444W. The break in the counts’ slope is mo… view at source ↗
Figure 2
Figure 2. Luminosity functions predicted by GALFORM at closely spaced redshifts in the range 0 < z < 2, as shown by the key, for the long wavelength filter F444W. Left: we plot the luminosity functions in the traditional rest frame absolute magnitudes vs number of objects per unit magnitude and unit volume. Right: we plot the luminosity function in the units of the number counts, i.e. observer frame apparent magnitudes vs num… view at source ↗
Figure 3
Figure 3. Mean redshift as a function of the apparent magnitude for the objects simulated in three representative NIRCam filters, F090W (blue line), F200W (green line) and F444W (red line). Error bars are the 25th and 75th per￾centiles of the associated redshift distribution for the related apparent magnitude. The two vertical dashed lines indicate approximately the location of the break in the counts at an apparent magnitude… view at source ↗
Figures from the paper (13 more)
Figure 4
Figure 4. Figure 4: shows the luminosity function in three represen￾tative outputs of the simulation, i.e. z = 0.04, z = 1.04 and z = 2.02., for the NIRCam filter F444W. As sug￾gested by the left panel of [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: Simulated galaxy number counts in the NIR￾Cam filter F444W. Different line colours are used to indi￾cate morphology through the B/T proxy, as shown by the legend. The green line is for all objects. The blue line is for disk-dominated galaxies with B/T ≤ 0.5. The red li…
Figure 6
Figure 6. Figure 6: Redshift distributions for the objects plotted in [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Left: simulated galaxy number counts in the filter F444W, built by using luminosity functions of objects satisfying different criteria indicated by the line colour: black, all objects, all the other lines are for objects with a bulge-total mass ratio greater than 0.5 (…
Figure 8
Figure 8. Figure 8: Galaxy number counts (top row) and relative redshift distributions (bottom row) split in bins of stellar mass to study the contribution of each stellar mass bin to each apparent magnitude. The analysis is repeated for the shortest wavelength NIRCam filter available in …
Figure 9
Figure 9. Figure 9: Comparison between the observer (red line) and rest frame (blue line) SEDs of two example galaxies at different redshifts. The difference between the rest and observer frame is the frequency term of the k-correction as in Eq. 11 (see text for more details). This figure…
Figure 10
Figure 10. Figure 10: Galaxy number counts in the observer (left panel) and rest frame (right panel) for all the Wide NIRCam filters. at different wavelengths and it is visible as well how the F444W get a steeper slope in the bright part compared to all the other counts, after receiving a …
Figure 11
Figure 11. Figure 11: Comparison between the number counts in the observer frame and in the rest frame to study the effect of the change in reference frame controlled by the k-correction [PITH_FULL_IMAGE:figures/full_fig_p019_11.png]
Figure 12
Figure 12. Figure 12: Frequency part of the k-correction as a function of redshift for all the Wide NIRCam filters, see Eq. 10. Median and standard deviation from the simulated sample at different snapshots [PITH_FULL_IMAGE:figures/full_fig_p020_12.png]
Figure 13
Figure 13. Figure 13: Constituent luminosity function in the rest frame apparent magnitude in filter F444W. We can see that without taking into account the change in the reference frame (the effect of the k-correction) the LFs do not compress around the break with a resulting break in the …
Figure 14
Figure 14. Figure 14: Luminosity functions in rest frame absolute magnitudes at z = 0 for all the NIRCam Wide filters. The intrinsic luminosities of galaxies vary depending on the filter with a peak between F150W and F200W. This corresponds to the peak of the Integrated Galaxy Light (IGL) …
Figure 15
Figure 15. Figure 15: Apparent magnitude of the break in the number counts as a function of wavelengths (black line). The trend is a consequence of the intrinsic luminosity of the luminosity functions in [PITH_FULL_IMAGE:figures/full_fig_p021_15.png]
Figure 16
Figure 16. Figure 16: Apparent magnitudes of the break in the power law for different luminosity functions as a function of redshift (left panel) and wavelength (right panel). To fully exploit the power of the simulation, in [PITH_FULL_IMAGE:figures/full_fig_p022_16.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Baryonic mass budgets in the central regions of the Bullet Cluster and their consistency with strong lensing in MOND

    astro-ph.GA 2026-06 unverdicted novelty 6.0 of 10

    MOND strong-lensing masses in the Bullet Cluster’s three BCG cores lie between lower and upper IGIMF baryonic mass estimates from JWST photometry.

Reference graph

Works this paper leans on

54 extracted references · 22 canonical work pages · cited by 1 Pith paper

  1. [1]

    M., Gonzalez-Perez, V., Lagos, C

    Baugh, C. M., Gonzalez-Perez, V., Lagos, C. d. P., et al. 2019, MNRAS, 483, 4922, doi: 10.1093/mnras/sty3427

    doi:10.1093/mnras/sty3427 2019

  2. [3]

    1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    doi:10.1051/aas:1996164 1996

  3. [4]

    W., & Longair, M

    Blain, A. W., & Longair, M. S. 1993, MNRAS, 264, 509, doi: 10.1093/mnras/264.2.509

    doi:10.1093/mnras/264.2.509 1993

  4. [5]

    R., & Roweis, S

    Blanton, M. R., & Roweis, S. 2007, AJ, 133, 734, doi: 10.1086/510127

    doi:10.1086/510127 2007

  5. [6]

    J., Ellis, R

    Broadhurst, T. J., Ellis, R. S., & Glazebrook, K. 1992, Nature, 355, 55, doi: 10.1038/355055a0

    work page doi:10.1038/355055a0 1992

  6. [8]

    D., Wu, C

    Coleman, G. D., Wu, C. C., & Weedman, D. W. 1980, ApJS, 43, 393, doi: 10.1086/190674

    doi:10.1086/190674 1980

  7. [9]

    Extragalactic Background Light: Measurements and Applications

    Cooray, A. 2016, Extragalactic Background Light: Measurements and Applications. https://arxiv.org/abs/1602.03512

    work page Pith review arXiv 2016

  8. [10]

    L., Gardner, J

    Cowie, L. L., Gardner, J. P., Hu, E. M., et al. 1994, ApJ, 434, 114, doi: 10.1086/174709

    work page doi:10.1086/174709 1994

Show all 54 references
  1. [11]

    L., Songaila, A., Hu, E

    Cowie, L. L., Songaila, A., Hu, E. M., & Cohen, J. G. 1996, AJ, 112, 839, doi: 10.1086/118058

    1996 doi

  2. [12]

    Lacey, C. G. 2018, MNRAS, 474, 2352, doi: 10.1093/mnras/stx2897

    2018 doi

  3. [13]

    Davies, L. J. M., Thorne, J. E., Robotham, A. S. G., et al. 2021, MNRAS, 506, 256, doi: 10.1093/mnras/stab1601

    2021 doi

  4. [14]

    Disney, M. J. 1994, MNRAS, 266, 155, doi: 10.1093/mnras/266.1.155

    1994 doi

  5. [15]

    P., Windhorst, R

    Driver, S. P., Windhorst, R. A., Ostrander, E. J., et al. 1995, ApJL, 449, L23, doi: 10.1086/309637

    1995 doi

  6. [16]

    P., Windhorst, R

    Driver, S. P., Windhorst, R. A., Phillipps, S., & Bristow, P. D. 1996, ApJ, 461, 525, doi: 10.1086/177079

    1996 doi

  7. [17]

    P., Hill, D

    Driver, S. P., Hill, D. T., Kelvin, L. S., et al. 2011, MNRAS, 413, 971, doi: 10.1111/j.1365-2966.2010.18188.x

    2011

  8. [18]

    P., Andrews, S

    Driver, S. P., Andrews, S. K., Davies, L. J., et al. 2016, ApJ, 827, 108, doi: 10.3847/0004-637X/827/2/108

    2016 doi

  9. [19]

    J., Baugh, C

    Elliott, E. J., Baugh, C. M., & Lacey, C. G. 2021, MNRAS, 506, 4011, doi: 10.1093/mnras/stab1837

    2021 doi

  10. [20]

    1995, MNRAS, 275, L19, doi: 10.1093/mnras/275.1.L19 23

    Glazebrook, K., Ellis, R., Santiago, B., & Griffiths, R. 1995, MNRAS, 275, L19, doi: 10.1093/mnras/275.1.L19 23

    1995 doi

  11. [21]

    Hogg, D. W. 1999, arXiv e-prints, astro, doi: 10.48550/arXiv.astro-ph/9905116

    1999 doi arXiv

  12. [22]

    1934, ApJ, 79, 8, doi: 10.1086/143517

    Hubble, E. 1934, ApJ, 79, 8, doi: 10.1086/143517

    1934 doi

  13. [23]

    R., Fong, R., Shanks, T., Ellis, R

    Jones, L. R., Fong, R., Shanks, T., Ellis, R. S., & Peterson, B. A. 1991, MNRAS, 249, 481, doi: 10.1093/mnras/249.3.481

    1991 doi

  14. [24]

    Kapteyn, J. C. 1922, ApJ, 55, 302, doi: 10.1086/142670

    1922 doi

  15. [25]

    M., Diaferio, A., & White, S

    Kauffmann, G., Colberg, J. M., Diaferio, A., & White, S. D. M. 1999, MNRAS, 303, 188, doi: 10.1046/j.1365-8711.1999.02202.x

    1999

  16. [26]

    P., Bellstedt, S., et al

    Koushan, S., Driver, S. P., Bellstedt, S., et al. 2021, MNRAS, 503, 2033, doi: 10.1093/mnras/stab540

    2021 doi

  17. [27]

    1993, MNRAS, 262, 627, doi: 10.1093/mnras/262.3.627

    Lacey, C., & Cole, S. 1993, MNRAS, 262, 627, doi: 10.1093/mnras/262.3.627

    1993 doi

  18. [28]

    G., Baugh, C

    Lacey, C. G., Baugh, C. M., Frenk, C. S., et al. 2016, MNRAS, 462, 3854, doi: 10.1093/mnras/stw1888

    2016 doi

  19. [29]

    J., Le Fevre, O., Hammer, F., & Crampton, D

    Lilly, S. J., Le Fevre, O., Hammer, F., & Crampton, D. 1996, ApJL, 460, L1, doi: 10.1086/309975

    1996 doi

  20. [30]

    J., Wu, C

    Ling, C.-T., Kim, S. J., Wu, C. K. W., et al. 2022, MNRAS, 517, 853, doi: 10.1093/mnras/stac2716

    2022 doi

  21. [31]

    S., Bose, S., et al

    Lu, S., Frenk, C. S., Bose, S., et al. 2024, arXiv e-prints, arXiv:2406.02672, doi: 10.48550/arXiv.2406.02672

    2024 doi arXiv

  22. [32]

    2024, arXiv e-prints, arXiv:2405.04601, doi: 10.48550/arXiv.2405.04601

    Madar, M., Baugh, C., & Shi, D. 2024, arXiv e-prints, arXiv:2405.04601, doi: 10.48550/arXiv.2405.04601

    2024 doi arXiv

  23. [33]

    2014, ARA&A, 52, 415, doi: 10.1146/annurev-astro-081811-125615

    Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415, doi: 10.1146/annurev-astro-081811-125615

    2014 doi

  24. [34]

    2000, MNRAS, 312, L9, doi: 10.1046/j.1365-8711.2000.03268.x

    Madau, P., & Pozzetti, L. 2000, MNRAS, 312, L9, doi: 10.1046/j.1365-8711.2000.03268.x

    2000

  25. [35]

    M., Norberg, P., et al

    Manzoni, G., Baugh, C. M., Norberg, P., et al. 2024, MNRAS, 530, 1394, doi: 10.1093/mnras/stae659

    2024 doi

  26. [36]

    Marr, J. H. 2023, Galaxies, 11, 65, doi: 10.3390/galaxies11030065

    2023 doi

  27. [37]

    Metcalfe, N., Shanks, T., Fong, R., & Jones, L. R. 1991, MNRAS, 249, 498, doi: 10.1093/mnras/249.3.498

    1991 doi

  28. [38]

    1995, MNRAS, 273, 257, doi: 10.1093/mnras/273.2.257

    Metcalfe, N., Shanks, T., Fong, R., & Roche, N. 1995, MNRAS, 273, 257, doi: 10.1093/mnras/273.2.257

    1995 doi

  29. [39]

    Noonan, T. W. 1971, PASP, 83, 31, doi: 10.1086/129059

    1971 doi

  30. [40]

    2008, MNRAS, 383, 557, doi: 10.1111/j.1365-2966.2007.12517.x Planck Collaboration, Ade, P

    Parkinson, H., Cole, S., & Helly, J. 2008, MNRAS, 383, 557, doi: 10.1111/j.1365-2966.2007.12517.x Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2014, A&A, 571, A16, doi: 10.1051/0004-6361/201321591

    2008

  31. [41]

    Robotham, A. S. G., Davies, L. J. M., Driver, S. P., et al. 2018, MNRAS, 476, 3137, doi: 10.1093/mnras/sty440

    2018 doi

  32. [42]

    2024, arXiv e-prints, arXiv:2406.04437, doi: 10.48550/arXiv.2406.04437

    Sajkov, L., Sajina, A., Pope, A., et al. 2024, arXiv e-prints, arXiv:2406.04437, doi: 10.48550/arXiv.2406.04437

    2024 doi arXiv

  33. [43]

    1961, ApJ, 133, 355, doi: 10.1086/147041

    Sandage, A. 1961, ApJ, 133, 355, doi: 10.1086/147041

    1961 doi

  34. [44]

    H., van Rhijn, P

    Seares, F. H., van Rhijn, P. J., Joyner, M. C., & Richmond, M. L. 1925, ApJ, 62, 320, doi: 10.1086/142940

    1925 doi

  35. [45]

    Shanks, T., Stevenson, P. R. F., Fong, R., & MacGillivray, H. T. 1984, MNRAS, 206, 767, doi: 10.1093/mnras/206.4.767

    1984 doi

  36. [46]

    1932, Annals of Harvard College Observatory, 88, 41

    Shapley, H., & Ames, A. 1932, Annals of Harvard College Observatory, 88, 41

    1932

  37. [47]

    A., Alberts, S., Rieke, G

    Stone, M. A., Alberts, S., Rieke, G. H., et al. 2024, ApJ, 972, 62, doi: 10.3847/1538-4357/ad6308

    2024 doi

  38. [48]

    Tinsley, B. M. 1977, ApJ, 211, 621, doi: 10.1086/154971 —. 1980, ApJ, 241, 41, doi: 10.1086/158315

    1977 doi

  39. [49]

    Tyson, J. A. 1988, AJ, 96, 1, doi: 10.1086/114786

    1988 doi

  40. [50]

    A., Cohen, S

    Windhorst, R. A., Cohen, S. H., Hathi, N. P., et al. 2011, ApJS, 193, 27, doi: 10.1088/0067-0049/193/2/27

    2011 doi

  41. [51]

    A., Cohen, S

    Windhorst, R. A., Cohen, S. H., Jansen, R. A., et al. 2023, AJ, 165, 13, doi: 10.3847/1538-3881/aca163

    2023 doi

  42. [52]

    Wu, C. K. W., Ling, C.-T., Goto, T., et al. 2023, MNRAS, 523, 5187, doi: 10.1093/mnras/stad1769

    2023 doi

  43. [53]

    B., et al

    Yang, G., Papovich, C., Bagley, M. B., et al. 2023, ApJL, 956, L12, doi: 10.3847/2041-8213/acfaa0

    2023 doi

  44. [54]

    K., et al

    Yasuda, N., Fukugita, M., Narayanan, V. K., et al. 2001, AJ, 122, 1104, doi: 10.1086/322093

    2001 doi

  45. [55]

    Yung, L. Y. A., Somerville, R. S., Ferguson, H. C., et al. 2022, MNRAS, 515, 5416, doi: 10.1093/mnras/stac2139

    2022 doi

  46. [56]

    1937, ApJ, 86, 217, doi: 10.1086/143864

    Zwicky, F. 1937, ApJ, 86, 217, doi: 10.1086/143864

    1937 doi

Pith tools

Reviewed August 8, 2026 · model on record in the stance chip above.