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DeepDive: A deep dive into the physics of the first massive quiescent galaxies in the Universe

T0 review · 3 major / 7 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read Deep JWST/NIRSpec spectroscopy of 150 quiescent galaxies at $1<z<5$ shows that the highest-redshift members have weaker 4000 Å breaks and bluer colors than their lower-redshift counterparts, implying they were caught shortly after their…

desk verdict A solid dataset paper that assembles the largest NIRSpec quiescent-galaxy sample at 1<z<5, but the headline redshift trend is partly a selection effect the authors themselves concede. read the letter →

arxiv 2506.22642 v1 pith:BA6NRAZP submitted 2025-06-27 astro-ph.GA

classification astro-ph.GA
keywords quiescentgalaxiesJWST/NIRSpecspectroscopyhigh-redshiftgalaxyevolution4000Åbreakquenchingstarformationhistoriesactivegalacticnucleistackedspectra
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 presents the DeepDive program, deep 1–3 hour JWST/NIRSpec observations of ten massive quiescent galaxies at $z\approx3$–$4$, and combines them with an archival search that brings the total spectroscopically confirmed sample to 150 quiescent galaxies spanning $1

What carries the argument

The central object is the $D_n4000$ index, the ratio of continuum flux in the 4000–4100 Å window to that in the 3850–3950 Å window following Balogh et al. (1999); it serves as the paper's spectroscopic clock for the age of a stellar population. The argument is carried by three linked instruments: the $D_n4000$ measure itself, the $S_Q = 0.75(V-J) + 0.66(U-V)$ coordinate that maps the UVJ quiescent box onto break strength, and the v4.0 reduction of G235M/F170LP grating spectra that extends coverage beyond the nominal cutoff to recover H$\alpha$ at $z\sim4$. Stacking follows the method of Onodera et al. (2012), with jackknife uncertainties, and Lick-index definitions (Trager et al. 1998) are used to measure H$\delta$A, Fe4383, and Mgb in the composites.

What would settle it

Take the released DeepDive spectra and recompute the $D_n4000$ indices and H$\alpha$ fluxes using an independent calibration — either a correction derived from many more grating–prism pairs or from JWST/MIRI photometry at $\lambda > 3.1\,\mu$m — and compare with the published values. If a substantial fraction of the $z\approx3$–$4$ targets then move above $D_n4000 \approx 1.35$, the conclusion that the highest-redshift quiescent galaxies are systematically younger would not survive.

Watch

Extended reading notes

Core claim

On its own terms, the paper establishes a single empirical picture: the massive quiescent galaxy population at $z\sim3$–$5$, sampled spectroscopically for the first time in large numbers, is dominated by galaxies caught shortly after quenching. They show weaker $D_n4000$ breaks and bluer rest-frame $UVJ$ colors than their $z\sim2$ counterparts, which the authors interpret as generally younger stellar populations. The deep G235M spectra extend redward of the nominal cutoff, so H$\alpha$ is recovered for the $z\sim4$ targets: narrow-line fluxes give SFRs of roughly $0$–$5\,M_\odot\,\mathrm{yr^{-1}}$, confirming quiescence, while two of ten galaxies show broad H$\alpha$ and are identified as AGN hosts. Stacked spectra binned by $D_n4000$ reach continuum S/N of $\sim80$ and reveal faint Fe4383 and Mgb absorption even in the lowest-$D_n4000$ bin at median $z\sim3$, so age- and metallicity-sensitive indices are measurable where they were previously inaccessible.

Load-bearing premise

The load-bearing premise is that a wavelength-dependent flux correction, worked out from a small set of grating–prism calibration pairs and reaching up to 20 percent at the red end, applies correctly to every galaxy in the sample; if it is biased for some sources, the star formation rates and 4000 Å break strengths that drive the main trends would shift systematically.

Editorial extensions

If this is right

  • Three independent quiescence criteria ($D_n4000$, $UVJ$, sSFR) agree at the ~90 percent level, so photometric samples can be mapped onto spectroscopic break strengths and vice versa.
  • The $D_n4000$–$S_Q$ calibration $D_n4000 = (0.32\pm0.05)S_Q + (0.86\pm0.08)$ extends to independently confirmed quiescent galaxies at $z\approx4.9$ and $7.3$, making it a tool for translating UVJ selections into ages at the highest redshifts.
  • Photometric redshifts of quiescent galaxies at $z=3.5$–$5$ are systematically low, with a median bias of about $-0.17$ in $\Delta z/(1+z)$, so spectroscopic follow-up remains necessary for the most distant quiescent population.
  • Medium-resolution stacking reaches continuum S/N of roughly 80–90, enough to measure Lick-style indices (H$\delta$A, Fe4383, Mgb) at $z\ge3$, opening metal-enrichment studies in the early Universe.
  • The detection of broad H$\alpha$ in two of ten targets shows that AGN activity is present in a non-negligible fraction of massive quiescent galaxies at $z\approx3$–$4$.

Reading between the lines

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

  • If the youthful look of the $z\approx3$–$5$ population is real, then older, fully red quiescent galaxies at these redshifts are rarer than simple extrapolation from $z\approx2$ suggests; deep surveys targeting specifically red (high-$D_n4000$) candidates would test whether such systems exist at all at $z>4$.
  • The Appendix C flux correction (up to 20 percent at $\lambda>3.1\,\mu$m) could be checked independently with JWST/MIRI photometry at rest-frame wavelengths beyond the correction region; sources where corrected grating fluxes disagree with MIRI would flag where the calibration breaks down.
  • The same stacking pipeline applied to star-forming galaxies at matched mass and redshift would anchor the emission-line differences seen between $D_n4000$ bins, separating AGN-driven from star-formation-driven ionization without relying on line ratios alone.
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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 DeepDive program paper presents new JWST/NIRSpec G235M/F170LP medium-resolution spectra for 10 massive quiescent galaxies at z~3-4, with an extended-wavelength reduction that recovers Halpha. It combines these with an archival compilation of 140 quiescent galaxies at 1<z<5 from the DAWN JWST Archive, selected through Dn4000, UVJ, and sSFR criteria. The main claims are: low Halpha-based SFRs (0-5 M_sun/yr) confirming quiescence; two AGN candidates with broad Halpha; a trend for higher-redshift quiescent galaxies to show weaker 4000 Angstrom breaks and bluer UVJ colors; a correlation between Dn4000 and the UVJ selection-box coordinate S_Q (Eq. 1); and stacked spectra exhibiting faint Fe4383 and Mgb absorption even in the low-Dn4000, high-redshift bin. The paper also reports ~90% pairwise overlap among the three quiescence selection criteria and a systematic underestimation of photometric redshifts at z>3.5.

Significance. If the results hold, the homogeneously reduced sample and the public data release constitute a valuable community resource for studying early massive quiescent galaxies. The detection of faint metal absorption features in z~3 stacks demonstrates that medium-resolution NIRSpec spectroscopy can push chemical-enrichment studies to earlier epochs, and the empirical Dn4000-S_Q relation is practically useful for comparing high-redshift break-based selection with lower-redshift UVJ-based selection. The main caveat is that the headline trend of weaker breaks and bluer colors at z~3-5 rests on a heterogeneously targeted sample with no selection-function correction; the result is plausible but not yet a statistical census, and the paper is transparent about several associated limitations.

major comments (3)
  1. [Section 3 and Section 6] The claim that z~3-5 quiescent galaxies 'typically exhibit weaker 4000 Angstrom breaks and bluer colors' is a central headline result, but the sample does not support the word 'typically.' The high-redshift wing is dominated by DeepDive primaries and archival targets from programs such as RUBIES, EXCELS, and de Graaff et al. that specifically selected bright (K<23) or post-starburst-like systems, while the z~2 population comes from broader continuum-selected surveys (Section 3, Appendix E). No selection function or parent-sample weighting is applied, and the Summary explicitly concedes that 'selection criteria privileging bright sources' contribute to the result. The authors should either restrict the claim to the specifically targeted population or demonstrate with a selection-function analysis, e.g., using a mass-complete photometric parent sample, that the redshift trend survives.
  2. [Section 2.4 and Appendix C] The Halpha-based SFR range (0-5 M_sun/yr) is a primary quantitative result, but for z>3.75 Halpha falls in the v4.0 extended-wavelength region where the G235M/F170LP flux correction reaches ~20%. The correction is derived from a subsample of grating-prism pairs (78 for G235M) and applied to all medium-resolution spectra, yet no systematic uncertainty from the spline fit is propagated into the SFR measurements. The paper correctly notes that the Halpha SFRs are upper limits because of possible AGN and shock contributions, but the additional flux-calibration uncertainty is not quantified. The authors should propagate the correction uncertainty (e.g., via bootstrap over the calibration sample or comparison with alternate calibrators) and state its impact on the quoted SFR range.
  3. [Section 4.2, Eq. (1)] The Dn4000-S_Q correlation is presented as an empirical relation whose inputs are 'almost independent' aside from flux calibration, but both quantities ultimately derive from the same photometry: the grating spectra are flux-corrected by anchoring to photometry (Section 2.4), and S_Q is computed from rest-frame UVJ colors obtained from EAZY fits to that photometry. Even a low-order polynomial correction can in principle alter the local continuum shape used for Dn4000, inducing a weak coupling. The authors should test for this by remeasuring Dn4000 from the spectra before the photometric anchoring (or from the Bagpipes continuum fits) and re-deriving Eq. (1) for that control case, reporting the correlation coefficient and best-fit parameters.
minor comments (7)
  1. [Abstract] The abstract states that the spectra are '1-3 hours' long, but Table A.1 lists exposure times as short as 2275.9 s (~0.63 hr) for ID 179; please revise to '0.6-3 hours' or 'up to 3 hours'.
  2. [Section 2.1] The phrase 'One target was not observed due to guiding failure in the NIRCam imaging' is ambiguous; please clarify whether the guiding failure prevented the NIRCam imaging of the target field, which in turn precluded the spectroscopic observation.
  3. [Figure 3 caption] The caption contains 'Noted that the SFR shown here' and should read 'Note that the SFR shown here'.
  4. [Section 4.1] There is a typo in 'see Section 4.2 for more disucssion'; it should be 'discussion'.
  5. [Section 4.2] The sentence 'The left and middle panels of Figure 7 offer different insights' should use the singular verb 'offers' because the subject is 'panels' as a collective set, or rephrase to 'offer different insights' if the intended subject is 'the left and middle panels' (plural). The grammar should be corrected.
  6. [Appendix C] The text says 'best-fit spline functions for the medium of them'; this should likely read 'the median of them'.
  7. [Section 3] The visual-inspection removal of 10 sources is described as removing those with 'significantly broad or strong emission lines,' but the quantitative threshold (e.g., FWHM or line EW) is not given; a brief specification would improve reproducibility.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the central claims rest on independent measurements, and the high-redshift trend is an acknowledged selection effect rather than a derivation from fitted inputs.

full rationale

I walked the claimed derivation chain and found no step in which a prediction reduces to its own inputs by construction. The H-alpha SFRs come from Gaussian line fitting of the spectra with dust corrections from SED fitting; even though the extended-wavelength grating spectra are calibrated against photometry via prism spectra, the paper does not present the H-alpha SFRs as predictions of the SED-based SFRs but merely notes they are broadly consistent. The Dn4000 index is measured directly from the spectra, while UVJ colors come from photometric SED modeling, and the paper explicitly states (Section 4.2) that the two are almost independent except for the photometric anchoring of the spectral calibration. The Dn4000-S_Q linear relation (Eq. 1) is an empirical fit, and the paper validates it against independent z=4.9 and z=7.3 objects not used in the fit, so it is not a fitted parameter renamed as a prediction. The stacked spectra are binned by Dn4000 and then examined for independent features such as Ca II, Fe4383, Mgb, and nebular emission lines, which are not used in the bin definition. Self-citations to MSAExp, DJA, and prior reduction papers are shared infrastructure and methodology, not load-bearing arguments for the scientific conclusions. The Summary does concede that 'selection criteria privileging bright sources' contribute to the blue colors and low Dn4000 values at high redshift, which is an honest selection-bias caveat rather than circular reasoning; the claimed redshift trend is thereby partly a consequence of how the high-z sample was assembled, but this is a correctness and interpretation concern, not a circular derivation. No equation in the paper is equivalent to its own inputs, and no 'prediction' is statistically forced by a fitted parameter.

Assumptions & free parameters 7 free parameters · 8 assumptions · 0 invented entities

The central claims rest on standard astrophysical assumptions (IMF, stellar population models, dust laws, cosmology) and on the newly introduced extended-wavelength flux correction. No new physical entities are proposed. The Dn4000-UVJ relation is an empirical fit, with the slope and intercept as free parameters, and the Bagpipes SED parameters are standard fitted values rather than invented constructs.

free parameters (7)
  • Bagpipes log(M_formed/M_sun) = varies per source
    Stellar mass formed, fitted in SED modeling with uniform prior (0,13).
  • Bagpipes A_V = varies per source
    Dust attenuation, fitted with uniform prior (0,4).
  • Bagpipes Z/Z_sun = varies per source
    Stellar metallicity, logarithmic prior (0.2,5).
  • Bagpipes tau/Gyr = varies per source
    Star formation timescale, uniform prior (0.1, t(zobs)).
  • Bagpipes alpha, beta (SFH power-law indices) = varies per source
    Double power-law SFH indices, logarithmic priors (1e-2,1e3).
  • Dn4000-SQ linear slope and intercept = 0.32 +/- 0.05, 0.86 +/- 0.08
    Linear fit to the observed Dn4000-versus-SQ relation (Eq. 1), with sources SQ>2.3 excluded.
  • G235M extended-range spline correction = up to 20% at lambda>3.1 micron
    Second-order wavelength-dependent flux correction derived from grating-prism ratios on a subsample and applied to all medium-resolution spectra (Appendix C).
assumptions (8)
  • domain assumption Flat LCDM cosmology with Omega_m=0.3, Omega_Lambda=0.7, H0=70 km/s/Mpc.
    Stated in the introduction; used for distance and SFR conversions.
  • domain assumption Chabrier (2003) IMF for EAZY and Kroupa (2002) IMF for Bagpipes.
    Stated in Section 2.5; affects stellar masses and SFRs.
  • domain assumption Bruzual & Charlot (2003) stellar population synthesis with MILES library and Bressan et al. (2012) tracks.
    Used in Bagpipes SED fitting (Section 2.5).
  • domain assumption Calzetti et al. (2000) dust attenuation law.
    Assumed in SED fitting (Section 2.5).
  • domain assumption Kennicutt & Evans (2012) conversion from H-alpha luminosity to SFR.
    Used in Section 2.6 to derive SFRs from H-alpha.
  • domain assumption Stellar dust attenuation equals nebular dust attenuation, and H-alpha is solely powered by star formation.
    Explicitly stated in Section 2.6; authors note SFRs should be treated as upper limits.
  • domain assumption Dn4000 threshold of 1.2 roughly corresponds to a simple stellar population age of a few 100 Myr at solar metallicity with no dust.
    Stated in Section 3, criterion 1.
  • domain assumption The v4.0 MSAExp pipeline correctly predicts the extended wavelength response, modulo the spline correction.
    Load-bearing for the H-alpha detections at z~4 (Sections 2.3 and Appendix C).

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Cite this review

Pith. "Pith review of DeepDive: A deep dive into the physics of the first massive quiescent galaxies in the Universe." pith.science (2026). https://pith.science/paper/BA6NRAZP

@misc{pith2026250622642,
  author       = {Pith},
  title        = {Pith review of: DeepDive: A deep dive into the physics of the first massive quiescent galaxies in the Universe},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BA6NRAZP}},
  note         = {Machine review of arXiv:2506.22642}
}
abstract

We present the DeepDive program, in which we obtained deep ($1-3$ hours) JWST/NIRSpec G235M/F170LP spectra for 10 primary massive ($\log{(M_\star/M_\odot)}=10.8-11.5$) quiescent galaxies at $z\sim3-4$. A novel reduction procedure extends the nominal wavelength coverage of G235M beyond H$\alpha$ and [NII] at $z\sim4$, revealing weak, narrow H$\alpha$ lines indicative of low star formation rates (${\rm SFR}\sim0-5\, M_\odot\, {\rm yr^{-1}}$). Two out of 10 primary targets have broad H$\alpha$ lines, indicating the presence of AGNs. We also conduct an archival search of quiescent galaxies observed with NIRSpec gratings in the DAWN JWST Archive, which provides a statistical context for interpreting the DeepDive targets. This archival search provides a spectroscopic sample of 140 quiescent galaxies spanning $1<z<5$ and covering more than an order of magnitude in stellar mass. We revisit the selection of quiescent galaxies based on rest-frame $UVJ$ colors, specific star formation rates, and the detection of the 4000\r{A} spectral break, finding $\sim90\%$ overlap between these criteria. The sample of a total of 150 quiescent galaxies constructed in this study shows that those at $z\sim3-5$, including the DeepDive targets, typically exhibit weaker 4000\r{A} breaks and bluer colors than their lower-redshift counterparts, indicating generally younger stellar populations. Stacked spectra of sources grouped by the $D_n4000$ index reveal faint Iron and Magnesium absorption line features in the stellar continuum even for the low $D_n4000$ ($D_n4000<1.35$) subsample at high redshift ($z\sim3$). In addition, higher $D_n4000$ subsamples show fainter nebular emission lines. These results demonstrate that medium-resolution NIRSpec spectroscopy is essential for robustly characterizing the diversity and evolution of early quiescent galaxies. All data from this study will be made publicly available.

Figures

Figures reproduced from arXiv: 2506.22642 by the authors.

Figure 1
Figure 1. Left: Spectra of the main DeepDive targets. Spectra are shown in black solid lines, and gray hatched regions represent their [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. SEDs of the main DeepDive targets. Blue squares represent the available photometric data, and black lines show the best-fit [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Left panel: Comparison between SFR from the SED fitting and SFR from H [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Venn diagram of the number of selected quiescent galax [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 6
Figure 6. Figure 6: Comparison between the spectroscopic redshift obtained [PITH_FULL_IMAGE:figures/full_fig_p008_6.png]
Figure 7
Figure 7. Figure 7: Left and middle panels show the UV J rest-color diagram, where markers are colored by their redshift and Dn4000, respec￾tively. The meaning of the markers is the same as in [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]
Figure 8
Figure 8. Figure 8: Top row, from left to right: Distribution of the [PITH_FULL_IMAGE:figures/full_fig_p011_8.png]
Figure 9
Figure 9. Figure 9: Top panel: HδA v.s. Fe4383 for the three Dn4000- subsamples, shown as filled stars colored as [PITH_FULL_IMAGE:figures/full_fig_p012_9.png]

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

  1. ATLAS. II. Extremely High Incidence of Balmer Line Absorption with Predominant Blueshifts in LRDs: Statistical Insights through Comparison with Type 1 AGNs

    astro-ph.GA 2026-07 conditional novelty 6.0 of 10

    Balmer-line absorption occurs in ~35% (14/40) of JWST little-red-dot AGNs, roughly 850x the rate in SDSS type-1 AGNs, with mostly slow blueshifted absorber velocities.

Reference graph

Works this paper leans on

144 extracted references · 44 canonical work pages · cited by 1 Pith paper

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

  3. [3]

    2025, , 978, 90

    Antwi-Danso , J., Papovich , C., Esdaile , J., et al. 2025, , 978, 90

  4. [4]

    2023, , 943, 166

    Antwi-Danso , J., Papovich , C., Leja , J., et al. 2023, , 943, 166

  5. [5]

    B., Finkelstein , S

    Bagley , M. B., Finkelstein , S. L., Koekemoer , A. M., et al. 2023, , 946, L12

  6. [6]

    The abundance and nature of high-redshift quiescent galaxies from JADES spectroscopy and the FLAMINGO simulations

    Baker , W. M., Lim , S., D'Eugenio , F., et al. 2024, arXiv e-prints, arXiv:2410.14773

  7. [7]

    M., Valentino , F., Lagos , C

    Baker , W. M., Valentino , F., Lagos , C. d. P., et al. 2025, arXiv e-prints, arXiv:2506.04119

  8. [8]

    L., Morris , S

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

Show all 144 references
  1. [9]

    2016, The Journal of Open Source Software, 1, 58

    Barbary , K. 2016, The Journal of Open Source Software, 1, 58

  2. [10]

    2024, arXiv e-prints, arXiv:2404.08052

    Barrufet , L., Oesch , P., Marques-Chaves , R., et al. 2024, arXiv e-prints, arXiv:2404.08052

  3. [11]

    B., & Ellis , R

    Belli , S., Newman , A. B., & Ellis , R. S. 2017, , 834, 18

  4. [12]

    B., & Ellis , R

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

  5. [13]

    B., Ellis , R

    Belli , S., Newman , A. B., Ellis , R. S., & Konidaris , N. P. 2014, , 788, L29

  6. [14]

    L., et al

    Belli , S., Park , M., Davies , R. L., et al. 2024, , 630, 54

  7. [15]

    & Arnouts , S

    Bertin , E. & Arnouts , S. 1996, , 117, 393

  8. [16]

    G., Kriek , M., Conroy , C., et al

    Beverage , A. G., Kriek , M., Conroy , C., et al. 2021, , 917, L1

  9. [17]

    G., Kriek , M., Suess , K

    Beverage , A. G., Kriek , M., Suess , K. A., et al. 2024, , 966, 234

  10. [18]

    G., Slob , M., Kriek , M., et al

    Beverage , A. G., Slob , M., Kriek , M., et al. 2025, , 979, 249

  11. [19]

    2016, , 596, A63

    Boucaud , A., Bocchio , M., Abergel , A., et al. 2016, , 596, A63

  12. [20]

    2021, eazy-py

    Brammer, G. 2021, eazy-py

  13. [21]

    2023 a , grizli

    Brammer , G. 2023 a , grizli

  14. [22]

    2023 b , msaexp: NIRSpec analyis tools

    Brammer , G. 2023 b , msaexp: NIRSpec analyis tools

  15. [23]

    B., van Dokkum , P

    Brammer , G. B., van Dokkum , P. G., & Coppi , P. 2008, , 686, 1503

  16. [24]

    B., van Dokkum , P

    Brammer , G. B., van Dokkum , P. G., Franx , M., et al. 2012, , 200, 13

  17. [25]

    2012, , 427, 127

    Bressan , A., Marigo , P., Girardi , L., et al. 2012, , 427, 127

  18. [26]

    & Charlot , S

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

  19. [27]

    2025, , 981, 25

    Bugiani , L., Belli , S., Park , M., et al. 2025, , 981, 25

  20. [28]

    J., Conroy , C., & Johnson , B

    Byler , N., Dalcanton , J. J., Conroy , C., & Johnson , B. D. 2017, , 840, 44

  21. [29]

    M., Stanway , E

    Byrne , C. M., Stanway , E. R., Eldridge , J. J., McSwiney , L., & Townsend , O. T. 2022, , 512, 5329

  22. [30]

    C., et al

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

  23. [31]

    2017, , 466, 798

    Cappellari , M. 2017, , 466, 798

  24. [32]

    2023, , 526, 3273

    Cappellari , M. 2023, , 526, 3273

  25. [33]

    C., Begley , R., McLeod , D

    Carnall , A. C., Begley , R., McLeod , D. J., et al. 2022 a , arXiv e-prints, arXiv:2207.08778

  26. [34]

    C., Cullen , F., McLure , R

    Carnall , A. C., Cullen , F., McLure , R. J., et al. 2024, arXiv e-prints, arXiv:2405.02242

  27. [35]

    C., Leja , J., Johnson , B

    Carnall , A. C., Leja , J., Johnson , B. D., et al. 2019, , 873, 44

  28. [36]

    C., McLeod , D

    Carnall , A. C., McLeod , D. J., McLure , R. J., et al. 2022 b , arXiv e-prints, arXiv:2208.00986

  29. [37]

    C., McLure , R

    Carnall , A. C., McLure , R. J., Dunlop , J. S., & Dav \'e , R. 2018, , 480, 4379

  30. [38]

    C., McLure , R

    Carnall , A. C., McLure , R. J., Dunlop , J. S., et al. 2023, , 619, 716

  31. [39]

    C., Walker , S., McLure , R

    Carnall , A. C., Walker , S., McLure , R. J., et al. 2020, , 496, 695

  32. [40]

    M., Kartaltepe , J

    Casey , C. M., Kartaltepe , J. S., Drakos , N. E., et al. 2023, , 954, 31

  33. [41]

    2003, , 115, 763

    Chabrier , G. 2003, , 115, 763

  34. [42]

    M., Kriek , M., Beverage , A

    Cheng , C. M., Kriek , M., Beverage , A. G., et al. 2025, arXiv e-prints, arXiv:2505.08858

  35. [43]

    & Gunn , J

    Conroy , C. & Gunn , J. E. 2010, , 712, 833

  36. [44]

    E., Whitaker , K

    Cutler , S. E., Whitaker , K. E., Weaver , J. R., et al. 2024, , 967, L23

  37. [45]

    2005, , 626, 680

    Daddi , E., Renzini , A., Pirzkal , N., et al. 2005, , 626, 680

  38. [46]

    L., Belli , S., Park , M., et al

    Davies , R. L., Belli , S., Park , M., et al. 2024, , 528, 4976

  39. [47]

    2024 a , arXiv e-prints, arXiv:2409.05948

    de Graaff , A., Brammer , G., Weibel , A., et al. 2024 a , arXiv e-prints, arXiv:2409.05948

  40. [48]

    J., Brammer , G., et al

    de Graaff , A., Setton , D. J., Brammer , G., et al. 2024 b , arXiv e-prints, arXiv:2404.05683

  41. [49]

    2025, arXiv e-prints, arXiv:2502.01724

    De Lucia , G., Fontanot , F., Hirschmann , M., & Xie , L. 2025, arXiv e-prints, arXiv:2502.01724

  42. [50]

    2024, , 687, A68

    De Lucia , G., Fontanot , F., Xie , L., & Hirschmann , M. 2024, , 687, A68

  43. [51]

    2023, , 670, A82

    Desprez , G., Picouet , V., Moutard , T., et al. 2023, , 670, A82

  44. [52]

    2021, , 653, A32

    D'Eugenio , C., Daddi , E., Gobat , R., et al. 2021, , 653, A32

  45. [53]

    G., Maiolino , R., et al

    D'Eugenio , F., P \'e rez-Gonz \'a lez , P. G., Maiolino , R., et al. 2024, Nature Astronomy, 8, 1443

  46. [54]

    & Davis , M

    Djorgovski , S. & Davis , M. 1987, , 313, 59

  47. [55]

    T., McLure , R

    Donnan , C. T., McLure , R. J., Dunlop , J. S., et al. 2024, , 533, 3222

  48. [56]

    J., Willott , C., Alberts , S., et al

    Eisenstein , D. J., Willott , C., Alberts , S., et al. 2023, arXiv e-prints, arXiv:2306.02465

  49. [57]

    2021, , 908, L35

    Esdaile , J., Glazebrook , K., Labb \'e , I., et al. 2021, , 908, L35

  50. [58]

    J., Faber , S

    Fang , J. J., Faber , S. M., Koo , D. C., et al. 2018, , 858, 100

  51. [59]

    L., Bagley , M

    Finkelstein , S. L., Bagley , M. B., Ferguson , H. C., et al. 2023, , 946, L13

  52. [60]

    C., Annunziatella , M., et al

    Forrest , B., Marsan , Z. C., Annunziatella , M., et al. 2020, , 903, 47

  53. [61]

    2022, , 938, 109

    Forrest , B., Wilson , G., Muzzin , A., et al. 2022, , 938, 109

  54. [62]

    Fruchter , A. S. & Hook , R. N. 2002, , 114, 144

  55. [63]

    L., Pascale , M., Pierel , J., et al

    Frye , B. L., Pascale , M., Pierel , J., et al. 2024, , 961, 171

  56. [64]

    Gaia Collaboration , Brown , A. G. A., Vallenari , A., et al. 2021, , 649, A1

  57. [65]

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

    Gallazzi , A., Bell , E. F., Zibetti , S., Brinchmann , J., & Kelson , D. D. 2014, , 788, 72

  58. [66]

    2024, , 628, 277

    Glazebrook , K., Nanayakkara , T., Schreiber , C., et al. 2024, , 628, 277

  59. [67]

    2017, , 544, 71

    Glazebrook , K., Schreiber , C., Labb \'e , I., et al. 2017, , 544, 71

  60. [68]

    A., Kocevski , D

    Grogin , N. A., Kocevski , D. D., Faber , S. M., et al. 2011, , 197, 35

  61. [69]

    E., Brammer , G

    Heintz , K. E., Brammer , G. B., Watson , D., et al. 2025, , 693, A60

  62. [70]

    S., Shimasaku , K., et al

    Ito , K., Tanaka , T. S., Shimasaku , K., et al. 2025 a , , 538, 1501

  63. [71]

    2024, , 964, 192

    Ito , K., Valentino , F., Brammer , G., et al. 2024, , 964, 192

  64. [72]

    2025 b , arXiv e-prints, arXiv:2503.01953

    Ito , K., Valentino , F., Farcy , M., et al. 2025 b , arXiv e-prints, arXiv:2503.01953

  65. [73]

    B., Mobasher , B., et al

    Jafariyazani , M., Newman , A. B., Mobasher , B., et al. 2024, arXiv e-prints, arXiv:2406.03549

  66. [74]

    2022, , 661, A80

    Jakobsen , P., Ferruit , P., Alves de Oliveira , C., et al. 2022, , 661, A80

  67. [75]

    J., Bonfield , D

    Jarvis , M. J., Bonfield , D. G., Bruce , V. A., et al. 2013, , 428, 1281

  68. [76]

    K., Melchior , P., Spergel , D

    Jespersen , C. K., Melchior , P., Spergel , D. N., et al. 2025 a , arXiv e-prints, arXiv:2503.03816

  69. [77]

    K., Steinhardt , C

    Jespersen , C. K., Steinhardt , C. L., Somerville , R. S., & Lovell , C. C. 2025 b , , 982, 23

  70. [78]

    2024, , 963, 49

    Kakimoto , T., Tanaka , M., Onodera , M., et al. 2024, , 963, 49

  71. [79]

    D., Rodighiero , G., et al

    Kashino , D., Silverman , J. D., Rodighiero , G., et al. 2013, , 777, L8

  72. [80]

    2025, arXiv e-prints, arXiv:2505.03089

    Kawinwanichakij , L., Glazebrook , K., Nanayakkara , T., et al. 2025, arXiv e-prints, arXiv:2505.03089

  73. [81]

    Kennicutt , R. C. & Evans , N. J. 2012, , 50, 531

  74. [82]

    J., Nicholls , D

    Kewley , L. J., Nicholls , D. C., & Sutherland , R. S. 2019, , 57, 511

  75. [83]

    D., Hasinger , G., Brightman , M., et al

    Kocevski , D. D., Hasinger , G., Brightman , M., et al. 2018, , 236, 48

  76. [84]

    M., Faber , S

    Koekemoer , A. M., Faber , S. M., Ferguson , H. C., et al. 2011, , 197, 36

  77. [85]

    2022, , 263, 38

    Kokorev , V., Brammer , G., Fujimoto , S., et al. 2022, , 263, 38

  78. [86]

    2024, arXiv e-prints, arXiv:2407.20320

    Kokorev , V., Chisholm , J., Endsley , R., et al. 2024, arXiv e-prints, arXiv:2407.20320

  79. [87]

    & Conroy , C

    Kriek , M. & Conroy , C. 2013, , 775, L16

  80. [88]

    H., Conroy , C., et al

    Kriek , M., Price , S. H., Conroy , C., et al. 2019, , 880, L31

  81. [89]

    G., Franx , M., et al

    Kriek , M., van Dokkum , P. G., Franx , M., et al. 2006, , 649, L71

  82. [90]

    G., Labb \'e , I., et al

    Kriek , M., van Dokkum , P. G., Labb \'e , I., et al. 2009, , 700, 221

  83. [91]

    Kron , R. G. 1980, , 43, 305

  84. [92]

    & Boily , C

    Kroupa , P. & Boily , C. M. 2002, , 336, 1188

  85. [93]

    2018, , 867, 1

    Kubo , M., Tanaka , M., Yabe , K., et al. 2018, , 867, 1

  86. [94]

    2003, , 125, 1107

    Labb \'e , I., Franx , M., Rudnick , G., et al. 2003, , 125, 1107

  87. [95]

    2005, , 624, L81

    Labb \'e , I., Huang , J., Franx , M., et al. 2005, , 624, L81

  88. [96]

    Lagos , C. d. P., Valentino , F., Wright , R. J., et al. 2024, arXiv e-prints, arXiv:2409.16916

  89. [97]

    J., D'Eugenio , F., Maiolino , R., et al

    Looser , T. J., D'Eugenio , F., Maiolino , R., et al. 2024, , 629, 53

  90. [98]

    C., Harrison , I., Harikane , Y., Tacchella , S., & Wilkins , S

    Lovell , C. C., Harrison , I., Harikane , Y., Tacchella , S., & Wilkins , S. M. 2023, , 518, 2511

  91. [99]

    C., Marchesini , D., Brammer , G

    Marsan , Z. C., Marchesini , D., Brammer , G. B., et al. 2017, , 842, 21

  92. [100]

    V., Lewis, Z., Matthee, J., et al

    Maseda, M. V., Lewis, Z., Matthee, J., et al. 2023, The Astrophysical Journal, 956, 11

  93. [101]

    T., Beifiori , A., Saglia , R

    Mendel , J. T., Beifiori , A., Saglia , R. P., et al. 2020, , 899, 87

  94. [102]

    2024, Scientific Reports, 14, 3724

    Nanayakkara , T., Glazebrook , K., Jacobs , C., et al. 2024, Scientific Reports, 14, 3724

  95. [103]

    2025, , 981, 78

    Nanayakkara , T., Glazebrook , K., Schreiber , C., et al. 2025, , 981, 78

  96. [104]

    Oke , J. B. & Gunn , J. E. 1983, , 266, 713

  97. [105]

    2012, , 755, 26

    Onodera , M., Renzini , A., Carollo , M., et al. 2012, , 755, 26

  98. [106]

    D., et al

    Onoue , M., Ding , X., Silverman , J. D., et al. 2024, arXiv e-prints, arXiv:2409.07113

  99. [107]

    G., Melinder , J., et al

    \"O stlin , G., P \'e rez-Gonz \'a lez , P. G., Melinder , J., et al. 2025, , 696, A57

  100. [108]

    2024 a , , 976, 72

    Park , M., Belli , S., Conroy , C., et al. 2024 a , , 976, 72

  101. [109]

    D., et al

    Park , M., Conroy , C., Johnson , B. D., et al. 2024 b , arXiv e-prints, arXiv:2410.21375

  102. [110]

    L., Gottumukkala , R., Heintz , K

    Pollock , C. L., Gottumukkala , R., Heintz , K. E., et al. 2025, arXiv e-prints, arXiv:2506.15779

  103. [111]

    2023, , 519, 1526

    Popesso , P., Concas , A., Cresci , G., et al. 2023, , 519, 1526

  104. [112]

    F., Jim \'e nez-Vicente , J., et al

    S \'a nchez-Bl \'a zquez , P., Peletier , R. F., Jim \'e nez-Vicente , J., et al. 2006, , 371, 703

  105. [113]

    2020, , 905, 40

    Saracco , P., Marchesini , D., La Barbera , F., et al. 2020, , 905, 40

  106. [114]

    2018 a , , 618, A85

    Schreiber , C., Glazebrook , K., Nanayakkara , T., et al. 2018 a , , 618, A85

  107. [115]

    2018 b , , 611, A22

    Schreiber , C., Labb \'e , I., Glazebrook , K., et al. 2018 b , , 611, A22

  108. [116]

    2015, , 575, A74

    Schreiber , C., Pannella , M., Elbaz , D., et al. 2015, , 575, A74

  109. [117]

    E., Sanders , R

    Shapley , A. E., Sanders , R. L., Topping , M. W., et al. 2025, , 980, 242

  110. [118]

    G., et al

    Slob , M., Kriek , M., Beverage , A. G., et al. 2024, , 973, 131

  111. [119]

    2025, arXiv e-prints, arXiv:2506.04310

    Slob , M., Kriek , M., de Graaff , A., et al. 2025, arXiv e-prints, arXiv:2506.04310

  112. [120]

    L., Jespersen , C

    Steinhardt , C. L., Jespersen , C. K., & Linzer , N. B. 2021, , 923, 8

  113. [121]

    2021, , 908, 135

    Stockmann , M., J rgensen , I., Toft , S., et al. 2021, , 908, 135

  114. [122]

    H., et al

    Sun , Y., Ji , Z., Rieke , G. H., et al. 2025, arXiv e-prints, arXiv:2504.14682

  115. [123]

    2019, , 885, L34

    Tanaka , M., Valentino , F., Toft , S., et al. 2019, , 885, L34

  116. [124]

    2003, , 339, 897

    Thomas , D., Maraston , C., & Bender , R. 2003, , 339, 897

  117. [125]

    2007, , 671, 285

    Toft , S., van Dokkum , P., Franx , M., et al. 2007, , 671, 285

  118. [126]

    C., Worthey , G., Faber , S

    Trager , S. C., Worthey , G., Faber , S. M., Burstein , D., & Gonz \'a lez , J. J. 1998, , 116, 1

  119. [127]

    M., Rudnick , G., et al

    Trujillo , I., F \"o rster Schreiber , N. M., Rudnick , G., et al. 2006, , 650, 18

  120. [128]

    Valentino , F., Brammer , G., Gould , K. M. L., et al. 2023, , 947, 20

  121. [129]

    E., Brammer , G., et al

    Valentino , F., Heintz , K. E., Brammer , G., et al. 2025, arXiv e-prints, arXiv:2503.01990

  122. [130]

    2020, , 889, 93

    Valentino , F., Tanaka , M., Davidzon , I., et al. 2020, , 889, 93

  123. [131]

    2022, , 936, 9

    van der Wel , A., van Houdt , J., Bezanson , R., et al. 2022, , 936, 9

  124. [132]

    G., Kriek , M., & Franx , M

    van Dokkum , P. G., Kriek , M., & Franx , M. 2009, , 460, 717

  125. [133]

    R., Cutler , S

    Weaver , J. R., Cutler , S. E., Pan , R., et al. 2024, , 270, 7

  126. [134]

    R., Kauffmann , O

    Weaver , J. R., Kauffmann , O. B., Ilbert , O., et al. 2022, , 258, 11

  127. [135]

    J., et al

    Weibel , A., de Graaff , A., Setton , D. J., et al. 2025, , 983, 11

  128. [136]

    E., Kriek , M., van Dokkum , P

    Whitaker , K. E., Kriek , M., van Dokkum , P. G., et al. 2012, , 745, 179

  129. [137]

    E., Labb \'e , I., van Dokkum , P

    Whitaker , K. E., Labb \'e , I., van Dokkum , P. G., et al. 2011, , 735, 86

  130. [138]

    E., van Dokkum , P

    Whitaker , K. E., van Dokkum , P. G., Brammer , G., et al. 2013, , 770, L39

  131. [139]

    J., Quadri , R

    Williams , R. J., Quadri , R. F., Franx , M., van Dokkum , P., & Labb \'e , I. 2009, , 691, 1879

  132. [140]

    Woosley , S. E. & Weaver , T. A. 1995, , 101, 181

  133. [141]

    E., Weaver , J

    Wright , L., Whitaker , K. E., Weaver , J. R., et al. 2024, , 964, L10

  134. [142]

    2024, arXiv e-prints, arXiv:2409.00471

    Wu , P.-F. 2024, arXiv e-prints, arXiv:2409.00471

  135. [143]

    2021, , 162, 201

    Wu , P.-F., Nelson , D., van der Wel , A., et al. 2021, , 162, 201

  136. [144]

    S., Franco , M., et al

    Yang , L., Kartaltepe , J. S., Franco , M., et al. 2025, arXiv e-prints, arXiv:2504.07185

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.