pith. sign in

arxiv: 2606.02698 · v1 · pith:DQV7XLNHnew · submitted 2026-06-01 · 🌌 astro-ph.GA

Unbreaking the Universe: MINERVA Measurements of Color Gradients in Massive Quiescent Galaxies Can Help Ease Too-Early Star Formation Tensions

Sam E. Cutler , Luke Robbins , Danilo Marchesini , Katherine A. Suess , Adam Muzzin , Gabriel Brammer , Yoshihisa Asada , Nicholas S. Martis
show 36 more authors
Stacey Alberts Jacqueline Antwi-Danso Aidan P. Cloonan Ivo Labb\'e Tim B. Miller Ikki Mitsuhashi Alexandra Pope Anna Sajina Ghassan T. E. Sarrouh Monu Sharma Mauro Stefanon Edgar P. Vidal Chris J. Willot Rachel Bezanson Maru\v{s}a Brada\v{c} Olivia R. Cooper Robert Feldmann Ben Forrest Karl Glazebrook Jenny E. Greene Valentina La Torre Jamie Lin Michael V. Maseda Ian McConachie Themiya Nananyakkara Ga\"el Noirot Richard Pan Kesha A. Patel Veronica Pratt Marcin Sawicki David J. Setton John R. Weaver Arjen van der Wel Katherine E. Whitaker Yunchong Zhang Kumail Zaidi
This is my paper

Pith reviewed 2026-06-28 13:45 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords quiescent galaxiescolor gradientshigh-redshift galaxiesstellar massJWST photometryslit spectroscopygalaxy formationage gradients
0
0 comments X

The pith

Color gradients in z>3 massive quiescent galaxies imply stellar masses 0.1 dex lower than central slit measurements suggest.

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

The paper analyzes color gradients in four massive quiescent galaxies at redshift greater than 3 using medium-band photometry from JWST observations. It shows that these gradients mean the full-galaxy stellar mass is lower than what is inferred from photometry limited to the central regions captured by NIRSpec slits. In the limiting case where the gradients reflect age differences alone, this adjustment reduces apparent tensions between the observed galaxies and extreme value statistics models of galaxy formation out to redshift around 9.5. The findings stress that central measurements alone may not represent entire galaxies and that spatially resolved spectra are required to separate age effects from dust and metallicity.

Core claim

Using resolved photometry in elliptical annuli out to 0.7 arcsec, the authors find negative color gradients in three of the four galaxies. For the most extreme gradient of Delta(U-V)/Delta R = -0.126 plus or minus 0.030 mag kpc^{-1}, the stellar mass is 0.1 dex lower than from slit photometry. In the limiting case where these color gradients are entirely driven by age, tensions with extreme value statistics models are lessened out to z approximately 9.5, though different stellar population modeling choices also contribute significantly.

What carries the argument

Negative color gradients measured in elliptical annuli from MINERVA JWST medium-band photometry, compared against photometry within NIRSpec slits.

If this is right

  • Stellar mass estimates from central slit data alone can be higher by 0.1 dex for galaxies with strong color gradients.
  • Tensions with galaxy formation models can be reduced out to z~9.5 if the gradients prove to be age-driven.
  • Different choices in stellar population modeling affect the inferred formation histories at a level comparable to the gradient correction.
  • Integral field unit spectroscopy is required to break the age-dust-metallicity degeneracy in these systems.

Where Pith is reading between the lines

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

  • If such color gradients turn out to be common among high-redshift quiescent galaxies, many earlier mass and formation-time estimates based on slit data may require downward revision.
  • The effect could alter how extreme the apparent mismatch is between observations and models of the earliest massive galaxies.
  • Applying the same annular photometry approach to larger samples would test whether the 0.1 dex shift is typical or limited to the most extreme cases.
  • Future observations with integral field units on JWST or next-generation facilities could systematically map these gradients to refine early-universe galaxy assembly timelines.

Load-bearing premise

That the observed color gradients are driven entirely by age differences rather than dust or metallicity variations.

What would settle it

Spatially resolved spectroscopy across the galaxies that directly measures radial profiles of age, dust, and metallicity and shows the color gradients are not primarily age-driven.

Figures

Figures reproduced from arXiv: 2606.02698 by Adam Muzzin, Aidan P. Cloonan, Alexandra Pope, Anna Sajina, Arjen van der Wel, Ben Forrest, Chris J. Willot, Danilo Marchesini, David J. Setton, Edgar P. Vidal, Gabriel Brammer, Ga\"el Noirot, Ghassan T. E. Sarrouh, Ian McConachie, Ikki Mitsuhashi, Ivo Labb\'e, Jacqueline Antwi-Danso, Jamie Lin, Jenny E. Greene, John R. Weaver, Karl Glazebrook, Katherine A. Suess, Katherine E. Whitaker, Kesha A. Patel, Kumail Zaidi, Luke Robbins, Marcin Sawicki, Maru\v{s}a Brada\v{c}, Mauro Stefanon, Michael V. Maseda, Monu Sharma, Nicholas S. Martis, Olivia R. Cooper, Rachel Bezanson, Richard Pan, Robert Feldmann, Sam E. Cutler, Stacey Alberts, Themiya Nananyakkara, Tim B. Miller, Valentina La Torre, Veronica Pratt, Yoshihisa Asada, Yunchong Zhang.

Figure 1
Figure 1. Figure 1: Image cutouts and resolved SEDs of the four ultra-massive quiescent galaxies. For each galaxy, a (F090W+F115W+F150W)-F277W￾F444W RGB image is shown in the top left while the bottom left shows a medium-band-only RGB image. The three medium-band filters for each galaxy, chosen to span the Balmer/4000Å break, are indicated in the top of the cutout. A neighboring galaxy is masked in the broadband RGB cutout of… view at source ↗
Figure 2
Figure 2. Figure 2: Most of the ultra-massive quiescent galaxies at z > 3 have negative color gradients. Top row: Change in observed colors with aperture semi-major axis (in kpc on the bottom axis and relative to the flux radius on the top) for each galaxy in our sample. The filters, chosen to be closest to the pivot wavelength of the rest-frame U and V bands, are indicated in the bottom left of each panel. Filled points (con… view at source ↗
Figure 3
Figure 3. Figure 3: The distribution of galaxy mass-weighted age, specific-star formation rate (averaged over the last 100 Myr of the galaxies’ SFHs), rest-frame V band mass-to-light ratio in the rest-frame Bessel V-band, and dust-corrected (“de-reddened”) D4000 and DB (D4000dr and DB,dr) strengths in each annular aperture for our “fiducial” model, whereby the metallicity is given a strong Gaussian prior set by the values fro… view at source ↗
Figure 4
Figure 4. Figure 4: Resolved, median SFHs from PROSPECTOR for the four C24 ultra-massive quiescent galaxies. Colors indicate the corresponding annulus that was used to measure photometry and are identical to [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Stellar mass assembly histories of the four ultra-massive quiescent galaxies based on our fiducial PROSPECTOR model. The sum of the median stellar mass assembly histories (defined as the cumulative sum of the mass of living stars and stellar remnants) for each of the annuli are shown with thick black lines. 1 and 2σ uncertainties are determined by a quadrature sum of the uncertainties on the assembly histo… view at source ↗
read the original abstract

The discovery of a population of massive, ancient quiescent galaxies within the first 2 Gyr of the Universe's history has led to significant tensions with models of galaxy formation. However, these analyses are often based on slit spectroscopy, which typically captures only the center-most region of these galaxies and, crucially, assumes these cores are representative of the entire galaxy. To illustrate the varying stellar populations present throughout these galaxies, we present an analysis of color gradients in four $z>3$ $\log(M_\star/M_\odot)>11$ quiescent galaxies which previous works have argued are in tension with models. Using medium-band photometry from MINERVA JWST observations, we measure resolved photometry in a series of elliptical annuli out to $0.7^{\prime\prime}$ ($\sim4~R_e$). We find negative color gradients in three galaxies, and for the most extreme color gradient ($\Delta(U-V)/\Delta R=-0.126\pm0.030~{\rm mag~kpc^{-1}}$), we find the stellar mass is 0.1 dex lower when compared to photometry measured within NIRSpec slits. In the limiting case where these color gradients are entirely driven by age, we find lessened tensions with extreme value statistics models out to $z\sim9.5$, though different stellar population modeling choices also contribute significantly. Ultimately, these findings highlight the need for integral field unit spectroscopy. Spatially-resolved spectra can provide the evidence needed to break the age-dust-metallicity degeneracy, and reliably separate the effects of the observed color gradients from the effects of different physical modeling assumptions on the formation histories of these galaxies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The manuscript presents MINERVA JWST medium-band photometry measurements of color gradients in four z>3, log(M*/M⊙)>11 quiescent galaxies previously argued to be in tension with models. Negative gradients are reported in three galaxies; for the strongest case (Δ(U-V)/ΔR = -0.126±0.030 mag kpc^{-1}), annular photometry yields a stellar mass 0.1 dex lower than NIRSpec slit photometry. In the limiting case where gradients are entirely age-driven, tensions with extreme value statistics models are stated to be reduced out to z~9.5, with the paper noting that stellar population modeling choices also contribute and calling for IFU spectroscopy to resolve age-dust-metallicity degeneracies.

Significance. The direct annular photometry provides a concrete, data-driven quantification of aperture effects in stellar mass estimates for early quiescent galaxies, which is a useful observational constraint independent of modeling assumptions. The explicit framing of the age-driven scenario as a limiting case and the constructive call for IFU data appropriately bound the interpretation. If the 0.1 dex offset is robust, it offers a pathway to ease model tensions under specific conditions, though the conditional nature limits broader impact.

major comments (2)
  1. [Abstract] Abstract and final paragraph: the claim that tensions are 'lessened' out to z~9.5 in the limiting age-driven case does not specify the extreme value statistics models used or the quantitative tension metric (e.g., change in probability or sigma level) before versus after the 0.1 dex adjustment, which is load-bearing for evaluating the practical significance of the mass offset.
  2. [Results (mass comparison)] The 0.1 dex stellar mass offset is derived from annular versus slit photometry, but the manuscript provides no details on the stellar population synthesis assumptions, IMF, or SFH templates used to convert the photometry to mass; without this, it is unclear whether the offset is independent of the same modeling choices that the paper states also contribute to tension reduction.
minor comments (3)
  1. [Methods] The radial range and binning for the elliptical annuli (out to 0.7 arcsec) should be explicitly tabulated or described to allow reproduction of the gradient fits.
  2. [Figures] Figure captions would benefit from stating the number of annuli per galaxy and the typical photometric uncertainties per annulus.
  3. [Discussion] The paper correctly identifies the need for IFU data but could add a brief discussion of which existing or upcoming IFU programs (e.g., specific JWST programs) would be most suitable for these targets.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive review and positive assessment of the work. We address each major comment below and will incorporate clarifications in a revised manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract and final paragraph: the claim that tensions are 'lessened' out to z~9.5 in the limiting age-driven case does not specify the extreme value statistics models used or the quantitative tension metric (e.g., change in probability or sigma level) before versus after the 0.1 dex adjustment, which is load-bearing for evaluating the practical significance of the mass offset.

    Authors: We agree that explicit identification of the models and a quantitative metric would allow readers to better evaluate the practical impact of the 0.1 dex offset. The manuscript draws on the extreme value statistics framework from prior works on the abundance of early massive galaxies, but we will revise the abstract and final paragraph to name the specific models referenced and report the change in tension (e.g., reduction in sigma level or probability) before versus after the mass adjustment under the age-driven limiting case. revision: yes

  2. Referee: [Results (mass comparison)] The 0.1 dex stellar mass offset is derived from annular versus slit photometry, but the manuscript provides no details on the stellar population synthesis assumptions, IMF, or SFH templates used to convert the photometry to mass; without this, it is unclear whether the offset is independent of the same modeling choices that the paper states also contribute to tension reduction.

    Authors: The 0.1 dex offset is obtained by applying identical stellar population synthesis assumptions, IMF, and SFH templates to both the annular and slit photometry, ensuring the difference arises solely from the aperture photometry rather than from varying the models. We acknowledge that these assumptions were not stated explicitly. In revision we will add the specific choices (e.g., the SPS library, IMF, and SFH parameterization) to the methods or results section so that readers can confirm the offset is measured under consistent modeling while the paper separately notes that different modeling choices contribute to tension reduction. revision: yes

Circularity Check

0 steps flagged

No significant circularity identified

full rationale

The paper's central claim rests on direct observational comparison of new MINERVA medium-band photometry in elliptical annuli versus existing NIRSpec slit apertures, producing a measured 0.1 dex stellar mass offset for the strongest gradient. The tension reduction with extreme value statistics models is presented only as a limiting case under the explicit assumption of age-driven gradients (not asserted as proven), with additional modeling choices noted as significant contributors. No equations, fitted parameters, or self-citations reduce any load-bearing step to its own inputs by construction; the derivation chain is self-contained against external photometric data and does not invoke uniqueness theorems or ansatzes from prior author work.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard photometric reduction assumptions and the limiting-case interpretation that color gradients trace age; no free parameters or invented entities are introduced in the abstract.

axioms (2)
  • domain assumption Medium-band photometry accurately traces stellar population differences when measured in elliptical annuli
    Invoked when converting color gradients to stellar mass differences (abstract).
  • domain assumption Slit spectroscopy captures only the central region and that region is not representative when gradients exist
    Core premise motivating the comparison (abstract, first paragraph).

pith-pipeline@v0.9.1-grok · 6067 in / 1400 out tokens · 21648 ms · 2026-06-28T13:45:46.873341+00:00 · methodology

discussion (0)

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

Reference graph

Works this paper leans on

150 extracted references · 148 canonical work pages · 19 internal anchors

  1. [1]

    Spatially resolved gas-phase metallicity at z~2-3 with JWST/NIRISS

    Acharyya, A., Watson, P. J., Vulcani, B., et al. 2025, arXiv e-prints, arXiv:2508.05335, doi: 10.48550/arXiv.2508.05335

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2508.05335 2025

  2. [2]

    E., Leja, J., et al

    Akhshik, M., Whitaker, K. E., Leja, J., et al. 2023, ApJ, 943, 179, doi: 10.3847/1538-4357/aca677

    work page doi:10.3847/1538-4357/aca677 2023

  3. [3]

    2024, ApJ, 976, 224, doi: 10.3847/1538-4357/ad7396

    Alberts, S., Lyu, J., Shivaei, I., et al. 2024, ApJ, 976, 224, doi: 10.3847/1538-4357/ad7396

    work page doi:10.3847/1538-4357/ad7396 2024

  4. [4]

    2025, arXiv e-prints, arXiv:2512.03154, doi: 10.48550/arXiv.2512.03154 Astropy Collaboration, Robitaille, T

    Antwi-Danso, J., Muzzin, A., Robbins, L., et al. 2025, arXiv e-prints, arXiv:2512.03154, doi: 10.48550/arXiv.2512.03154 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f ...

    work page doi:10.48550/arxiv.2512.03154 2025

  5. [5]

    M., Lim, S., D’Eugenio, F., et al

    Baker, W. M., Lim, S., D’Eugenio, F., et al. 2025, MNRAS, 539, 557, doi: 10.1093/mnras/staf475

    work page doi:10.1093/mnras/staf475 2025

  6. [6]

    2016, extinction v0.3.0, Zenodo, doi: 10.5281/zenodo.804967

    Barbary, K. 2016, extinction v0.3.0, Zenodo, doi: 10.5281/zenodo.804967

    work page doi:10.5281/zenodo.804967 2016

  7. [7]

    2016, Journal of Open Source Software, 1, 58, doi:10.21105/joss.00058

    Barbary, K. 2016, JOSS, 1, 58, doi: 10.21105/joss.00058

    work page doi:10.21105/joss.00058 2016

  8. [8]

    F., & de Jong, R

    Bell, E. F., & de Jong, R. S. 2001, ApJ, 550, 212, doi: 10.1086/319728

    work page doi:10.1086/319728 2001

  9. [9]

    B., & Ellis, R

    Belli, S., Newman, A. B., & Ellis, R. S. 2019, ApJ, 874, 17, doi: 10.3847/1538-4357/ab07af

    work page doi:10.3847/1538-4357/ab07af 2019

  10. [10]

    L., et al

    Belli, S., Park, M., Davies, R. L., et al. 2024, Nature, 630, 54, doi: 10.1038/s41586-024-07412-1

    work page doi:10.1038/s41586-024-07412-1 2024

  11. [11]

    G., Tal, T., et al

    Bezanson, R., van Dokkum, P. G., Tal, T., et al. 2009, ApJ, 697, 1290, doi: 10.1088/0004-637X/697/2/1290

    work page doi:10.1088/0004-637x/697/2/1290 2009

  12. [12]

    2016, A&A, 596, A63, doi: 10.1051/0004-6361/201629080

    Boucaud, A., Bocchio, M., Abergel, A., et al. 2016, A&A, 596, A63, doi: 10.1051/0004-6361/201629080

    work page doi:10.1051/0004-6361/201629080 2016

  13. [13]

    2025, astropy/photutils: 2.3.0, 2.3.0 Zenodo, doi: 10.5281/zenodo.17129028

    Bradley, L., Sip˝ocz, B., Robitaille, T., et al. 2025, astropy/photutils: 2.3.0, 2.3.0 Zenodo, doi: 10.5281/zenodo.17129028

    work page doi:10.5281/zenodo.17129028 2025

  14. [14]

    2023, grizli, v1.9.11 Zenodo, doi: 10.5281/zenodo.8370018

    Brammer, G. 2023, grizli, v1.9.11 Zenodo, doi: 10.5281/zenodo.8370018

    work page doi:10.5281/zenodo.8370018 2023

  15. [15]

    , title =

    Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJ, 686, 1503, doi: 10.1086/591786 Bruzual A., G. 1983, ApJ, 273, 105, doi: 10.1086/161352

    work page internal anchor Pith review doi:10.1086/591786 2008

  16. [16]

    C., McLure, R

    Carnall, A. C., McLure, R. J., Dunlop, J. S., & Davé, R. 2018, MNRAS, 480, 4379, doi: 10.1093/mnras/sty2169

    work page internal anchor Pith review doi:10.1093/mnras/sty2169 2018

  17. [17]

    C., McLure, R

    Carnall, A. C., McLure, R. J., Dunlop, J. S., et al. 2019, MNRAS, 490, 417, doi: 10.1093/mnras/stz2544

    work page doi:10.1093/mnras/stz2544 2019

  18. [18]

    C., McLeod, D

    Carnall, A. C., McLeod, D. J., McLure, R. J., et al. 2023a, MNRAS, 520, 3974, doi: 10.1093/mnras/stad369

    work page doi:10.1093/mnras/stad369

  19. [19]

    C., McLure, R

    Carnall, A. C., McLure, R. J., Dunlop, J. S., et al. 2023b, Nature, 619, 716, doi: 10.1038/s41586-023-06158-6

    work page doi:10.1038/s41586-023-06158-6

  20. [20]

    C., Cullen, F., McLure, R

    Carnall, A. C., Cullen, F., McLure, R. J., et al. 2024, MNRAS, 534, 325, doi: 10.1093/mnras/stae2092

    work page doi:10.1093/mnras/stae2092 2024

  21. [21]

    2003, Publications of the Astronomical Society of the Pacific, 115, 763, doi: 10.1086/376392

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

    work page internal anchor Pith review doi:10.1086/376392 2003

  22. [22]

    A Bending in the Size-mass Relation of Star-forming Galaxies across $0.5 < z < 6.0$ at a Critical Stellar Mass of $10^{10}M_\odot$ Revealed by JWST

    Chen, L., Wang, T., Sun, H., et al. 2026, arXiv e-prints, arXiv:2603.22239, doi: 10.48550/arXiv.2603.22239

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2603.22239 2026

  23. [23]

    M., Kriek, M., Beverage, A

    Cheng, C. M., Kriek, M., Beverage, A. G., et al. 2024, MNRAS, 532, 3604, doi: 10.1093/mnras/stae1739

    work page doi:10.1093/mnras/stae1739 2024

  24. [24]

    Clues to inside-out quenching in quiescent galaxies at $1.2\lesssim z\lesssim2.2$: Age, Fe-, and Mg-abundance gradients from JWST-SUSPENSE

    Cheng, C. M., Slob, M., Kriek, M., et al. 2025, arXiv e-prints, arXiv:2509.12316, doi: 10.48550/arXiv.2509.12316

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2509.12316 2025

  25. [25]

    G., Glazebrook, K., Nanayakkara, T., et al

    Chittenden, H. G., Glazebrook, K., Nanayakkara, T., et al. 2026, MNRAS, 547, stag474, doi: 10.1093/mnras/stag474

    work page doi:10.1093/mnras/stag474 2026

  26. [26]

    2016, ApJ, 823, 102, doi: 10.3847/0004-637X/823/2/102

    Choi, J., Dotter, A., Conroy, C., et al. 2016, ApJ, 823, 102, doi: 10.3847/0004-637X/823/2/102

    work page internal anchor Pith review doi:10.3847/0004-637x/823/2/102 2016

  27. [27]

    G., Whitaker, K

    Clausen, M., Momcheva, I. G., Whitaker, K. E., et al. 2025, ApJ, 993, 106, doi: 10.3847/1538-4357/ae03aa

    work page doi:10.3847/1538-4357/ae03aa 2025

  28. [28]

    Cochrane, R. K. 2025, MNRAS, 544, 1530, doi: 10.1093/mnras/staf1568

    work page doi:10.1093/mnras/staf1568 2025

  29. [29]

    Modeling the Panchromatic Spectral Energy Distributions of Galaxies

    Conroy, C. 2013, ARA&A, 51, 393, doi: 10.1146/annurev-astro-082812-141017

    work page internal anchor Pith review doi:10.1146/annurev-astro-082812-141017 2013

  30. [30]

    Conroy, C., & Gunn, J. E. 2010, ApJ, 712, 833, doi: 10.1088/0004-637X/712/2/833

    work page internal anchor Pith review doi:10.1088/0004-637x/712/2/833 2010

  31. [31]

    E., & White, M

    Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486, doi: 10.1088/0004-637X/699/1/486

    work page internal anchor Pith review doi:10.1088/0004-637x/699/1/486 2009

  32. [32]

    P., Zaritsky, D., et al

    Conroy, C., Naidu, R. P., Zaritsky, D., et al. 2019, ApJ, 887, 237, doi: 10.3847/1538-4357/ab5710

    work page doi:10.3847/1538-4357/ab5710 2019

  33. [33]

    Conroy, C., White, M., & Gunn, J. E. 2010, ApJ, 708, 58, doi: 10.1088/0004-637X/708/1/58

    work page doi:10.1088/0004-637x/708/1/58 2010

  34. [34]

    E., Giavalisco, M., Ji, Z., & Cheng, Y

    Cutler, S. E., Giavalisco, M., Ji, Z., & Cheng, Y . 2023, ApJ, 945, 97, doi: 10.3847/1538-4357/acb5e9

    work page doi:10.3847/1538-4357/acb5e9 2023

  35. [35]

    E., Whitaker, K

    Cutler, S. E., Whitaker, K. E., Weaver, J. R., et al. 2024, ApJL, 967, L23, doi: 10.3847/2041-8213/ad464c de Graaff, A., Setton, D. J., Brammer, G., et al. 2025, Nature Astronomy, 9, 280, doi: 10.1038/s41550-024-02424-3

    work page doi:10.3847/2041-8213/ad464c 2024

  36. [36]

    2014, MNRAS, 438, 1870, doi: 10.1093/mnras/stt2331 D’Eugenio, F., van der Wel, A., Wu (柏锋), P.-F., et al

    Dekel, A., & Burkert, A. 2014, MNRAS, 438, 1870, doi: 10.1093/mnras/stt2331 D’Eugenio, F., van der Wel, A., Wu (柏锋), P.-F., et al. 2020, MNRAS, 497, 389, doi: 10.1093/mnras/staa1937 D’Eugenio, F., Pérez-González, P. G., Maiolino, R., et al. 2024, Nature Astronomy, 8, 1443, doi: 10.1038/s41550-024-02345-1

    work page doi:10.1093/mnras/stt2331 2014

  37. [37]

    2016, ApJS, 222, 8, doi: 10.3847/0067-0049/222/1/8

    Dotter, A. 2016, ApJS, 222, 8, doi: 10.3847/0067-0049/222/1/8

    work page internal anchor Pith review doi:10.3847/0067-0049/222/1/8 2016

  38. [38]

    S., et al

    Drlica-Wagner, A., Sevilla-Noarbe, I., Rykoff, E. S., et al. 2018, ApJS, 235, 33, doi: 10.3847/1538-4365/aab4f5

    work page doi:10.3847/1538-4365/aab4f5 2018

  39. [39]

    J., Li, Q., et al

    Duan, Q., Conselice, C. J., Li, Q., et al. 2025, MNRAS, 540, 774, doi: 10.1093/mnras/staf638

    work page doi:10.1093/mnras/staf638 2025

  40. [40]

    S., Abraham, R

    Dunlop, J. S., Abraham, R. G., Ashby, M. L. N., et al. 2021, PRIMER: Public Release IMaging for Extragalactic Research„ JWST Proposal. Cycle 1, ID. #1837

    2021

  41. [41]

    N., et al., 2009, ApJS, 182, 543 Adelman-McCarthy J

    Foreman-Mackey, D., Sick, J., & Johnson, B. 2014, python-fsps: Python bindings to FSPS (v0.1.1), v0.1.1 Zenodo, doi: 10.5281/zenodo.12157

    work page doi:10.5281/zenodo.12157 2014

  42. [42]

    C., Annunziatella, M., et al

    Forrest, B., Marsan, Z. C., Annunziatella, M., et al. 2020, ApJ, 903, 47, doi: 10.3847/1538-4357/abb819 Fortuné, S., Remus, R.-S., Kimmig, L. C., Burkert, A., & Dolag, K. 2025, A&A, 704, A185, doi: 10.1051/0004-6361/202554805 COLORGRADIENTS OFULTRA-MASSIVEQUIESCENTGALAXIES21

    work page doi:10.3847/1538-4357/abb819 2020

  43. [43]

    2017, Nature, 544, 71, doi: 10.1038/nature21680

    Glazebrook, K., Schreiber, C., Labbé, I., et al. 2017, Nature, 544, 71, doi: 10.1038/nature21680

    work page doi:10.1038/nature21680 2017

  44. [44]

    2024, Nature, 628, 277, doi: 10.1038/s41586-024-07191-9

    Glazebrook, K., Nanayakkara, T., Schreiber, C., et al. 2024, Nature, 628, 277, doi: 10.1038/s41586-024-07191-9

    work page doi:10.1038/s41586-024-07191-9 2024

  45. [45]

    2012, The DrizzlePac Handbook (Baltimore, MD: STScI)

    Gonzaga, S., Hack, W., Fruchter, A., & Mack, J. 2012, The DrizzlePac Handbook (Baltimore, MD: STScI)

    2012

  46. [46]

    E., Janish, R., Ma, C.-P., et al

    Greene, J. E., Janish, R., Ma, C.-P., et al. 2015, ApJ, 807, 11, doi: 10.1088/0004-637X/807/1/11

    work page doi:10.1088/0004-637x/807/1/11 2015

  47. [47]

    Adams, J. J. 2012, ApJ, 750, 32, doi: 10.1088/0004-637X/750/1/32

    work page doi:10.1088/0004-637x/750/1/32 2012

  48. [48]

    A., Kocevski, D

    Grogin, N. A., Kocevski, D. D., Faber, S. M., et al. 2011, ApJS, 197, 35, doi: 10.1088/0067-0049/197/2/35

    work page doi:10.1088/0067-0049/197/2/35 2011

  49. [49]

    2011, ApJ, 735, 18, doi: 10.1088/0004-637X/735/1/18

    Guo, Y ., Giavalisco, M., Cassata, P., et al. 2011, ApJ, 735, 18, doi: 10.1088/0004-637X/735/1/18

    work page doi:10.1088/0004-637x/735/1/18 2011

  50. [50]

    L., Whitaker, K

    Hamadouche, M. L., Whitaker, K. E., Valentino, F., et al. 2026, arXiv e-prints, arXiv:2602.02485, doi: 10.48550/arXiv.2602.02485

    work page doi:10.48550/arxiv.2602.02485 2026

  51. [51]

    2012, MNRAS, 420, L18, doi:10.1111/j.1745-3933.2011.01184.x

    Harrison, I., & Coles, P. 2011, MNRAS, 418, L20, doi: 10.1111/j.1745-3933.2011.01134.x

    work page doi:10.1111/j.1745-3933.2011.01134.x 2011

  52. [52]

    J., Adams, N

    Harvey, T., Conselice, C. J., Adams, N. J., et al. 2025, ApJ, 978, 89, doi: 10.3847/1538-4357/ad8c29

    work page doi:10.3847/1538-4357/ad8c29 2025

  53. [53]

    2013, ApJS, 208, 19, doi: 10.1088/0067-0049/208/2/19

    Hinshaw, G., Larson, D., Komatsu, E., et al. 2013, ApJS, 208, 19, doi: 10.1088/0067-0049/208/2/19

    work page internal anchor Pith review doi:10.1088/0067-0049/208/2/19 2013

  54. [54]

    Hunter, J. D. 2007, CSE, 9, 90, doi: 10.1109/MCSE.2007.55

    work page doi:10.1109/mcse.2007.55 2007

  55. [55]

    2005, A&A, 439, 863, doi: 10.1051/0004-6361:20041961

    Ilbert, O., Tresse, L., Zucca, E., et al. 2005, A&A, 439, 863, doi: 10.1051/0004-6361:20041961

    work page doi:10.1051/0004-6361:20041961 2005

  56. [56]

    B., Mobasher, B., et al

    Jafariyazani, M., Newman, A. B., Mobasher, B., et al. 2020, ApJL, 897, L42, doi: 10.3847/2041-8213/aba11c

    work page doi:10.3847/2041-8213/aba11c 2020

  57. [57]

    K., Carnall, A

    Jespersen, C. K., Carnall, A. C., & Lovell, C. C. 2025, ApJL, 988, L19, doi: 10.3847/2041-8213/adeb7c

    work page doi:10.3847/2041-8213/adeb7c 2025

  58. [58]

    D., Leja, J., Conroy, C., & Speagle, J

    Johnson, B. D., Leja, J., Conroy, C., & Speagle, J. S. 2021, ApJS, 254, 22, doi: 10.3847/1538-4365/abef67

    work page internal anchor Pith review doi:10.3847/1538-4365/abef67 2021

  59. [59]

    2025, The Astrophysical Journal Letters, 978, L39, doi: 10.3847/2041-8213/ada150

    Ju, M., Wang, X., Jones, T., et al. 2025, ApJL, 978, L39, doi: 10.3847/2041-8213/ada150

    work page doi:10.3847/2041-8213/ada150 2025

  60. [60]

    2026, ApJ, 997, 29, doi: 10.3847/1538-4357/ae0a18

    Kawinwanichakij, L., Glazebrook, K., Nanayakkara, T., et al. 2026, ApJ, 997, 29, doi: 10.3847/1538-4357/ae0a18

    work page doi:10.3847/1538-4357/ae0a18 2026

  61. [61]

    Kepner, J. V . 1999, ApJ, 520, 59, doi: 10.1086/307419

    work page doi:10.1086/307419 1999

  62. [62]

    1999, ApJ, 527, 573, doi: 10.1086/308092

    Kobayashi, C., & Arimoto, N. 1999, ApJ, 527, 573, doi: 10.1086/308092

    work page doi:10.1086/308092 1999

  63. [63]

    M., Faber, S

    Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36, doi: 10.1088/0067-0049/197/2/36

    work page doi:10.1088/0067-0049/197/2/36 2011

  64. [64]

    2013, ApJL, 775, L16, doi: 10.1088/2041-8205/775/1/L16

    Kriek, M., & Conroy, C. 2013, ApJL, 775, L16, doi: 10.1088/2041-8205/775/1/L16

    work page doi:10.1088/2041-8205/775/1/l16 2013

  65. [65]

    G., Price, S

    Kriek, M., Beverage, A. G., Price, S. H., et al. 2024, ApJ, 966, 36, doi: 10.3847/1538-4357/ad2df9

    work page doi:10.3847/1538-4357/ad2df9 2024

  66. [66]

    Kron, R. G. 1980, ApJS, 43, 305, doi: 10.1086/190669 Labbé, I., Franx, M., Rudnick, G., et al. 2003, AJ, 125, 1107, doi: 10.1086/346140

    work page doi:10.1086/190669 1980

  67. [67]

    C., Johnson, B

    Leja, J., Carnall, A. C., Johnson, B. D., Conroy, C., & Speagle, J. S. 2019a, ApJ, 876, 3, doi: 10.3847/1538-4357/ab133c

    work page internal anchor Pith review doi:10.3847/1538-4357/ab133c

  68. [68]

    2019b, ApJL, 880, L9, doi: 10.3847/2041-8213/ab2f8c

    Leja, J., Tacchella, S., & Conroy, C. 2019b, ApJL, 880, L9, doi: 10.3847/2041-8213/ab2f8c

    work page doi:10.3847/2041-8213/ab2f8c 2041

  69. [69]

    2026, arXiv e-prints, arXiv:2602.13114, doi: 10.48550/arXiv.2602.13114

    Leung, H.-H., Wild, V ., Papathomas, M., et al. 2026, arXiv e-prints, arXiv:2602.13114, doi: 10.48550/arXiv.2602.13114

    work page doi:10.48550/arxiv.2602.13114 2026

  70. [70]

    2024, Research in Astronomy and Astrophysics, 24, 015009, doi: 10.1088/1674-4527/ad0864

    Lin, H., Gong, Y ., Yue, B., & Chen, X. 2024, Research in Astronomy and Astrophysics, 24, 015009, doi: 10.1088/1674-4527/ad0864

    work page doi:10.1088/1674-4527/ad0864 2024

  71. [71]

    2019, ApJ, 872, 50, doi: 10.3847/1538-4357/aafa84

    Lin, L., Hsieh, B.-C., Pan, H.-A., et al. 2019, ApJ, 872, 50, doi: 10.3847/1538-4357/aafa84

    work page doi:10.3847/1538-4357/aafa84 2019

  72. [72]

    2022, ApJL, 937, L30, doi: 10.3847/2041-8213/ac927f

    Liu, B., & Bromm, V . 2022, ApJL, 937, L30, doi: 10.3847/2041-8213/ac927f

    work page doi:10.3847/2041-8213/ac927f 2022

  73. [73]

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

    Lovell, C. C., Harrison, I., Harikane, Y ., Tacchella, S., & Wilkins, S. M. 2022, Monthly Notices of the Royal Astronomical Society, 518, 2511, doi: 10.1093/mnras/stac3224

    work page doi:10.1093/mnras/stac3224 2022

  74. [74]

    Prevailing thermally-pulsing-asymptotic-giant branch stars in the near-infrared rest-frame spectra of distant quiescent galaxies: towards robust galaxy ages and masses

    Lu, S., Daddi, E., Maraston, C., et al. 2026, arXiv e-prints, arXiv:2604.19942, doi: 10.48550/arXiv.2604.19942 M Evans, N. H., & Peacock, B. 2001, Measurement Science and Technology, 12, 117, doi: 10.1088/0957-0233/12/1/702

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2604.19942 2026

  75. [75]

    2023, A&A, 672, A71, doi: 10.1051/0004-6361/202345851

    Maio, U., & Viel, M. 2023, A&A, 672, A71, doi: 10.1051/0004-6361/202345851

    work page doi:10.1051/0004-6361/202345851 2023

  76. [76]

    C., Marchesini, D., Brammer, G

    Marsan, Z. C., Marchesini, D., Brammer, G. B., et al. 2015, ApJ, 801, 133, doi: 10.1088/0004-637X/801/2/133

    work page doi:10.1088/0004-637x/801/2/133 2015

  77. [77]

    2026, A&A, 705, A236, doi: 10.1051/0004-6361/202555974

    Martorano, M., van der Wel, A., Gebek, A., et al. 2026, A&A, 705, A236, doi: 10.1051/0004-6361/202555974

    work page doi:10.1051/0004-6361/202555974 2026

  78. [78]

    V ., et al

    McConachie, I., de Graaff, A., Maseda, M. V ., et al. 2025, arXiv e-prints, arXiv:2510.25024, doi: 10.48550/arXiv.2510.25024

    work page doi:10.48550/arxiv.2510.25024 2025

  79. [79]

    B., van Dokkum, P., & Mowla, L

    Miller, T. B., van Dokkum, P., & Mowla, L. 2023, ApJ, 945, 155, doi: 10.3847/1538-4357/acbc74

    work page doi:10.3847/1538-4357/acbc74 2023

  80. [80]

    C., et al

    Mobasher, B., Dahlen, T., Ferguson, H. C., et al. 2015, ApJ, 808, 101, doi: 10.1088/0004-637X/808/1/101

    work page doi:10.1088/0004-637x/808/1/101 2015

Showing first 80 references.