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Evolution of the S\'ersic Index up to z=2.5 from JWST and HST

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read The median Sérsic index of galaxies barely changes from z=2.5 to z=0.5, except for the most massive galaxies, whose profiles steepen from n≈2.5 to n≈4 by z<1.

desk verdict Solid empirical step forward on near-IR Sérsic indices; the slow-evolution result is probably safe, but the optical-vs-NIR wavelength claim rests on a thin cross-survey comparison and the abstract overstates the green-valley scatter. read the letter →

arxiv 2501.02956 v1 pith:OKWAOVMN submitted 2025-01-06 astro-ph.GA

Marco Martorano , Arjen van der Wel , Maarten Baes , Eric F. Bell , Gabriel Brammer , Marijn Franx , Andrea Gebek , Sharon E. Meidt
show 7 more authors
Tim B. Miller Erica Nelson Angelos Nersesian Sedona H. Price Pieter van Dokkum Katherine Whitaker Stijn Wuyts
This is my paper · ORCID
classification astro-ph.GA
keywords Sérsicindexgalaxystructureevolutionrest-framenear-infraredJWSTNIRCamstarformationquiescentgalaxies
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 measures how the radial concentration of galaxy light, quantified by the Sérsic index $n$, changes between redshift 2.5 and 0.5, using JWST near-infrared images of about 15,000 galaxies combined with HST optical images of a similar sample. It argues that, at fixed stellar mass below about $10^{10.5}\,M_\odot$, the median Sérsic index barely changes over roughly 11 billion years: galaxies keep approximately exponential profiles at all redshifts studied. The exception is the most massive galaxies ($M_\star > 10^{11}\,M_\odot$), whose median $n$ rises from about 2.5 to about 4 toward $z<1$. The paper also establishes that star-forming galaxies have lower $n$ than quiescent galaxies in both optical and near-infrared light, and that at $z>1$ the near-infrared $n$ depends on star-formation activity but not on stellar mass. These results matter because they tie the buildup of central concentrations to mass and quenching, and provide near-infrared light profiles that simulations can compare directly with stellar mass profiles.

What carries the argument

The central object is the Sérsic index $n$, the shape parameter of the Sérsic profile $I(r)\propto \exp[-b_n(r/r_e)^{1/n}]$, with $n=1$ exponential-like and $n=4$ de Vaucouleurs-like. The argument is carried by comparing two rest-frame measurements on HST-selected parent samples: $n$ at 0.5 µm from HST/CANDELS F125W/F160W fits and $n$ at 1.5 µm from JWST/NIRCam F277W/F444W fits in COSMOS-Web and PRIMER-COSMOS, interpolated to the rest-frame wavelengths. Stellar masses, star-formation rates, and the quiescent/star-forming classification come from SED fitting and an offset from the star-forming main sequence; redshift evolution is characterized with fits $n_\lambda \propto (1+z)^{\beta_\lambda}$. The load-bearing comparison is the difference between the two rest-frame indices for the same mass-redshift bins.

What would settle it

Measure rest-frame 0.5 µm and 1.5 µm Sérsic indices for the same galaxies, using the roughly 10% of JWST sources with HST/CANDELS coverage or a single survey covering both wavelengths, and check whether the $n_{1.5\,\mu m} > n_{0.5\,\mu m}$ offset for star-forming galaxies at $z>1$ persists; if it vanishes, the claimed wavelength dependence is a sample-selection artifact.

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Extended reading notes

Core claim

The paper's central claim is that the rest-frame near-infrared Sérsic index, measured at 1.5 µm with JWST/NIRCam, is a stable structural parameter for most galaxies: for stellar masses below about $10^{10.5}\,M_\odot$ the median $n \approx 1.4$ at all redshifts from 0.5 to 2.5, and the same holds in the rest-frame optical at 0.5 µm. Only galaxies with $M_\star > 10^{11}\,M_\odot$ show significant evolution, increasing from $n\approx 2.5$ at $z\approx 2.5$ to $n\approx 4$ at $z<1$, with the optical index evolving more strongly with redshift than the near-IR index. The higher near-IR than optical $n$ for star-forming galaxies at $z>1$ is attributed to radially varying dust and young-star outshining in the optical, while the structural distinction between quiescent and star-forming galaxies persists in the near-IR, implying a physical difference in stellar mass distribution rather than a mere light-profile artifact. Two trends are new: at $z>1$ the median near-IR $n$ tracks specific star-formation rate without any mass dependence, and the scatter in near-IR $n$ peaks in the green valley (0.25 dex) versus 0.18 dex elsewhere, a peak hidden in the optical by dust and young stars.

Load-bearing premise

The optical and near-IR samples come from different surveys with only about 10% overlap, so the comparison assumes the two samples are statistically equivalent populations at fixed mass, redshift, and star-formation activity.

Editorial extensions

If this is right

  • Below $M_\star\approx10^{10.5}\,M_\odot$, the radial light profiles of galaxies are essentially in place by $z=2.5$; subsequent evolution is mostly growth in stellar mass along a constant $n$, not a transformation of the profile.
  • The late-time rise in $n$ for $M_\star>10^{11}\,M_\odot$ means the most massive galaxies build their concentrated central profiles at $z<1$, plausibly through dissipationless merging and central growth.
  • Rest-frame near-IR $n$ is a cleaner proxy for the stellar mass profile than optical $n$; optical measurements of massive star-forming galaxies at $z>1$ are flattened by dust and young stars.
  • The elevated scatter in near-IR $n$ in the green valley indicates that the transition from star-forming to quiescent is structurally diverse, with multiple possible pathways.
  • The tabulated $n_{1.5\,\mu m}$ measurements give simulations a direct observable to match for radial stellar mass profiles.

Reading between the lines

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

  • If the near-IR index stays constant at fixed mass while sizes grow, then the observed size evolution of low-mass galaxies must be driven by mass growth along a fixed concentration, which would shift the interpretation of the size-mass relation from structural transformation to assembly.
  • The wavelength-dependent $n$ for massive star-forming galaxies implies that scaling relations built on optical concentration (for example, black-hole–bulge relations) may be systematically biased at $z>1$; near-IR-based relations should be tested.
  • A direct test of the sample-equivalence assumption would be to measure both rest-frame indices for the same galaxies in the roughly 10% overlap region, or to use JWST filters that cover rest-frame optical at $z>3$ to trace when the mass dependence of $n$ first appears.
  • The green-valley scatter peak suggests that structural diversity could be used to separate quenching mechanisms, such as mergers versus feedback, in future samples with kinematic or environmental data.
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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 / 4 minor

Summary. The paper measures rest-frame 1.5 micron Sérsic indices for approximately 15,000 galaxies in the COSMOS-Web and PRIMER-COSMOS fields with JWST/NIRCam and combines them with previously published rest-frame 0.5 micron Sérsic indices from HST/CANDELS. Over 0.5<z<2.5 and stellar masses 10^9.5 to 10^11.5 Msun, the authors find that the median Sérsic index evolves weakly with redshift for galaxies below ~10^10.5 Msun, while the most massive galaxies (M*>10^11 Msun) increase from n~2.5 at z=2.5 to n~4 at z<1. They further report that star-forming galaxies have lower optical than near-IR n at z>1 but not at z<1, that at z>1 near-IR n depends strongly on specific star formation rate but not on stellar mass, and that the scatter in near-IR n peaks in the green valley. The paper provides tabulated medians and percentiles and fits the redshift evolution with a power-law n ∝ (1+z)^beta.

Significance. If the results are robust, this is a valuable empirical benchmark: it extends structural measurements to rest-frame near-IR at cosmic noon with a sample an order of magnitude larger than previous JWST studies, and it provides tabulated data that can be used to test simulations. Strengths include the careful documentation of sample cuts, bootstrap-resampled fits, the use of a consistent Prospector setup for stellar masses and SFRs across the two samples, and the explicit Appendix B data tables. The main novel claim, the optical-near-IR wavelength dependence among star-forming galaxies at z>1, rests on a cross-survey comparison that is not yet validated; if that validation succeeds, the paper makes a strong case that dust and stellar-population gradients affect optical profiles more than near-IR profiles.

major comments (3)
  1. [Sections 2.2 and Appendix A] The claim that at z>1 star-forming galaxies have lower rest-frame 0.5 micron than 1.5 micron Sérsic indices is built on comparing two largely disjoint samples: the HST/CANDELS sample fitted with Galfit and the JWST/COSMOS-Web+PRIMER sample fitted with GalfitM, using different filters, PSF models, and parent photometric catalogs. Appendix A validates stellar masses and SFRs for the 1,656 overlapping galaxies, but it does not validate the Sérsic indices themselves. A systematic offset in n between the two pipelines that depends on redshift, mass, or galaxy type would directly produce or erase the reported wavelength dependence. The authors should compare Sérsic indices measured from HST and JWST imaging for the same galaxies (e.g., n from F160W vs. n from F277W), or otherwise demonstrate that the pipeline differences do not affect the median n difference, before the wavelength-dependence result can be considered secure.
  2. [Section 3.2, Figure 4] The new result that at z>1 the median near-IR Sérsic index depends on sSFR but not on stellar mass is stated qualitatively. The figure shows spline-quantile regressions and medians, but no quantitative measure of the strength of the mass dependence at fixed sSFR (e.g., a fitted slope of n1.5um versus log M* in narrow sSFR bins, with uncertainties). Without such a measure, the absence of a mass dependence is not demonstrated; the reader cannot tell whether the apparent flatness is consistent with, say, a 0.3 dex change in n across the mass range. Adding this quantification would make the claim testable.
  3. [Section 2.1] The decisions to retain flag=1 galaxies and to clip n to the [0.2,8] range are justified with summary statements (the sample is not biased; medians change by <4%) but no supporting diagnostics are shown. If the flag=1 galaxies or the clipped galaxies are concentrated in particular mass-redshift bins (e.g., the highest masses, where fits are most difficult), these choices could affect exactly the bins that drive the reported high-mass evolution and the near-IR/optical difference. The authors should provide the fraction of flag=1 and clipped sources per mass-redshift bin, or repeat the key analyses excluding these sources.
minor comments (4)
  1. [Abstract and Section 1] The text uses '≈ 15.000' with a period as the thousands separator; these should be '≈15,000'.
  2. [Figure 2 caption] The caption for the right panel reads 'rest-frame 0.5µm (left panel)'; it should say 'right panel'.
  3. [Appendix A] The sentence 'These differences do not play a major role in this work' would benefit from a quantitative justification, especially because SFR differences up to 0.6 dex could shift galaxies across the adopted quiescence boundary.
  4. [Section 4] The statement that 'conclusions based on observations such as those presented in this paper will always remain speculative' is vague and could be replaced with a more specific caveat about the limitations of Sérsic fits and projection effects.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: this is an empirical measurement paper whose central claims are summary statistics and descriptive fits to the measured Sérsic indices, with no derivation that reduces to its own inputs.

full rationale

The paper is an observational measurement study, not a derivation. The central claims—median Sérsic index as a function of redshift, stellar mass, and star-formation activity—are computed directly from Galfit/GalfitM Sérsic profile fits to JWST and HST imaging. The only fitted quantities, the β_λ exponents in Table 1 (n_λ ∝ (1+z)^β_λ), are explicitly descriptive fits to the same median data, not independent predictions. The near-IR Sérsic catalog is taken from the authors' prior work (Martorano et al. 2024), but that catalog is a measurement product, not an unverified theorem or a parameter fitted to the present paper's claims; using one's own previously published measurements is normal and does not create circularity. The prior expectation that optical and near-IR Sérsic indices are similar (Martorano et al. 2023) is cited as motivation, but the conclusion is re-derived from the new data rather than imported. The potential issue that the optical and near-IR samples are only ~10% overlapping is a data-comparison and selection-function concern, not a circular-reasoning concern: the paper does not define the wavelength-dependence claim in terms of the overlap or fit it by construction. Similarly, Appendix A validates stellar masses and SFRs rather than Sérsic indices, which is a limitation of cross-sample comparability, not a circular step. No equation is shown to be equivalent to another by construction, no fitted parameter is renamed as a prediction, and no load-bearing uniqueness theorem is imported from self-citations. The score is therefore 0.

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

The paper's quantitative claims rest on several carried-in assumptions from the literature and from the authors' previous work: the Sérsic parameterization, the stellar masses and SFRs from Prospector, the SFMS ridge, and the comparability of the two survey samples. No new physical entities are introduced.

free parameters (4)
  • Beta exponent for n evolution = Table 1 values, e.g. -0.77 to 0.45 depending on mass bin and wavelength
    The parameterization n proportional to (1+z)^beta is fitted to the measured median Sérsic indices in each stellar mass bin and for each population (full, star-forming, quiescent). The inferred evolution claims rest on these fitted exponents.
  • Quiescence threshold offset = 0.8 dex below the star-forming main sequence ridge
    Galaxies are classified as quiescent or star-forming based on a chosen offset of 0.8 dex from the SFMS ridge defined by Leja et al. (2022). This choice affects the split-sample analysis and the quoted median n for each population.
  • Sérsic index clipping range = n between 0.2 and 8
    Galaxies with fitted n outside this range have their n set to the nearest boundary value. This hand-chosen clipping affects the distribution and medians, and the paper notes it can shift medians by up to 4%.
  • Stellar mass threshold = M* = 10^9.5 M_sun
    A stellar-mass completeness threshold is adopted to define the sample. The paper claims completeness to z=2.5 based on Tal et al. (2014), but the exact threshold is a selection choice that could affect the low-mass trends.
assumptions (4)
  • domain assumption The Sérsic profile accurately describes galaxy radial light profiles.
    The entire measurement is based on fitting Sérsic profiles to images, which is standard in the field but is a modeling assumption that can fail for irregular or merging galaxies.
  • domain assumption The rest-frame optical and near-IR samples are representative of the same underlying galaxy population despite different survey footprints and selection functions.
    The comparison between n0.5 and n1.5 assumes the HST/CANDELS and JWST/COSMOS-Web and PRIMER samples are statistically equivalent. Only about 10% of the JWST sample is also in the HST sample, so sample differences could masquerade as wavelength differences.
  • domain assumption Rest-frame near-IR luminosity traces the stellar mass distribution better than rest-frame optical light.
    The paper interprets n1.5 as more representative of the stellar mass profile, based on the reduced impact of dust and young stars at longer wavelengths. This is a physical assumption from the literature, not tested directly in this work.
  • domain assumption The star-forming main sequence ridge from Leja et al. (2022) correctly separates quiescent and star-forming galaxies.
    The quiescent/star-forming classification uses the SFMS ridge and the 0.8 dex offset. Appendix A shows SFR differences up to 0.6 dex between the two SED fitting runs used here, so the ridge location is uncertain at that level.

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Cite this review

Pith. "Pith review of Evolution of the S\'ersic Index up to z=2.5 from JWST and HST." pith.science (2026). https://pith.science/paper/OKWAOVMN

@misc{pith2026250102956,
  author       = {Pith},
  title        = {Pith review of: Evolution of the S\'ersic Index up to z=2.5 from JWST and HST},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/OKWAOVMN}},
  note         = {Machine review of arXiv:2501.02956}
}
abstract

The James Webb Space Telescope (JWST) is unveiling the rest-frame near-IR structure of galaxies. We measure the evolution with redshift of the rest-frame optical and near-IR S\'ersic index ($n$), and examine the dependence on stellar mass and star-formation activity across the redshift range $0.5\leq z\leq2.5$. We infer rest-frame near-IR S\'ersic profiles for $\approx 15.000$ galaxies in publicly available NIRCam imaging mosaics from the COSMOS-Web and PRIMER surveys. We augment these with rest-frame optical S\'ersic indices, previously measured from HST imaging mosaics. The median S\'ersic index evolves slowly or not at all with redshift, except for very high-mass galaxies ($M_\star > 10^{11}~{\text{M}}_\odot$), which show an increase from $n\approx 2.5$ to $n\approx 4$ at $z<1$. High-mass galaxies have higher $n$ than lower-mass galaxies ($M_\star=10^{9.5}~{\text{M}}_\odot$) at all redshifts, with a stronger dependence in the rest-frame near-IR than in the rest-frame optical at $z>1$. This wavelength dependence is caused by star-forming galaxies that have lower optical than near-IR $n$ at z>1 (but not at z<1). Both at optical and near-IR wavelengths, star-forming galaxies have lower $n$ than quiescent galaxies, fortifying the connection between star-formation activity and radial stellar mass distribution. At $z>1$ the median near-IR $n$ varies strongly with star formation activity, but not with stellar mass. The scatter in near-IR $n$ is higher in the green valley (0.25 dex) than on the star-forming sequence and among quiescent galaxies (0.18 dex) -- this trend is not seen in the optical because dust and young stars contribute to the variety in optical light profiles. Our newly measured rest-frame near-IR radial light profiles motivate future comparisons with radial stellar mass profiles of simulated galaxies as a stringent constraint on processes that govern galaxy formation.

Figures

Figures reproduced from arXiv: 2501.02956 by the authors.

Figure 1
Figure 1. Sérsic index at rest-frame 1.5µm (left panel) and rest-frame 0.5µm (right panel) as a function of stellar mass. Dots in the background represent nλ of the individual star-forming (blue) and quiescent (red) galaxies. Filled circles show the median nλ in stellar mass bins of width 0.25 dex and four redshift bins from low-z (light) to high-z (dark). Error bars identify the statistical uncertainties computed as σ/ √ N w… view at source ↗
Figure 2
Figure 2. Sérsic index at rest-frame 1.5µm (left panel) and rest-frame 0.5µm (left panel) as a function of redshift. Dots in the background represent nλ of the individual star-forming (blue) and quiescent (red) galaxies. Filled circles show the median nλ in redshift bins of width 0.25 and in four stellar mass bins from high-M⋆ (dark) to high-M⋆ (light). Error bars identify the statistical uncertainties computed as σ/ √ N with… view at source ↗
Figure 3
Figure 3. Star-formation rate (SFR) vs stellar mass in four redshift bins color-coded by n1.5µm. The dashed black line represents the SFR-ridge identified in Leja et al. (2020). Solid lines show the median trends in five n1.5µm bins. Hexbins are drawn around groups of at least 10 galaxies and colored with the median n1.5µm. For reference, constant log(sSFR) lines are shown in light grey. Exponential-like galaxies lay on the S… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Sérsic index as a function of the specific Star Formation Rate (sSFR) in four redshift bins. Each color represents a stellar mass bin with solid lines showing spline-quantile regression and squares showing the median Sérsic index in sSFR bins. Error bars show the stati…
Figure 5
Figure 5. Figure 5: SFR-stellar mass plane for galaxies at redshifts 0.5 ≤ z < 1 in hexbins, color-coded by half of the 16-84th percentile range of log10(nλ) computed over at least 10 galaxies. Numerical values represent the median nλ of galaxies within the hexbin. Left: n0.5µm; Right: n1…
Figure 6
Figure 6. Figure 6: Same as [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]
Figure 7
Figure 7. Figure 7: Same as [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]

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Forward citations

Cited by 2 Pith papers

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Reference graph

Works this paper leans on

125 extracted references · 28 canonical work pages · cited by 2 Pith papers

  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]

    2002, Monthly Notices of the Royal Astronomical Society, 329, 355

    Arnouts, S., Moscardini, L., Vanzella, E., et al. 2002, Monthly Notices of the Royal Astronomical Society, 329, 355

    2002

  4. [4]

    2024, , 683, A182

    Baes , M., Mosenkov , A., Kelly , R., et al. 2024, , 683, A182

    2024

  5. [5]

    M., Koo , D

    Barro , G., Faber , S. M., Koo , D. C., et al. 2017, , 840, 47

    2017

  6. [6]

    M., P \'e rez-Gonz \'a lez , P

    Barro , G., Faber , S. M., P \'e rez-Gonz \'a lez , P. G., et al. 2014, , 791, 52

    2014

  7. [7]

    F., van der Wel , A., Papovich , C., et al

    Bell , E. F., van der Wel , A., Papovich , C., et al. 2012, , 753, 167

    2012

  8. [8]

    R., Brinkmann , J., Csabai , I., et al

    Blanton , M. R., Brinkmann , J., Csabai , I., et al. 2003, , 125, 2348

    2003

Show all 125 references
  1. [9]

    Bluck , A. F. L., Mendel , J. T., Ellison , S. L., et al. 2014, , 441, 599

    2014

  2. [10]

    Bluck , A. F. L., Piotrowska , J. M., & Maiolino , R. 2023, , 944, 108

    2023

  3. [11]

    B., S \'a nchez-Janssen , R., Labb \'e , I., et al

    Brammer , G. B., S \'a nchez-Janssen , R., Labb \'e , I., et al. 2012, , 758, L17

    2012

  4. [12]

    S., Conselice , C

    Bundy , K., Ellis , R. S., Conselice , C. J., et al. 2006, , 651, 120

    2006

  5. [13]

    2016, Monthly Notices of the Royal Astronomical Society, 465, 54

    Calura, F., Pozzi, F., Cresci, G., et al. 2016, Monthly Notices of the Royal Astronomical Society, 465, 54

    2016

  6. [14]

    M., Kartaltepe , J

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

    2023

  7. [15]

    2010, , 404, 2151

    Ceverino , D., Dekel , A., & Bournaud , F. 2010, , 404, 2151

    2010

  8. [16]

    2003, , 115, 763

    Chabrier , G. 2003, , 115, 763

    2003

  9. [17]

    2017, , 233, 19

    Chang , Y.-Y., Le Floc'h , E., Juneau , S., et al. 2017, , 233, 19

    2017

  10. [18]

    2019, , 877, 48

    Chauke , P., van der Wel , A., Pacifici , C., et al. 2019, , 877, 48

    2019

  11. [19]

    2022, , 939, L7

    Chen , C.-C., Gao , Z.-K., Hsu , Q.-N., et al. 2022, , 939, L7

    2022

  12. [20]

    M., Koo , D

    Chen , Z., Faber , S. M., Koo , D. C., et al. 2020, , 897, 102

    2020

  13. [21]

    Conselice , C. J. 2014, , 52, 291

    2014

  14. [22]

    A., et al

    Costantin , L., Gillman , S., Boogaard , L. A., et al. 2024, arXiv e-prints, arXiv:2407.00153

    2024 arXiv

  15. [23]

    G., Vega-Ferrero , J., et al

    Costantin , L., P \'e rez-Gonz \'a lez , P. G., Vega-Ferrero , J., et al. 2023, , 946, 71

    2023

  16. [24]

    J., Springel , V., White , S

    Croton , D. J., Springel , V., White , S. D. M., et al. 2006, , 365, 11

    2006

  17. [25]

    E., Whitaker , K

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

    2024

  18. [26]

    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

  19. [27]

    L., Bagley , M

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

    2023

  20. [28]

    L., Dickinson , M., Ferguson , H

    Finkelstein , S. L., Dickinson , M., Ferguson , H. C., et al. 2017, The Cosmic Evolution Early Release Science (CEERS) Survey , JWST Proposal ID 1345. Cycle 0 Early Release Science

    2017

  21. [29]

    G., Schreiber , N

    Franx , M., van Dokkum , P. G., Schreiber , N. M. F., et al. 2008, , 688, 770

    2008

  22. [30]

    G., Crain , R

    Furlong , M., Bower , R. G., Crain , R. A., et al. 2015, ArXiv e-prints [ [arXiv] 1510.05645 ]

    2015 arXiv

  23. [31]

    Gadotti , D. A. 2009, , 393, 1531

    2009

  24. [32]

    D., Monachesi , A., G \'o mez , F

    Gargiulo , I. D., Monachesi , A., G \'o mez , F. A., et al. 2022, , 512, 2537

    2022

  25. [33]

    2018, , 474, 3976

    Genel , S., Nelson , D., Pillepich , A., et al. 2018, , 474, 3976

    2018

  26. [34]

    2023, , 676, A26

    Gillman , S., Gullberg , B., Brammer , G., et al. 2023, , 676, A26

    2023

  27. [35]

    2024, arXiv e-prints, arXiv:2406.03544

    Gillman , S., Smail , I., Gullberg , B., et al. 2024, arXiv e-prints, arXiv:2406.03544

    2024

  28. [36]

    A., Kocevski , D

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

    2011

  29. [37]

    P., Vika , M., et al

    H \"a u ler , B., Bamford , S. P., Vika , M., et al. 2013, , 430, 330

    2013

  30. [38]

    G., et al

    Huertas-Company , M., Bernardi , M., P \'e rez-Gonz \'a lez , P. G., et al. 2016, , 462, 4495

    2016

  31. [39]

    J., et al

    Ilbert , O., Arnouts , S., McCracken , H. J., et al. 2006, , 457, 841

    2006

  32. [40]

    2010, , 709, 644

    Ilbert , O., Salvato , M., Le Floc'h , E., et al. 2010, , 709, 644

    2010

  33. [41]

    & Leja , J

    Johnson , B. & Leja , J. 2017, Bd-J/Prospector: Initial Release , Zenodo

    2017

  34. [42]

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

    Johnson , B. D., Leja , J., Conroy , C., & Speagle , J. S. 2021, , 254, 22

    2021

  35. [43]

    M., White , S

    Kauffmann , G., Heckman , T. M., White , S. D. M., et al. 2003, , 341, 54

    2003

  36. [44]

    M., Faber , S

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

    2011

  37. [45]

    J., Ilbert , O., et al

    Laigle , C., McCracken , H. J., Ilbert , O., et al. 2016, , 224, 24

    2016

  38. [46]

    S., et al

    Lang , P., Wuyts , S., Somerville , R. S., et al. 2014, , 788, 11

    2014

  39. [47]

    P., Robotham , A

    Lange , R., Driver , S. P., Robotham , A. S. G., et al. 2015, , 447, 2603

    2015

  40. [48]

    2023, arXiv e-prints, arXiv:2307.07599

    Le Bail , A., Daddi , E., Elbaz , D., et al. 2023, arXiv e-prints, arXiv:2307.07599

    2023 arXiv

  41. [49]

    C., et al

    Lee , H., Acharyya , A., Wright , A. C., et al. 2023, Research Notes of the American Astronomical Society, 7, 202

    2023

  42. [50]

    C., Johnson , B

    Leja , J., Carnall , A. C., Johnson , B. D., Conroy , C., & Speagle , J. S. 2019 a , , 876, 3

    2019

  43. [51]

    D., Conroy , C., et al

    Leja , J., Johnson , B. D., Conroy , C., et al. 2019 b , , 877, 140

    2019

  44. [52]

    S., Johnson , B

    Leja , J., Speagle , J. S., Johnson , B. D., et al. 2020, , 893, 111

    2020

  45. [53]

    S., Ting , Y.-S., et al

    Leja , J., Speagle , J. S., Ting , Y.-S., et al. 2022, , 936, 165

    2022

  46. [54]

    2019, , 489, 1265

    Mancini , C., Daddi , E., Juneau , S., et al. 2019, , 489, 1265

    2019

  47. [55]

    2010, , 407, 830

    Maraston , C., Pforr , J., Renzini , A., et al. 2010, , 407, 830

    2010

  48. [56]

    2009, , 707, 250

    Martig , M., Bournaud , F., Teyssier , R., & Dekel , A. 2009, , 707, 250

    2009

  49. [57]

    2024, arXiv e-prints, arXiv:2406.17756

    Martorano , M., van der Wel , A., Baes , M., et al. 2024, arXiv e-prints, arXiv:2406.17756

    2024 arXiv

  50. [58]

    F., et al

    Martorano , M., van der Wel , A., Bell , E. F., et al. 2023, , 957, 46

    2023

  51. [59]

    B., Whitaker , K

    Miller , T. B., Whitaker , K. E., Nelson , E. J., et al. 2022, , 941, L37

    2022

  52. [60]

    2024, , 963, 9

    Morishita , T., Stiavelli , M., Chary , R.-R., et al. 2024, , 963, 9

    2024

  53. [61]

    2013, , 777, 18

    Muzzin , A., Marchesini , D., Stefanon , M., et al. 2013, , 777, 18

    2013

  54. [62]

    H., & Ostriker , J

    Naab , T., Johansson , P. H., & Ostriker , J. P. 2009, , 699, L178

    2009

  55. [63]

    Nair , P., van den Bergh , S., & Abraham , R. G. 2011, , 734, L31

    2011

  56. [64]

    2024, , 961, 73

    Narayanan , D., Lower , S., Torrey , P., et al. 2024, , 961, 73

    2024

  57. [65]

    V., Rafelski , M., Teplitz , H

    Nedkova , K. V., Rafelski , M., Teplitz , H. I., et al. 2024, , 970, 188

    2024

  58. [66]

    J., Suess , K

    Nelson , E. J., Suess , K. A., Bezanson , R., et al. 2023, , 948, L18

    2023

  59. [67]

    J., van Dokkum , P

    Nelson , E. J., van Dokkum , P. G., Momcheva , I. G., et al. 2016, , 817, L9

    2016

  60. [68]

    & Maechler , M

    Ng , P. & Maechler , M. 2007, Statistical Modelling, 7, 315

    2007

  61. [69]

    & Maechler , M

    Ng , P. & Maechler , M. 2022, COBS -- Constrained B-splines (Sparse matrix based), r package version 1.3-5

    2022

  62. [70]

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

    1983

  63. [71]

    2024, , 963, 54

    Pandya , V., Zhang , H., Huertas-Company , M., et al. 2024, , 963, 54

    2024

  64. [72]

    Papovich , C., Dickinson , M., & Ferguson , H. C. 2001, , 559, 620

    2001

  65. [73]

    J., et al

    Park , M., Tacchella , S., Nelson , E. J., et al. 2022, , 515, 213

    2022

  66. [74]

    & Miller , T

    Pasha , I. & Miller , T. B. 2023, arXiv e-prints, arXiv:2306.05454

    2023 arXiv

  67. [75]

    G., van Dokkum , P

    Patel , S. G., van Dokkum , P. G., Franx , M., et al. 2013, , 766, 15

    2013

  68. [76]

    Y., Ho , L

    Peng , C. Y., Ho , L. C., Impey , C. D., & Rix , H.-W. 2002, , 124, 266

    2002

  69. [77]

    Y., Ho , L

    Peng , C. Y., Ho , L. C., Impey , C. D., & Rix , H.-W. 2010, , 139, 2097

    2010

  70. [78]

    2019, , 490, 3196

    Pillepich , A., Nelson , D., Springel , V., et al. 2019, , 490, 3196

    2019

  71. [79]

    H., Suess , K

    Price , S. H., Suess , K. A., Williams , C. C., et al. 2023, arXiv e-prints, arXiv:2310.02500

    2023 arXiv

  72. [80]

    A., Pettini , M., Steidel , C

    Reddy , N. A., Pettini , M., Steidel , C. C., et al. 2012, , 754, 25

    2012

  73. [81]

    D., Tacchella , S., et al

    Robertson , B., Johnson , B. D., Tacchella , S., et al. 2023, arXiv e-prints, arXiv:2312.10033

    2023

  74. [82]

    Robotham, A. S. G., Taranu, D. S., Tobar, R., Moffett, A., & Driver, S. P. 2016, Monthly Notices of the Royal Astronomical Society, 466, 1513

    2016

  75. [83]

    2015, , 219, 4

    Salo , H., Laurikainen , E., Laine , J., et al. 2015, , 219, 4

    2015

  76. [84]

    Sersic , J. L. 1968, Atlas de galaxias australes

    1968

  77. [85]

    2015, , 219, 15

    Shibuya , T., Ouchi , M., & Harikane , Y. 2015, , 219, 15

    2015

  78. [86]

    2024, arXiv e-prints, arXiv:2402.07989

    Shivaei , I., Alberts , S., Florian , M., et al. 2024, arXiv e-prints, arXiv:2402.07989

    2024 arXiv

  79. [87]

    E., Whitaker , K

    Skelton , R. E., Whitaker , K. E., Momcheva , I. G., et al. 2014, , 214, 24

    2014

  80. [88]

    & Sawicki , M

    Sorba , R. & Sawicki , M. 2018, , 476, 1532

    2018

  81. [89]

    A., Bezanson , R., Nelson , E

    Suess , K. A., Bezanson , R., Nelson , E. J., et al. 2022 a , , 937, L33

    2022

  82. [90]

    A., Leja , J., Johnson , B

    Suess , K. A., Leja , J., Johnson , B. D., et al. 2022 b , , 935, 146

    2022

  83. [91]

    M., et al

    Tacchella , S., Dekel , A., Carollo , C. M., et al. 2016, , 458, 242

    2016

  84. [92]

    2019, , 487, 5416

    Tacchella , S., Diemer , B., Hernquist , L., et al. 2019, , 487, 5416

    2019

  85. [93]

    2023, , 957, L15

    Tadaki , K.-i., Kodama , T., Koyama , Y., et al. 2023, , 957, L15

    2023

  86. [94]

    2014, , 789, 164

    Tal , T., Dekel , A., Oesch , P., et al. 2014, , 789, 164

    2014

  87. [95]

    F., H \"a ussler , B., et al

    van der Wel , A., Bell , E. F., H \"a ussler , B., et al. 2012, , 203, 24

    2012

  88. [96]

    F., van den Bosch , F

    van der Wel , A., Bell , E. F., van den Bosch , F. C., Gallazzi , A., & Rix , H.-W. 2009, , 698, 1232

    2009

  89. [97]

    F., et al

    van der Wel , A., Chang , Y.-Y., Bell , E. F., et al. 2014, , 792, L6

    2014

  90. [98]

    2024, , 960, 53

    van der Wel , A., Martorano , M., H \"a u ler , B., et al. 2024, , 960, 53

    2024

  91. [99]

    G., Leja , J., Nelson , E

    van Dokkum , P. G., Leja , J., Nelson , E. J., et al. 2013, , 771, L35

    2013

  92. [100]

    G., Whitaker , K

    van Dokkum , P. G., Whitaker , K. E., Brammer , G., et al. 2010, , 709, 1018

    2010

  93. [101]

    Wang , D., Lagos , C. D. P., Croom , S. M., et al. 2023, , 523, 6020

    2023

  94. [102]

    2024, , 962, 176

    Ward , E., de la Vega , A., Mobasher , B., et al. 2024, , 962, 176

    2024

  95. [103]

    R., Kauffmann , O

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

    2022

  96. [104]

    R., Tinker , J

    Wetzel , A. R., Tinker , J. L., Conroy , C., & van den Bosch , F. C. 2013, , 432, 336

    2013

  97. [105]

    E., Bezanson , R., van Dokkum , P

    Whitaker , K. E., Bezanson , R., van Dokkum , P. G., et al. 2017, , 838, 19

    2017

  98. [106]

    E., Franx , M., Bezanson , R., et al

    Whitaker , K. E., Franx , M., Bezanson , R., et al. 2015, , 811, L12

    2015

  99. [107]

    E., Franx , M., Leja , J., et al

    Whitaker , K. E., Franx , M., Leja , J., et al. 2014, , 795, 104

    2014

  100. [108]

    2018, , 868, 37

    Wu , P.-F., van der Wel , A., Bezanson , R., et al. 2018, , 868, 37

    2018

  101. [109]

    J., Hayward , C

    Wuyts , S., Cox , T. J., Hayward , C. C., et al. 2010, , 722, 1666

    2010

  102. [110]

    M., van der Wel , A., et al

    Wuyts , S., F \"o rster Schreiber , N. M., van der Wel , A., et al. 2011, , 742, 96

    2011

  103. [111]

    R., Faber , S

    Zhang , H., Primack , J. R., Faber , S. M., et al. 2019, , 484, 5170

    2019

  104. [112]

    E., et al

    Zhang , J., Wuyts , S., Cutler , S. E., et al. 2023, , 524, 4128

    2023

  105. [113]

    N.,& Stewart, J

    Cox, A. N.,& Stewart, J. N. 1969,

    1969

  106. [114]

    Tscharnuter W. M. 1987,

    1987

  107. [115]

    1992, in ASP Conf

    Terlevich, R. 1992, in ASP Conf. Ser. 31,

    1992

  108. [116]

    F., Tytler, D

    Zheng, W., Davidsen, A. F., Tytler, D. & Kriss, G. A

  109. [117]

    1966, in Stellar Evolution, ed.\ R

    Baker, N. 1966, in Stellar Evolution, ed.\ R. F. Stein,& A. G. W. Cameron (Plenum, New York) 333

    1966

  110. [118]

    1988, A&A, 200, 58

    Balluch, M. 1988, A&A, 200, 58

    1988

  111. [119]

    Cox, J. P. 1980, Theory of Stellar Pulsation (Princeton University Press, Princeton) 165

    1980

  112. [120]

    N.,& Stewart, J

    Cox, A. N.,& Stewart, J. N. 1969, Academia Nauk, Scientific Information 15, 1

    1969

  113. [121]

    1980, Prog

    Mizuno H. 1980, Prog. Theor. Phys., 64, 544

    1980

  114. [122]

    Tscharnuter W. M. 1987, A&A, 188, 55

    1987

  115. [123]

    1992, in ASP Conf

    Terlevich, R. 1992, in ASP Conf. Ser. 31, Relationships between Active Galactic Nuclei and Starburst Galaxies, ed. A. V. Filippenko, 13

    1992

  116. [124]

    Yorke, H. W. 1980a, A&A, 86, 286

  117. [125]

    F., Tytler, D

    Zheng, W., Davidsen, A. F., Tytler, D. & Kriss, G. A. 1997, preprint

    1997

Pith tools

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