Pith. sign in

REVIEW 4 major objections 4 minor 2 cited by

Early dark energy, tuned only by CMB data, reproduces JWST's surplus of bright, massive, disky galaxies at cosmic dawn, then fades back to standard cosmology by z≈3.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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

T0 review · deepseek-v4-flash

2026-08-04 15:21 UTC pith:AWWVXAOQ

load-bearing objection First hydro sims of EDE show a robust EDE-vs-LCDM offset in high-z galaxies, but the absolute match to JWST is degenerate with star-formation efficiency and dust choices. the 4 major comments →

arxiv 2509.19427 v1 pith:AWWVXAOQ submitted 2025-09-23 astro-ph.GA astro-ph.COhep-ph

The Cosmic Rush Hour: Rapid Formation of Bright, Massive, Disky, Star-Forming Galaxies as Signatures of Early-Universe Physics

Xuejian Shen , Oliver Zier , Mark Vogelsberger , Michael Boylan-Kolchin , Lars Hernquist , Sandro Tacchella , Rohan P. Naidu This is my paper
classification astro-ph.GA astro-ph.COhep-ph
keywords early dark energyhigh-redshift galaxiesJWSTUV luminosity functionstellar mass functiondisk galaxiescosmological hydrodynamic simulationsHubble tension
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper argues that a pre-recombination burst of early dark energy—an ingredient originally proposed to resolve the Hubble tension—also explains the surprisingly abundant, massive, star-forming disk galaxies JWST sees at z≈4–14. It does this with two large cosmological hydrodynamic simulations, one in standard ΛCDM and one with EDE parameters fixed by CMB fits; the galaxy formation model is the same out-of-the-box, low-redshift-calibrated model in both runs. In the EDE run, UV luminosity functions and stellar mass functions agree with JWST measurements with essentially no recalibration, and the number density of disky galaxies rises by about half a dex at z≈6–7. Predictions converge to ΛCDM at z≲3, preserving known low-redshift successes. The paper concludes that early-universe physics can simultaneously address several JWST anomalies and the Hubble tension.

Core claim

The central claim is that EDE's accelerated early structure formation, driven mainly by an enhanced small-scale matter power spectrum with higher spectral index, primordial amplitude, and matter density, boosts the abundance of bright and massive galaxies enough to remove the 0.5–1 dex shortfall that standard ΛCDM simulations show against JWST at z≳10. Because EDE decays after recombination, the same run converges back to ΛCDM predictions at z≲3 with ≲0.2 dex differences. The faster assembly of massive halos also makes stellar and gaseous disks appear earlier: number densities of disky galaxies are about half a dex larger at z≈6–7, while the disky fraction at fixed stellar mass is unchanged,

What carries the argument

The central object is early dark energy as a scalar field with an axion-like potential V(φ)≈[1−cos(φ/f)]³, with parameters taken from CMB fits that also yield H0≈74.8 km/s/Mpc. The field acts as a cosmological constant before recombination and then dilutes; its observable imprint is an enhanced small-scale linear power spectrum (higher n_s and A_s) that accelerates the collapse of the first halos. The simulations couple this cosmology to the IllustrisTNG galaxy formation model in the Arepo code, with identical subgrid physics in EDE and ΛCDM runs, so any galaxy differences come purely from the altered expansion history and power spectrum.

Load-bearing premise

The galaxy formation model, calibrated at low redshift, is assumed to stay accurate at z=4–14 with no recalibration; if real high-redshift star formation or feedback differs systematically, the EDE simulation's agreement with JWST could be coincidence rather than evidence for EDE.

What would settle it

Measure the UV luminosity function at z≈12–14 with a larger, purely spectroscopic sample: if the bright-end number density turns out to be roughly 0.5 dex lower than current JWST photometric estimates, the EDE match disappears. Conversely, a robust measurement of the clustering bias of bright galaxies at z≈6–8—EDE predicts lower bias than ΛCDM at fixed luminosity—would discriminate the two.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

Share X Bluesky LinkedIn Reddit HN

If this is right

  • JWST's excess of UV-bright galaxies at z≈10–14 does not require exotic star-formation physics; a CMB-consistent EDE cosmology with standard galaxy formation reproduces the observed counts.
  • Massive galaxy candidates in the COSMOS-Web field at z≈11–12, which appear as >3σ outliers in ΛCDM, fall within about 2–3σ of EDE predictions.
  • Stellar and gaseous disks form earlier in EDE, so ALMA and JWST disk detections at z≈6–8 become expected rather than surprising, with gaseous disk number densities roughly a factor of three higher at z≈6–7.
  • At z≲3 the EDE run converges to ΛCDM within ≲0.2 dex, preserving the established low-redshift successes of the standard model.
  • The model predicts fewer massive quenched galaxies than ΛCDM at z≳3.5, supporting the paper's view that the early-quenching puzzle is likely a baryonic or black-hole-physics limitation, not a cosmological one.

Where Pith is reading between the lines

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

  • Any beyond-ΛCDM model that increases the pre-recombination expansion rate generically tilts the small-scale power spectrum upward, so high-redshift galaxy abundance could serve as a broad probe of early-universe physics beyond EDE itself.
  • The paper's reduced-bias prediction—bright galaxies less clustered in EDE at fixed luminosity—offers a direct observational test: galaxy clustering at z≈6–10 from JWST fields could distinguish EDE from baryonic solutions like feedback-free starbursts or top-heavy initial mass functions.
  • If high-z star formation or feedback is later shown to be systematically different, the EDE match could be coincidental; the paper's own shortfall in quenched galaxies already signals that the subgrid black-hole model limits the comparison.
  • Lyman-α forest and 21-cm observations, usually used to rule out suppressed small-scale power, could be turned around to constrain enhanced small-scale power of the kind EDE produces.

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

4 major / 4 minor

Summary. This manuscript presents the first large-scale cosmological hydrodynamic simulations of an Early Dark Energy (EDE) cosmology using the IllustrisTNG galaxy formation model, alongside a matched ΛCDM simulation. EDE parameters are taken from a CMB fit (Smith et al. 2022) and are not adjusted to galaxy data. The central claim is that EDE, through an enhanced small-scale matter power spectrum, boosts the abundance of UV-bright and massive galaxies at z ≃ 4–14, bringing simulated UV luminosity functions and stellar mass functions into 'excellent agreement' with JWST measurements, while predictions converge to ΛCDM by z ≲ 3. The paper also reports earlier emergence of disky galaxies in EDE and a surprising delay in quenched galaxies due to the younger universe. The comparison is supported by an empirical model and by an appendix isolating the power-spectrum change from the H0 change.

Significance. If the headline claim holds, this is an important result: it demonstrates that modifications to pre-recombination cosmology can simultaneously ease several JWST 'too early, too massive, too disk-like' tensions without retuning the IllustrisTNG baryonic model. The controlled EDE-versus-ΛCDM comparison with identical subgrid physics is a genuine strength, as is the authors' use of an independent empirical model and the clear decomposition of the effect into power-spectrum versus H0 changes. The paper is also commendably transparent about the quenched-galaxy underprediction. However, the absolute 'excellent agreement with JWST' is less secure than the differential EDE-ΛCDM signal: it depends on post-processing choices (zero dust attenuation at z ≥ 10, empirically calibrated dust at z < 10) and on the IllustrisTNG star-formation efficiency at high redshift, which Fig. 4 shows is at the lower envelope of current models. These degeneracies do not invalidate the differential statement, but they weaken the inference that EDE is required by the JWST abundance data.

major comments (4)
  1. [§3.1, Fig. 5; §2.3–2.4] The claimed 'excellent agreement' at z ≥ 10 relies on setting dust attenuation to zero at z ≥ 10 while using empirically calibrated dust at lower redshifts. This is an upper-limit choice in brightness: simulated galaxies do contain dust, and the motivation 'observed blue UV slopes' is partly circular when the goal is to match observed UV luminosity functions. The EDE-ΛCDM differential remains robust, but the absolute normalization of the z = 12–14 UV LFs, which is a headline result, is not. Please show the intrinsic A_UV distribution of the simulated galaxies at z ≥ 10, or test the sensitivity of Fig. 5 to a small nonzero attenuation (e.g., A_UV = 0.2–0.5 mag).
  2. [§2.2, Fig. 4; §3.1] The inference that EDE is needed to match JWST is degenerate with the high-redshift star-formation efficiency. The IllustrisTNG SFE in Fig. 4 is nearly redshift-independent and lies at the lower envelope of published models; FIREbox, thesan-zoom, and the FFB scenario show SFEs 0.5–1 dex higher at M_halo ~ 10^10–10^11 M_sun. Because the EDE boost to the halo mass function is roughly 0.2–0.8 dex over the relevant range, a modest upward revision of TNG's high-z SFE in ΛCDM could produce the same UV LF and SMF as EDE+TNG. The 'essentially no additional calibration' claim is therefore relative to TNG, not to the space of plausible baryonic models. Please quantify this degeneracy—e.g., show what a ΛCDM run with a 0.3–0.5 dex higher SFE would predict—or identify an observable that breaks it (clustering, stellar mass functions at fixed UV luminosity, or [C II] kinematics).
  3. [§3.1, Fig. 5; Table 2] The conclusions at z = 9–14 are based on a single (100 cMpc)^3 simulation volume per cosmology. In Fig. 5 the shaded 'one galaxy per mag' region indicates that the bright-end bins at z = 12 and 14 contain very few galaxies, and the Poisson errors do not include cosmic variance. The empirical model and Eq. (4) provide a useful volume correction, but the claimed 'almost perfect' agreement at z ≳ 12 could be affected substantially by sample variance. Please quantify cosmic variance—for example, by using the empirical model to estimate the expected field-to-field scatter in the z = 12–14 UV LF bins, or by running a second realization of at least one cosmology.
  4. [Abstract; §3.4, Fig. 10] The abstract's phrase 'simultaneously reconcile multiple high-redshift challenges' is too broad in light of the paper's own finding that quenched galaxies at M* ≳ 10^10 M_sun are underpredicted by an order of magnitude at z ≳ 3 in both cosmologies, and that EDE delays rather than accelerates quenching. The authors are appropriately candid in §3.4 and §4, but the abstract and conclusions should explicitly state that EDE does not address the early-quenching tension and may worsen it. This does not undermine the UV LF and SMF results, but it does limit the 'multiple challenges' claim.
minor comments (4)
  1. [§2.4] The empirical-model parameter σ_UV = 0.75 mag is described as 'assumed' and 'purely for interpretation.' Since this scatter directly affects the LF shape and the stellar-mass-function derivation in Eq. (1), please state its source and the sensitivity of the empirical-model curves to it.
  2. [§2.1, Table 1] The adopted EDE parameters from Smith et al. (2022) are now less favored by Planck PR4+BAO and are more aggressive than the ACT DR6/DESI-based fits cited in §2.1. The paper discusses this, but the abstract and conclusions should more clearly present the simulations as a proof-of-principle for a broader class of early-universe models, not as evidence for the specific best-fit model.
  3. [§3.3] The disk thresholds (D/T)_* = 0.7 and (D/T)_gas = 0.8 are reasonable but somewhat arbitrary. A brief sensitivity test (e.g., varying the thresholds by ±0.1) would help confirm that the half-dex EDE-ΛCDM difference in disky-galaxy number density is not driven by the exact cut.
  4. [§3.2, Fig. 7] The Schechter-function fits at z ≥ 5 fix the break mass to 10^11 M_sun. This is justified, but the choice could affect the integrated stellar-mass-density comparison; a short statement of the resulting systematic uncertainty would be useful.

Circularity Check

0 steps flagged

Central EDE-vs-ΛCDM comparison is externally anchored by CMB fits and a fixed low-z-calibrated galaxy formation model; no circular reduction found.

full rationale

The paper's headline inference—that EDE improves agreement with JWST galaxy abundance measurements—rests on two external anchors, not on the target data. The EDE parameters are taken from Smith et al. (2022), a CMB fit independent of the JWST abundance data, and the IllustrisTNG galaxy formation model is an out-of-the-box model calibrated at low redshift (§2.2). Both the ΛCDM and EDE runs use identical subgrid physics, so the EDE-vs-ΛCDM differential comparison is not a fitted prediction: the baryonic model is common to both and the SFE is explicitly shown to be indistinguishable between runs (Fig. 4). The paper does not fit the UV luminosity function or stellar mass function to JWST data and then re-predict them. The only potentially load-bearing modeling choice for the high-redshift absolute comparison is the assumption of no dust attenuation at z≥10, justified by observed blue UV slopes of the same high-z galaxies (§2.3). This is an input assumption motivated by an independent observable (UV spectral slope), not a parameter fitted to the luminosity-function amplitude; it does not reduce the predicted LF to an observed LF by construction. The empirical model from the authors' prior work (Shen et al. 2023, 2024b) is used mainly for interpretation and volume corrections, not as the evidence for EDE. The paper also explicitly acknowledges the quenched-galaxy underprediction as a limitation of the SMBH subgrid model (§3.4), and it discusses degeneracies with baryonic alternatives (§4). Self-citations appear frequently but are not load-bearing for the central claim: the EDE model and its parameters are externally cited, and the IllustrisTNG model is externally defined. No uniqueness theorem is imported from the authors, and no ansatz is smuggled in via self-citation. Accordingly, there is no significant circularity; the score reflects only the minor use of author's prior empirical model as a comparison tool, which is not load-bearing.

Axiom & Free-Parameter Ledger

4 free parameters · 5 axioms · 0 invented entities

The paper introduces no new physical entities; the EDE scalar field is a pre-existing cosmological model. The free parameters listed are choices in post-processing or empirical comparison, not fits to the JWST data being explained. The main unfalsifiable-to-this-study input is the trust placed in the IllustrisTNG subgrid model at high redshift.

free parameters (4)
  • UV variability scatter sigma_UV = 0.75 mag
    Set to mimic the low burstiness of IllustrisTNG in the empirical model used for volume corrections; affects the width, not the central value, of the UV luminosity function.
  • Dust attenuation constants C0, C1 = C0 ~ 4.9, C1 ~ 2
    Adopted from Bowler et al. (2024) for the Meurer A_UV-beta relation and applied to simulation predictions at z<10, affecting the absolute normalization of the UV LFs.
  • Disk selection thresholds = (D/T)_star > 0.7, (D/T)_gas > 0.8
    Chosen by hand to match kinematic studies of low-redshift Milky Way-mass galaxies and ALMA samples; directly sets the disky galaxy number densities.
  • sSFR quenched cut = sSFR < 0.2 / t_H(z)
    Widely used literature cut to separate star-forming and quenched galaxies; affects the quenched fractions reported in Section 3.4.
axioms (5)
  • domain assumption EDE cosmology with Smith et al. (2022) best-fit parameters (f_EDE ~ 0.179, log10 z_c ~ -3.528, theta_i ~ -2.806, m ~ 4.38e-28 eV, etc.)
    The model is fixed by CMB data, but Section 2.1 acknowledges that more recent ACT DR6/Planck/DESI analyses favor a weaker EDE; the qualitative conclusions are argued to survive.
  • domain assumption The IllustrisTNG subgrid physics, calibrated at low redshift, is valid at z=4-14 without recalibration
    Section 2.2 and Section 4: the out-of-the-box TNG model is used; the paper itself notes it underpredicts quenched galaxies by an order of magnitude, indicating model limitations.
  • standard math The linear matter power spectrum from CAMB's early-quintessence implementation, with adiabatic and Gaussian primordial perturbations, is correct
    Initial conditions and transfer functions in Section 2.1 rely on this; the authors verify Axiclass gives identical results.
  • domain assumption Empirical dust attenuation relations (Meurer et al. 1999; Bouwens et al. 2014; Cullen et al. 2023) apply to simulated galaxies at z<10
    Section 2.4: these observed relations are applied to the simulations, and the no-dust assumption at z>=10 is motivated by blue UV slopes of the observed population.
  • standard math Halo mass function and halo accretion-rate fitting formulae (Press-Schechter/Sheth-Tormen, Rodriguez-Puebla et al. 2016) are accurate for EDE cosmologies
    Used in the empirical model for volume corrections and comparison; Appendix A verifies the mass function matches the simulation subhalo masses at z=12.

pith-pipeline@v1.3.0-alltime-deepseek · 31726 in / 12062 out tokens · 105276 ms · 2026-08-04T15:21:53.805625+00:00 · methodology

0 comments
Cite this review

Pith. "Pith review of The Cosmic Rush Hour: Rapid Formation of Bright, Massive, Disky, Star-Forming Galaxies as Signatures of Early-Universe Physics." pith.science (2026). https://pith.science/paper/AWWVXAOQ

@misc{pith2026250919427,
  author       = {Pith},
  title        = {Pith review of: The Cosmic Rush Hour: Rapid Formation of Bright, Massive, Disky, Star-Forming Galaxies as Signatures of Early-Universe Physics},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AWWVXAOQ}},
  note         = {Machine review of arXiv:2509.19427}
}
Share X Bluesky LinkedIn Reddit HN
read the original abstract

Early JWST observations have revealed a high-redshift universe more vibrant than predicted by canonical galaxy-formation models within $\Lambda$CDM, showing an excess of ultraviolet(UV)-bright, massive, and morphologically mature galaxies. Departures from $\Lambda$CDM prior to recombination can imprint signatures on non-linear structure formation at high redshift. In this paper, we investigate one such scenario - Early Dark Energy, originally proposed to resolve the Hubble tension - and its implications for these high-redshift challenges. We present the first large-scale cosmological hydrodynamic simulations of these models. Modifications to the pre-recombination expansion history accelerate early structure formation and produce UV luminosity and stellar mass functions in excellent agreement with JWST measurements, requiring essentially no additional calibrations. Predictions converge to $\Lambda$CDM at lower redshifts ($z \lesssim 3$), thereby preserving all successes of $\Lambda$CDM. This model also accelerates the emergence of stellar and gaseous disks, increasing their number densities by $\sim 0.5$ dex at $z\simeq 6$-7, primarily due to the higher abundance of massive galaxies. Taken together, these results demonstrate how early-universe physics can simultaneously reconcile multiple high-redshift challenges and the Hubble tension while retaining the core achievements of $\Lambda$CDM. This opens a pathway to constraining a broad class of beyond-$\Lambda$CDM models with forthcoming observations.

Figures

Figures reproduced from arXiv: 2509.19427 by Lars Hernquist, Mark Vogelsberger, Michael Boylan-Kolchin, Oliver Zier, Rohan P. Naidu, Sandro Tacchella, Xuejian Shen.

Figure 1
Figure 1. Figure 1: Ratios between the dimensionless linear matter power spectrum (Δ 2 ) of the EDE and ΛCDM models. The vertical dotted line indicates the fundamental mode of the box size (𝑘fd ≡ 2𝜋/𝐿box) in ΛCDM. The vertical dashed line shows roughly the Nyquist limit of our simulation, 𝑘Nq ≡ (2𝜋/𝐿box ) (𝑁 1/3 dm /2), where 𝑁 1/3 dm is the number of dark matter par￾ticles per dimension. The top axis shows the halo mass at 𝑧… view at source ↗
Figure 2
Figure 2. Figure 2: Dark matter surface density in a 25 cMpc field of view (1/4 of the simulation box length) centered on the most massive halo at 𝑧 ≃ 9. The thickness of the layer for projection is also 25 cMpc. The left and right panels show the dark matter maps in the ΛCDM and EDE runs. Dark matter clustering appears stronger in the EDE model. We overlay the location of moderately bright (intrinsic 𝑀UV ≤ −18 mag) and very … view at source ↗
Figure 3
Figure 3. Figure 3: Similar to [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Star-formation efficiency (SFE) versus halo mass. We show our ΛCDM simulation results as open circles with 1𝜎 error bars at 𝑧 ≃ 5, 7, and 9. The EDE run yields identical results. We compare them to the SFE assumed in our empirical model (Shen et al. 2023, 2024b) and other choices in literature (Mason et al. 2015; Behroozi et al. 2019; Harikane et al. 2022; Li et al. 2023; Feldmann et al. 2025; Shen et al. … view at source ↗
Figure 5
Figure 5. Figure 5: Galaxy rest-frame UV luminosity function at 𝑧 ≃ 4 − 14 in the ΛCDM and EDE simulations. Binned estimations from the simulations are shown with solid circles, and Poisson errors are computed using the formula in Gehrels (1986). Dust attenuation has been applied at 𝑧 < 10 as described in Section 2.4. We compare the results to the observational constraints compiled in Shen et al. (2024b). The predictions from… view at source ↗
Figure 6
Figure 6. Figure 6: Galaxy stellar mass function at 𝑧 = 3, 5, 7, and 9 in the ΛCDM and EDE runs. They are shown in solid circles, and Poisson errors are computed using the formula from Gehrels (1986). We compare them to the pre-JWST observational constraints from Santini et al. (2012); Ilbert et al. (2013); Song et al. (2016); Davidzon et al. (2017); Stefanon et al. (2021); Weaver et al. (2023) (in solid gray points) and more… view at source ↗
Figure 7
Figure 7. Figure 7: Cosmic stellar mass density versus redshift. We integrate the Schechter function fitted at each redshift with 𝑀min = 108 M⊙ and 𝑀max = 1013 M⊙ to obtain the cosmic stellar mass density. The top two axes show the age of the universe in the two cosmologies. Observational constraints from Santini et al. (2012); Ilbert et al. (2013); Song et al. (2016); Stefanon et al. (2021); Weaver et al. (2023); Weibel et a… view at source ↗
Figure 8
Figure 8. Figure 8: Maximum stellar mass of galaxies within a volume probed by the COSMOS-Web survey (≃ 0.28 deg2 used in Casey et al. 2024). The solid lines in the top and bottom panels show the estimates based on our ΛCDM and EDE simulations, respectively. The shaded regions display 1, 2, 3𝜎 dispersion computed using the extreme value statistics (Lovell et al. 2023a) and the dashed lines show the theory limit, which is the … view at source ↗
Figure 9
Figure 9. Figure 9: Top: Number density of disky galaxies in the universe versus redshift in the ΛCDM and EDE runs. We show the number densities of massive galaxies (𝑀∗ ≥ 109.5 M⊙) with stellar disks in solid lines, and those of galaxies (𝑀∗ ≥ 109 M⊙) with gaseous disks in dashed lines. Disky galaxies in EDE appear systematically earlier, and the number density of disky galaxies is enhanced by roughly half a dex at 𝑧 ≳ 6. Dot… view at source ↗
Figure 10
Figure 10. Figure 10: Number density of massive quenched galaxies versus redshift in the ΛCDM and EDE simulations. We show the number density of massive galaxies (𝑀∗ ≥ 1010 M⊙) in dashed lines, massive and quenched galax￾ies in solid lines, and massive SMBHs (𝑀BH ≥ 108 M⊙) in dotted lines. The quenched galaxy number density is compared to the observational esti￾mates reported in Schreiber et al. (2018); Merlin et al. (2019); C… view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

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

  1. Resolving galaxy formation in the early Universe with BonFIRE and CampFIRE

    astro-ph.GA 2026-05 unverdicted novelty 5.0

    BonFIRE and CampFIRE simulations show bursty clustered star formation in early galaxies and predict UV luminosity functions matching observations at faint magnitudes with a turnover at M_UV approx -14 but overpredicti...

  2. Dark Secrets of Baryons: Illuminating Dark Matter-Baryon Interactions with JWST

    hep-ph 2025-11 conditional novelty 5.0

    JWST ultraviolet luminosity function data currently provide the strongest upper limits on velocity-dependent (∝v^{-2}) dark matter–proton scattering for sub-GeV dark matter.

Reference graph

Works this paper leans on

262 extracted references · 3 canonical work pages · cited by 2 Pith papers · 2 internal anchors

  1. [1]

    Abdalla E., et al., 2022, @doi [Journal of High Energy Astrophysics] 10.1016/j.jheap.2022.04.002 , https://ui.adsabs.harvard.edu/abs/2022JHEAp..34...49A 34, 49

    doi:10.1016/j.jheap.2022.04.002 2022

  2. [2]

    arXiv:2203.08128

    Ach \'u carro A., et al., 2022, @doi [arXiv e-prints] 10.48550/arXiv.2203.08128 , https://ui.adsabs.harvard.edu/abs/2022arXiv220308128A p. arXiv:2203.08128

    Pith/arXiv arXiv doi:10.48550/arxiv.2203.08128 2022

  3. [3]

    J., et al., 2023, @doi [ ] 10.1093/mnras/stac3347 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.4755A 518, 4755

    Adams N. J., et al., 2023, @doi [ ] 10.1093/mnras/stac3347 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.4755A 518, 4755

    doi:10.1093/mnras/stac3347 2023

  4. [4]

    J., et al., 2024, @doi [ ] 10.3847/1538-4357/ad2a7b , https://ui.adsabs.harvard.edu/abs/2024ApJ...965..169A 965, 169

    Adams N. J., et al., 2024, @doi [ ] 10.3847/1538-4357/ad2a7b , https://ui.adsabs.harvard.edu/abs/2024ApJ...965..169A 965, 169

    doi:10.3847/1538-4357/ad2a7b 2024

  5. [5]

    B., et al., 2023, @doi [ ] 10.3847/1538-4357/acef21 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956...61A 956, 61

    Akins H. B., et al., 2023, @doi [ ] 10.3847/1538-4357/acef21 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956...61A 956, 61

    doi:10.3847/1538-4357/acef21 2023

  6. [6]

    B., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.10341 , https://ui.adsabs.harvard.edu/abs/2024arXiv240610341A p

    Akins H. B., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.10341 , https://ui.adsabs.harvard.edu/abs/2024arXiv240610341A p. arXiv:2406.10341

    Pith/arXiv arXiv doi:10.48550/arxiv.2406.10341 2024

  7. [7]

    Alberts S., et al., 2024, @doi [ ] 10.3847/1538-4357/ad66cc , https://ui.adsabs.harvard.edu/abs/2024ApJ...975...85A 975, 85

    doi:10.3847/1538-4357/ad66cc 2024

  8. [8]

    Aloni D., Berlin A., Joseph M., Schmaltz M., Weiner N., 2022, @doi [ ] 10.1103/PhysRevD.105.123516 , https://ui.adsabs.harvard.edu/abs/2022PhRvD.105l3516A 105, 123516

    doi:10.1103/physrevd.105.123516 2022

  9. [9]

    Arvanitaki A., Dimopoulos S., Dubovsky S., Kaloper N., March-Russell J., 2010, @doi [ ] 10.1103/PhysRevD.81.123530 , https://ui.adsabs.harvard.edu/abs/2010PhRvD..81l3530A 81, 123530

    doi:10.1103/physrevd.81.123530 2010

  10. [10]

    Atek H., et al., 2023, @doi [ ] 10.1093/mnras/stac3144 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.1201A 519, 1201

    doi:10.1093/mnras/stac3144 2023

  11. [11]

    Barnes J., Hut P., 1986, @doi [ ] 10.1038/324446a0 , https://ui.adsabs.harvard.edu/abs/1986Natur.324..446B 324, 446

    doi:10.1038/324446a0 1986

  12. [12]

    Bashinsky S., Seljak U., 2004, @doi [ ] 10.1103/PhysRevD.69.083002 , https://ui.adsabs.harvard.edu/abs/2004PhRvD..69h3002B 69, 083002

    doi:10.1103/physrevd.69.083002 2004

  13. [13]

    S., Wechsler R

    Behroozi P. S., Wechsler R. H., Conroy C., 2013, @doi [ ] 10.1088/0004-637X/770/1/57 , https://ui.adsabs.harvard.edu/abs/2013ApJ...770...57B 770, 57

    doi:10.1088/0004-637x/770/1/57 2013

  14. [14]

    H., Hearin A

    Behroozi P., Wechsler R. H., Hearin A. P., Conroy C., 2019, @doi [ ] 10.1093/mnras/stz1182 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.3143B 488, 3143

    doi:10.1093/mnras/stz1182 2019

  15. [15]

    F., McIntosh D

    Bell E. F., McIntosh D. H., Katz N., Weinberg M. D., 2003, @doi [ ] 10.1086/378847 , https://ui.adsabs.harvard.edu/abs/2003ApJS..149..289B 149, 289

    doi:10.1086/378847 2003

  16. [16]

    Belokurov V., Kravtsov A., 2022, @doi [ ] 10.1093/mnras/stac1267 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514..689B 514, 689

    doi:10.1093/mnras/stac1267 2022

  17. [17]

    Bland-Hawthorn J., Tepper-Garcia T., Agertz O., Freeman K., 2023, @doi [ ] 10.3847/1538-4357/acc469 , https://ui.adsabs.harvard.edu/abs/2023ApJ...947...80B 947, 80

    doi:10.3847/1538-4357/acc469 2023

  18. [18]

    R., Cole S., Efstathiou G., Kaiser N., 1991, @doi [ ] 10.1086/170520 , https://ui.adsabs.harvard.edu/abs/1991ApJ...379..440B 379, 440

    Bond J. R., Cole S., Efstathiou G., Kaiser N., 1991, @doi [ ] 10.1086/170520 , https://ui.adsabs.harvard.edu/abs/1991ApJ...379..440B 379, 440

    doi:10.1086/170520 1991

  19. [19]

    J., et al., 2014, @doi [ ] 10.1088/0004-637X/793/2/115 , https://ui.adsabs.harvard.edu/abs/2014ApJ...793..115B 793, 115

    Bouwens R. J., et al., 2014, @doi [ ] 10.1088/0004-637X/793/2/115 , https://ui.adsabs.harvard.edu/abs/2014ApJ...793..115B 793, 115

    doi:10.1088/0004-637x/793/2/115 2014

  20. [20]

    J., et al., 2021, @doi [ ] 10.3847/1538-3881/abf83e , https://ui.adsabs.harvard.edu/abs/2021AJ....162...47B 162, 47

    Bouwens R. J., et al., 2021, @doi [ ] 10.3847/1538-3881/abf83e , https://ui.adsabs.harvard.edu/abs/2021AJ....162...47B 162, 47

    doi:10.3847/1538-3881/abf83e 2021

  21. [21]

    J., et al., 2022, @doi [ ] 10.3847/1538-4357/ac5a4a , https://ui.adsabs.harvard.edu/abs/2022ApJ...931..160B 931, 160

    Bouwens R. J., et al., 2022, @doi [ ] 10.3847/1538-4357/ac5a4a , https://ui.adsabs.harvard.edu/abs/2022ApJ...931..160B 931, 160

    doi:10.3847/1538-4357/ac5a4a 2022

  22. [22]

    Bouwens R., Illingworth G., Oesch P., Stefanon M., Naidu R., van Leeuwen I., Magee D., 2023a, @doi [ ] 10.1093/mnras/stad1014 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.1009B 523, 1009

    doi:10.1093/mnras/stad1014

  23. [23]

    J., et al., 2023b, @doi [ ] 10.1093/mnras/stad1145 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.1036B 523, 1036

    Bouwens R. J., et al., 2023b, @doi [ ] 10.1093/mnras/stad1145 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.1036B 523, 1036

    doi:10.1093/mnras/stad1145

  24. [24]

    Bowler R. A. A., Jarvis M. J., Dunlop J. S., McLure R. J., McLeod D. J., Adams N. J., Milvang-Jensen B., McCracken H. J., 2020, @doi [ ] 10.1093/mnras/staa313 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.2059B 493, 2059

    doi:10.1093/mnras/staa313 2020

  25. [25]

    Bowler R. A. A., et al., 2024, @doi [ ] 10.1093/mnras/stad3578 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.5808B 527, 5808

    doi:10.1093/mnras/stad3578 2024

  26. [26]

    Boylan-Kolchin M., 2023, @doi [Nature Astronomy] 10.1038/s41550-023-01937-7 , https://ui.adsabs.harvard.edu/abs/2023NatAs...7..731B 7, 731

    doi:10.1038/s41550-023-01937-7 2023

  27. [27]

    Boylan-Kolchin M., 2025, @doi [ ] 10.1093/mnras/staf471 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.538.3210B 538, 3210

    doi:10.1093/mnras/staf471 2025

  28. [28]

    R., 2021, @doi [ ] 10.1093/mnras/stab1521 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.2764B 505, 2764

    Boylan-Kolchin M., Weisz D. R., 2021, @doi [ ] 10.1093/mnras/stab1521 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.2764B 505, 2764

    doi:10.1093/mnras/stab1521 2021

  29. [29]

    Brout D., et al., 2022, @doi [ ] 10.3847/1538-4357/ac8e04 , https://ui.adsabs.harvard.edu/abs/2022ApJ...938..110B 938, 110

    doi:10.3847/1538-4357/ac8e04 2022

  30. [30]

    L., Norman M

    Bryan G. L., Norman M. L., 1998, @doi [ ] 10.1086/305262 , https://ui.adsabs.harvard.edu/abs/1998ApJ...495...80B 495, 80

    doi:10.1086/305262 1998

  31. [31]

    S., Boylan-Kolchin M., 2017, @doi [ ] 10.1146/annurev-astro-091916-055313 , https://ui.adsabs.harvard.edu/abs/2017ARA&A..55..343B 55, 343

    Bullock J. S., Boylan-Kolchin M., 2017, @doi [ ] 10.1146/annurev-astro-091916-055313 , https://ui.adsabs.harvard.edu/abs/2017ARA&A..55..343B 55, 343

    doi:10.1146/annurev-astro-091916-055313 2017

  32. [32]

    Calabr \`o A., et al., 2024, @doi [ ] 10.3847/1538-4357/ad7602 , https://ui.adsabs.harvard.edu/abs/2024ApJ...975..245C 975, 245

    doi:10.3847/1538-4357/ad7602 2024

  33. [33]

    C., McLure R

    Carnall A. C., McLure R. J., Dunlop J. S., Dav \'e R., 2018, @doi [ ] 10.1093/mnras/sty2169 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.4379C 480, 4379

    doi:10.1093/mnras/sty2169 2018

  34. [34]

    C., et al., 2023a, @doi [ ] 10.1093/mnras/stad369 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.3974C 520, 3974

    Carnall A. C., et al., 2023a, @doi [ ] 10.1093/mnras/stad369 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.3974C 520, 3974

    doi:10.1093/mnras/stad369

  35. [35]

    C., et al., 2023b, @doi [ ] 10.1038/s41586-023-06158-6 , https://ui.adsabs.harvard.edu/abs/2023Natur.619..716C 619, 716

    Carnall A. C., et al., 2023b, @doi [ ] 10.1038/s41586-023-06158-6 , https://ui.adsabs.harvard.edu/abs/2023Natur.619..716C 619, 716

    doi:10.1038/s41586-023-06158-6

  36. [36]

    Carniani S., et al., 2024, @doi [ ] 10.1038/s41586-024-07860-9 , https://ui.adsabs.harvard.edu/abs/2024Natur.633..318C 633, 318

    doi:10.1038/s41586-024-07860-9 2024

  37. [37]

    M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad2075 , https://ui.adsabs.harvard.edu/abs/2024ApJ...965...98C 965, 98

    Casey C. M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad2075 , https://ui.adsabs.harvard.edu/abs/2024ApJ...965...98C 965, 98

    doi:10.3847/1538-4357/ad2075 2024

  38. [38]

    Castellano M., et al., 2022, @doi [ ] 10.3847/2041-8213/ac94d0 , https://ui.adsabs.harvard.edu/abs/2022ApJ...938L..15C 938, L15

    doi:10.3847/2041-8213/ac94d0 2022

  39. [39]

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

    doi:10.1086/376392 2003

  40. [40]

    Chandra V., et al., 2024, @doi [ ] 10.3847/1538-4357/ad5b60 , https://ui.adsabs.harvard.edu/abs/2024ApJ...972..112C 972, 112

    doi:10.3847/1538-4357/ad5b60 2024

  41. [41]

    Chatzikos M., et al., 2023, @doi [ ] 10.22201/ia.01851101p.2023.59.02.12 , https://ui.adsabs.harvard.edu/abs/2023RMxAA..59..327C 59, 327

    doi:10.22201/ia.01851101p.2023.59.02.12 2023

  42. [42]

    Chen X., 2010, @doi [Advances in Astronomy] 10.1155/2010/638979 , https://ui.adsabs.harvard.edu/abs/2010AdAst2010E..72C 2010, 638979

    doi:10.1155/2010/638979 2010

  43. [43]

    Chittenden H. G., Glazebrook K., Nanayakkara T., Kawinwanichakij L., Lagos C., Kimmig L., Remus R.-S., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2504.19696 , https://ui.adsabs.harvard.edu/abs/2025arXiv250419696C p. arXiv:2504.19696

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2504.19696 2025

  44. [44]

    G., 2018, @doi [ ] 10.1093/mnras/sty1229 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.3994C 478, 3994

    Clauwens B., Schaye J., Franx M., Bower R. G., 2018, @doi [ ] 10.1093/mnras/sty1229 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.3994C 478, 3994

    doi:10.1093/mnras/sty1229 2018

  45. [45]

    Hierarchical assembly impedes the inference of stellar mass growth histories for individual galaxies

    Cochrane R. K., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2509.02700 , https://ui.adsabs.harvard.edu/abs/2025arXiv250902700C p. arXiv:2509.02700

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2509.02700 2025

  46. [46]

    arXiv:2204.02989

    Conroy C., et al., 2022, @doi [arXiv e-prints] 10.48550/arXiv.2204.02989 , https://ui.adsabs.harvard.edu/abs/2022arXiv220402989C p. arXiv:2204.02989

    Pith/arXiv arXiv doi:10.48550/arxiv.2204.02989 2022

  47. [47]

    Cortese L., et al., 2016, @doi [ ] 10.1093/mnras/stw1891 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.463..170C 463, 170

    doi:10.1093/mnras/stw1891 2016

  48. [48]

    R., Hutter A., Dayal P., Gottl \"o ber S., Heintz K

    Cueto E. R., Hutter A., Dayal P., Gottl \"o ber S., Heintz K. E., Mason C., Trebitsch M., Yepes G., 2024, @doi [ ] 10.1051/0004-6361/202349017 , https://ui.adsabs.harvard.edu/abs/2024A&A...686A.138C 686, A138

    doi:10.1051/0004-6361/202349017 2024

  49. [49]

    Cullen F., et al., 2023, @doi [ ] 10.1093/mnras/stad073 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520...14C 520, 14

    doi:10.1093/mnras/stad073 2023

  50. [50]

    Cullen F., et al., 2024, @doi [ ] 10.1093/mnras/stae1211 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531..997C 531, 997

    doi:10.1093/mnras/stae1211 2024

  51. [51]

    Curtis-Lake E., et al., 2023, @doi [Nature Astronomy] 10.1038/s41550-023-01918-w , https://ui.adsabs.harvard.edu/abs/2023NatAs.tmp...66C

    doi:10.1038/s41550-023-01918-w 2023

  52. [52]

    Cyr-Racine F.-Y., Sigurdson K., 2013, @doi [ ] 10.1103/PhysRevD.87.103515 , https://ui.adsabs.harvard.edu/abs/2013PhRvD..87j3515C 87, 103515

    doi:10.1103/physrevd.87.103515 2013

  53. [53]

    L., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.21863 , https://ui.adsabs.harvard.edu/abs/2025arXiv250321863D p

    Danhaive A. L., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.21863 , https://ui.adsabs.harvard.edu/abs/2025arXiv250321863D p. arXiv:2503.21863

    doi:10.48550/arxiv.2503.21863 2025

  54. [54]

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

    doi:10.1051/0004-6361/201730419 2017

  55. [55]

    C., Birnboim Y., Mandelker N., Li Z., 2023, @doi [ ] 10.1093/mnras/stad1557 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.3201D 523, 3201

    Dekel A., Sarkar K. C., Birnboim Y., Mandelker N., Li Z., 2023, @doi [ ] 10.1093/mnras/stad1557 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.3201D 523, 3201

    doi:10.1093/mnras/stad1557 2023

  56. [56]

    Desprez G., et al., 2024, @doi [ ] 10.1093/mnras/stae1084 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.530.2935D 530, 2935

    doi:10.1093/mnras/stae1084 2024

  57. [57]

    Dong F., Zhao D., Han J., Li Z., Jing Y., Yang X., 2022, @doi [ ] 10.3847/1538-4357/ac5aaa , https://ui.adsabs.harvard.edu/abs/2022ApJ...929..120D 929, 120

    doi:10.3847/1538-4357/ac5aaa 2022

  58. [58]

    T., et al., 2023, @doi [ ] 10.1093/mnras/stac3472 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.6011D 518, 6011

    Donnan C. T., et al., 2023, @doi [ ] 10.1093/mnras/stac3472 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.6011D 518, 6011

    doi:10.1093/mnras/stac3472 2023

  59. [59]

    T., et al., 2024, @doi [ ] 10.1093/mnras/stae2037 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.533.3222D 533, 3222

    Donnan C. T., et al., 2024, @doi [ ] 10.1093/mnras/stae2037 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.533.3222D 533, 3222

    doi:10.1093/mnras/stae2037 2024

  60. [60]

    Donnari M., et al., 2021, @doi [ ] 10.1093/mnras/staa3006 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.500.4004D 500, 4004

    doi:10.1093/mnras/staa3006 2021

  61. [61]

    Duncan K., et al., 2019, @doi [ ] 10.3847/1538-4357/ab148a , https://ui.adsabs.harvard.edu/abs/2019ApJ...876..110D 876, 110

    doi:10.3847/1538-4357/ab148a 2019

  62. [62]

    Efstathiou G., Rosenberg E., Poulin V., 2024, @doi [ ] 10.1103/PhysRevLett.132.221002 , https://ui.adsabs.harvard.edu/abs/2024PhRvL.132v1002E 132, 221002

    doi:10.1103/physrevlett.132.221002 2024

  63. [63]

    El-Badry K., et al., 2018, @doi [ ] 10.1093/mnras/stx2482 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473.1930E 473, 1930

    doi:10.1093/mnras/stx2482 2018

  64. [64]

    J., Stanway E

    Eldridge J. J., Stanway E. R., Xiao L., McClelland L. A. S., Taylor G., Ng M., Greis S. M. L., Bray J. C., 2017, @doi [ ] 10.1017/pasa.2017.51 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...58E 34, e058

    doi:10.1017/pasa.2017.51 2017

  65. [65]

    Emsellem E., et al., 2007, @doi [ ] 10.1111/j.1365-2966.2007.11752.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.379..401E 379, 401

    arXiv 2007

  66. [66]

    P., Whitler L., Topping M

    Endsley R., Stark D. P., Whitler L., Topping M. W., Chen Z., Plat A., Chisholm J., Charlot S., 2023, @doi [ ] 10.1093/mnras/stad1919 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.2312E 524, 2312

    doi:10.1093/mnras/stad1919 2023

  67. [67]

    M., et al., 2007, @doi [ ] 10.1086/519294 , https://ui.adsabs.harvard.edu/abs/2007ApJ...665..265F 665, 265

    Faber S. M., et al., 2007, @doi [ ] 10.1086/519294 , https://ui.adsabs.harvard.edu/abs/2007ApJ...665..265F 665, 265

    doi:10.1086/519294 2007

  68. [68]

    Fakhouri O., Ma C.-P., Boylan-Kolchin M., 2010, @doi [ ] 10.1111/j.1365-2966.2010.16859.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.406.2267F 406, 2267

    arXiv 2010

  69. [69]

    Faucher-Gigu \`e re C.-A., Lidz A., Zaldarriaga M., Hernquist L., 2009, @doi [ ] 10.1088/0004-637X/703/2/1416 , https://ui.adsabs.harvard.edu/abs/2009ApJ...703.1416F 703, 1416

    doi:10.1088/0004-637x/703/2/1416 2009

  70. [70]

    Feldmann R., et al., 2025, @doi [ ] 10.1093/mnras/stae2633 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.536..988F 536, 988

    doi:10.1093/mnras/stae2633 2025

  71. [71]

    J., Korista K

    Ferland G. J., Korista K. T., Verner D. A., Ferguson J. W., Kingdon J. B., Verner E. M., 1998, @doi [ ] 10.1086/316190 , https://ui.adsabs.harvard.edu/abs/1998PASP..110..761F 110, 761

    doi:10.1086/316190 1998

  72. [72]

    Ferreira L., et al., 2023, @doi [ ] 10.3847/1538-4357/acec76 , https://ui.adsabs.harvard.edu/abs/2023ApJ...955...94F 955, 94

    doi:10.3847/1538-4357/acec76 2023

  73. [73]

    L., et al., 2022, @doi [ ] 10.3847/2041-8213/ac966e , https://ui.adsabs.harvard.edu/abs/2022ApJ...940L..55F 940, L55

    Finkelstein S. L., et al., 2022, @doi [ ] 10.3847/2041-8213/ac966e , https://ui.adsabs.harvard.edu/abs/2022ApJ...940L..55F 940, L55

    doi:10.3847/2041-8213/ac966e 2022

  74. [74]

    L., et al., 2023, @doi [ ] 10.3847/2041-8213/acade4 , https://ui.adsabs.harvard.edu/abs/2023ApJ...946L..13F 946, L13

    Finkelstein S. L., et al., 2023, @doi [ ] 10.3847/2041-8213/acade4 , https://ui.adsabs.harvard.edu/abs/2023ApJ...946L..13F 946, L13

    doi:10.3847/2041-8213/acade4 2023

  75. [75]

    L., et al., 2024, @doi [ ] 10.3847/2041-8213/ad4495 , https://ui.adsabs.harvard.edu/abs/2024ApJ...969L...2F 969, L2

    Finkelstein S. L., et al., 2024, @doi [ ] 10.3847/2041-8213/ad4495 , https://ui.adsabs.harvard.edu/abs/2024ApJ...969L...2F 969, L2

    doi:10.3847/2041-8213/ad4495 2024

  76. [76]

    G., F \"o rster Schreiber N

    Franx M., van Dokkum P. G., F \"o rster Schreiber N. M., Wuyts S., Labb \'e I., Toft S., 2008, @doi [ ] 10.1086/592431 , https://ui.adsabs.harvard.edu/abs/2008ApJ...688..770F 688, 770

    doi:10.1086/592431 2008

  77. [77]

    L., et al., 2019, @doi [ ] 10.3847/1538-4357/ab2f73 , https://ui.adsabs.harvard.edu/abs/2019ApJ...882...34F 882, 34

    Freedman W. L., et al., 2019, @doi [ ] 10.3847/1538-4357/ab2f73 , https://ui.adsabs.harvard.edu/abs/2019ApJ...882...34F 882, 34

    doi:10.3847/1538-4357/ab2f73 2019

  78. [78]

    L., Madore B

    Freedman W. L., Madore B. F., Hoyt T. J., Jang I. S., Lee A. J., Owens K. A., 2025, @doi [ ] 10.3847/1538-4357/adce78 , https://ui.adsabs.harvard.edu/abs/2025ApJ...985..203F 985, 203

    doi:10.3847/1538-4357/adce78 2025

  79. [79]

    arXiv:2402.18543

    Fujimoto S., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2402.18543 , https://ui.adsabs.harvard.edu/abs/2024arXiv240218543F p. arXiv:2402.18543

    Pith/arXiv arXiv doi:10.48550/arxiv.2402.18543 2024

  80. [80]

    F., Zibetti S., Brinchmann J., Kelson D

    Gallazzi A., Bell E. F., Zibetti S., Brinchmann J., Kelson D. D., 2014, @doi [ ] 10.1088/0004-637X/788/1/72 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...72G 788, 72

    doi:10.1088/0004-637x/788/1/72 2014

Showing first 80 references.