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Potential-Driven Metal Cycling: JADES Census of Gas-Phase Metallicity for galaxies at 1 < z < 7

T0 review · 3 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read At fixed mass and redshift, more compact galaxies at 1<z<7 are more metal-rich, a trend seen with four independent metallicity calibrations.

desk verdict Solid first census of the size-metallicity relation at 1<z<7, but the residual correlation depends on an unpublished mass-size relation and needs a redshift-control test before I'd fully trust it. read the letter →

arxiv 2504.18820 v2 pith:AXK737ZG submitted 2025-04-26 astro-ph.GA

Cheng Jia , Enci Wang , Cheqiu Lyu , Chengyu Ma , Jie Song , Yangyao Chen , Kai Wang , Haoran Yu
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Zeyu Chen Jinyang Wang Yifan Wang Xu Kong
This is my paper · ORCID
classification astro-ph.GA
keywords gas-phasemetallicitymass-metallicityrelationmass-sizegalaxysizegravitationalpotentialJADEShigh-redshiftgalaxiesstrong-linediagnostics
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

Gas-phase metallicity records how many generations of stars have enriched a galaxy's gas, and at low redshift it is known to rise with stellar mass. This paper asks whether the underlying driver, the depth of a galaxy's gravitational potential as traced by its physical size, already operated at 13$ subsample. Read as the paper's authors read it, this is the first evidence that gravitational potential regulates gas-phase metallicity towards cosmic dawn, meaning the material-exchange processes that set local galaxy chemical abundances were already active in the early universe.

What carries the argument

The carrying object is the residual pair $(\Delta\log(\mathrm{O/H}), \Delta\log R_e)$. The metallicity residual comes from the fitted mass-metallicity relation for each of four calibrations, and the size residual is defined as $\Delta\log R_e = \log R_e - \log R_{\rm model}$ with $\log R_{\rm model} = \alpha\log(M_*/M_\odot)+\beta\log(1+z)+k$, using coefficients $\alpha=0.162$, $\beta=-0.614$, $k=-0.964$ from a companion analysis. Sizes are measured with Sérsic fits in JWST and HST bands and homogenized to rest-frame 1 μm, where the light traces older stellar populations and hence better approximates the underlying mass distribution and gravitational potential. The argument works by cross-checking the same anticorrelation across four independent metallicity diagnostics, repeating it for the $z>3$ subsample, and comparing the slope against low-redshift observations and cosmological simulations, so that a single calibration's systematics cannot produce the signal.

What would settle it

Re-fit the mass-size relation to the same galaxies with full uncertainty propagation (or adopt an independent size-mass calibration from the same redshift range), recompute $\Delta\log R_e$, and check whether the Spearman p-values remain below 0.01 for all four metallicity tracers; if the anticorrelation disappears, the central claim fails. A complementary check is to measure stellar velocity dispersions and see whether the size-metallicity correlation vanishes once the actual potential depth is controlled for.

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Extended reading notes

Core claim

The central claim is that the residual compactness of a high-redshift galaxy, defined by its deviation from the mass-size relation at the corresponding redshift, is significantly negatively correlated with its deviation from the mass-metallicity relation. The paper demonstrates this with 75-97 galaxies at 1<z<7 from the JADES survey, using four strong-line metallicity estimators (N2S2Hα, R23, N2, and O3N2): compact galaxies are enriched in oxygen at fixed stellar mass and redshift. For the full sample the Spearman p-values are below 0.01 for every tracer, and for the smaller $z>3$ subsample (21-34 galaxies) they are below 0.05. The authors also quantify the effect by fitting a modified mass-metallicity relation of the form $12+\log(\mathrm{O/H}) = k(\log(M_*/M_\odot)+\beta\,\Delta\log R_e)+b$, finding $\beta$ between $-0.4$ and $-1.1$, broadly consistent with low-redshift measurements and with cosmological simulations. They conclude that gravitational potential, traced by size, plays a key role in regulating gas-phase metallicity and metal retention in the early universe.

Load-bearing premise

The entire analysis leans on a mass-size relation from an unpublished companion paper, whose three coefficients are adopted as fixed numbers without uncertainties, so every compactness residual, and hence the claimed correlation, would shift if that baseline is wrong.

Editorial extensions

If this is right

  • At fixed stellar mass and redshift, size acts as an independent lever on gas-phase metallicity, so the mass-metallicity relation is a projection of a relation that also depends on compactness.
  • Deeper potential wells retain more metals: the fitted $\beta$ in $x=\log(M_*/M_\odot)+\beta\,\Delta\log R_e$ is between $-0.4$ and $-1.1$, bracketing low-redshift and simulation values and supporting the outflows-suppressed-by-gravity picture.
  • The anticorrelation persists for galaxies with $z>3$ alone, so the result is not driven by the more numerous lower-redshift galaxies in the sample.
  • Because all four strong-line diagnostics reproduce the trend despite their systematic differences, the correlation is unlikely to be an artifact of one metallicity calibration.
  • The consistency with low-redshift data and with cosmological simulations implies that potential-driven metal cycling was already in place a few billion years after the Big Bang rather than emerging only at late times.

Reading between the lines

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

  • A natural extension is to split the sample by stellar mass: the gas-regulator picture predicts the size-metallicity anticorrelation should be strongest at low masses, where outflows remove a larger fraction of the metal budget.
  • The gravitational-potential interpretation predicts that directly measured stellar velocity dispersions should correlate with metallicity at fixed mass and redshift; if dispersion explains the trend and size does not add information, the radius-based interpretation would be weakened.
  • The result's dependence on the companion mass-size relation could be tested by re-fitting $\Delta\log R_e$ with a relation derived from this sample with full uncertainty propagation, or by using an independent size-mass calibration in the same redshift range.
  • At $z>5$ the sample contains only a handful of galaxies; the same analysis on future data releases would show whether the anticorrelation steepens or flattens as the universe approaches reionization.
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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 / 5 minor

Summary. The paper analyzes JADES DR3 galaxies at 1 < z < 7 to test whether galaxy size, as a proxy for gravitational potential, correlates with gas-phase metallicity at fixed stellar mass. Using four strong-line metallicity calibrations (N2S2Hα, R23, N2, O3N2), the authors define Δlog(O/H) as the residual from a fitted mass–metallicity relation and Δlog Re as the residual from a mass–size relation that includes a redshift term. They report a significant negative Spearman correlation between these two residuals for all four calibrators (p < 0.01), and for the z > 3 subsample (p < 0.05). They compare the slope of this relation with MaNGA and TNG50 results and interpret the finding as evidence that gravitational potential regulates metallicity in the early universe.

Significance. If the central correlation is robust, this would be among the first evidence at 1 < z < 7 that galaxy size, independent of stellar mass and redshift, plays a role in setting gas-phase metallicity. The paper's strengths include the use of four independent metallicity calibrators, the public JADES DR3 sample, a dedicated z > 3 subsample, and quantitative comparison with MaNGA and TNG50. The consistency across calibrators is a genuine point in favor of the result. However, the central claim depends on an externally calibrated mass–size relation that is not yet published and is used without uncertainties, and the residual-based test has not been shown to be robust against shared redshift trends in the two residuals. These issues are load-bearing for the main conclusion and require additional analysis.

major comments (3)
  1. [Section 3.2, Eq. (10)] The definition of Δlog Re uses coefficients α = 0.162, β = −0.614, k = −0.964 from an unpublished companion paper (Song et al. in prep) with no reported uncertainties. Every value of Δlog Re in the analysis inherits these coefficients, so an error in β, the log(1+z) coefficient, would make Δlog Re systematically correlated with redshift. Because Δlog(O/H) is the residual from a MZR fit that includes no redshift term, both residuals could share a common monotonic redshift trend, and the Spearman test could reach p < 0.01 even in the absence of an intrinsic size–metallicity relation at fixed mass and redshift. Please report the uncertainties on these coefficients, re-fit the mass–size relation within the JADES sample, or repeat the analysis with published mass–size relations at these redshifts to show that the correlation is not an artifact of the adopted calibration.
  2. [Section 3.2, paragraph following Fig. 3] The text acknowledges that fitting the MZR over a wide redshift range 'may introduce potential biases' and that unaccounted-for redshift evolution in metallicity may contribute additional scatter, but then asserts without proof that correcting for size evolution makes artificial correlations unlikely. This is not a substitute for a quantitative test. A partial Spearman correlation controlling for redshift, or an analysis in which both the MZR and the mass–size relation include explicit redshift terms, is needed to establish that the reported Δlog(O/H)–Δlog Re correlation is not driven by residual redshift trends shared by both variables.
  3. [Appendix B] The z > 3 test reuses the full-sample mass–size relation and MZR rather than re-fitting them to the high-redshift subsample. This narrows the redshift range and reduces the shared-trend concern, but it does not remove the dependence on the external mass–size coefficients in Eq. (10). The text should state this explicitly and discuss what is and is not tested by the z > 3 subsample.
minor comments (5)
  1. [Figure 3] The Spearman r values are displayed as positive (e.g., r = 0.4257 for N2S2Hα, r = 0.3767 for N2) while the text describes a negative correlation; please clarify whether these are absolute values or specify the sign convention in the caption.
  2. [Figure 1] The caption reads 'mass-extinction diagram'; this should be 'mass-excitation (MEx) diagram'.
  3. [Section 3.2] The heading contains the typo 'metalllicity', and the text contains 'correpsonding'; these should be corrected.
  4. [Appendix B] Please state explicitly that the z > 3 analysis uses the full-sample MZR and mass–size relation rather than re-fitting them; the current wording, 'consistent with those described in Section 3.2', leaves this ambiguous.
  5. [Abstract] The final sentence 'at very early universe' is ungrammatical; suggest 'in the very early universe' or 'at very early times'.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the central Delta-log(O/H) vs Delta-log Re correlation is an empirical residual analysis with an external size calibration.

full rationale

The paper's central claim is an observed Spearman correlation between residuals from two independently fitted scaling relations: the offset from the mass-metallicity relation, Delta log(O/H), and the offset from the mass-size relation, Delta log Re. The MZR is fitted to the same galaxies used for the residual analysis, which is standard practice and does not by construction force a correlation with an unrelated size residual. The MSR coefficients in Eq. (10) are taken from an unpublished companion paper (Song et al., in prep) rather than derived from the metallicity target, so the size residual is not defined in terms of metallicity and the claimed correlation is not baked in. The beta fit in Section 3.3 is explicitly a fit to characterize the relation, not a prediction from the model, and no fitted parameter is renamed as a prediction. Self-citations to Wang & Lilly (2021) and Ma et al. (2024) are contextual support for the low-redshift gas-regulator framework and for comparison samples, but they are not load-bearing in the derivation of the new high-redshift correlation, and no uniqueness theorem or forbidden alternative is imported from the authors' prior work. The paper's own caveat that fitting the MZR over a wide redshift range may introduce bias is a potential confounding effect, not a circular reduction, and the skeptical concern about the unpublished mass-size relation is a correctness risk rather than a self-definitional equivalence. Thus no circular step can be exhibited with a specific equation-level reduction, and the analysis is self-contained as an empirical study.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

No new physical entities are introduced. The analysis rests on public JADES data, standard SED fitting, and literature calibrations; the main unquantified input is the mass-size relation from an unpublished companion paper.

free parameters (3)
  • Mass-size relation coefficients alpha, beta, k = alpha=0.162, beta=-0.614, k=-0.964
    Used in Eq. 10 to define Delta log Re; taken from the unpublished Song et al. in prep; no uncertainties are given.
  • MZR slope and intercept for each of the four metallicity tracers = Not reported numerically in the text
    Fitted to the JADES sample via MCMC (Section 3.1); Delta log(O/H) residuals are computed from these fits, so the correlation depends on them.
  • Best-fit beta in the modified MZR (Eq. 11-12) = Between -0.4 and -1.1; around -1.1 for N2S2Halpha
    Fitted by minimizing residual scatter in Section 3.3; used for quantitative comparison with MaNGA and TNG50, not for the main correlation.
assumptions (5)
  • domain assumption Rest-frame 1 micron effective radius traces the underlying stellar mass distribution and gravitational potential
    Section 2.3 adopts this to justify using Re as a potential proxy; if size is affected by star-forming regions, the correlation could be distorted.
  • domain assumption For z>3.5, the F444W size is an acceptable approximation to the rest-frame 1 micron size
    Section 2.3 states this directly; at z~7, F444W corresponds to rest-frame ~0.55 micron, tracing different stellar populations.
  • domain assumption Low-redshift strong-line metallicity calibrations remain valid at 1<z<7
    Section 2.4 applies the N2S2Halpha, N2, O3N2, and R23 calibrations to high-redshift spectra without a high-z recalibration.
  • domain assumption The mass-metallicity relation does not evolve significantly over 1<z<7
    Section 3.1 fits a single MZR across the full sample and finds no evolution; residuals are measured from this fit, and the authors note in Section 3.2 that any unaccounted evolution could affect the slope.
  • domain assumption Star formation rate is not a significant driver of metallicity at high redshift
    Section 3.3 omits SFR from the modified MZR, citing Cuestas et al. 2025 at z~2.3; the extrapolation to z=7 is assumed.

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Cite this review

Pith. "Pith review of Potential-Driven Metal Cycling: JADES Census of Gas-Phase Metallicity for galaxies at 1 < z < 7." pith.science (2026). https://pith.science/paper/AXK737ZG

@misc{pith2026250418820,
  author       = {Pith},
  title        = {Pith review of: Potential-Driven Metal Cycling: JADES Census of Gas-Phase Metallicity for galaxies at 1 < z < 7},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AXK737ZG}},
  note         = {Machine review of arXiv:2504.18820}
}
abstract

The gravitational potential is established as a critical determinant of gas-phase metallicity (12+log(O/H)) in low-redshift galaxies, whereas its influence remains unconfirmed at high redshifts. We investigate the correlation between gas-phase metallicity and effective radius ($R_{\rm e}$) for a sample of galaxies with redshifts ranging from 1 to 7, drawn from JADES (JWST Advanced Deep Extragalactic Survey) Data Release 3. We calculate the metallicities using four strong-line methods: ${\rm N2S2H\alpha}$, ${\rm R23}$, ${\rm N2}$, and ${\rm O3N2}$, respectively. After taking out the evolution of size, we find that the offsets of mass-size relation ($\Delta \log R_{\rm e}$) are significantly negatively correlated with the offset of mass-metallicity relation ($\Delta \log({\rm O/H})$) for the four metallicity tracers. Regardless of the metallicity tracer used, we obtain Spearman rank $p-$values much less than 0.01, rejecting the null hypothesis that the observed correlation is statistically nonsignificant and attributable to random chance. This is also true for galaxies with $z>3$, with $p-$values less than 0.05 for the four metallicity tracers. We for the first time find evidence of size playing a key role in determining gas-phase metallicity towards cosmic dawn, suggesting that the gravitational potential influences their material-exchange processes with the surrounding environment at very early universe.

Figures

Figures reproduced from arXiv: 2504.18820 by the authors.

Figure 1
Figure 1. , the solid and dashed red lines denote thresh￾olds for high and low AGN probability, respectively. We adopt the solid line to exclude likely AGN hosts (pink points), while retaining galaxies with lower AGN likelihood (sky-blue and green points). In addition, we remove sources lacking a measurement of O3Hβ (= log([OIII]5007/[Hβ])) to ensure the purity of the sample. Since different metallicity calibration methods re… view at source ↗
Figure 2
Figure 2. The MZR measured using the four metallicity indicators and a comparison with others. Solid dots in the left panel represent measurements from individual sources, while the black dashed lines indicate the best-fit results. The gray shade around best-fit model represents the error. Data points are color-coded with the redshift of galaxies. In the right panel, the solid points in various colors and the corresponding so… view at source ↗
Figure 3
Figure 3. Correlation between ∆log(O/H) and ∆ log Re. Solid circular points represent individual galaxies, color-coded by redshift. Green diamonds indicate the median values within three bins: (−3σdZ, −σdZ), (−σdZ, σdZ), and (σdZ, 3σdZ). The Spearman rank p-values are displayed in the upper left corner of each panel. ure 4. For TNG50, we compute ∆log(O/H) and ∆ log Re based on the redshift-dependent linear MSR and MZR. Notabl… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Similar to [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: The relative scatter in residual log (O/H), de￾noted as σ/σmin, as a function of β. Solid lines in different colors show results obtained using various metallicity indica￾tors. The pink shaded region represents the best-fit β range for redshifts z = 0–5 from the TNG50 …
Figure 6
Figure 6. Figure 6: The redshift–stellar mass diagram of our sample. Sky-blue and pink points represent star-forming galaxies and AGNs, respectively, from the final samples used for different metallicity measurement methods. Gray dots indicate all galaxies in the JADES field with availabl…
Figure 7
Figure 7. Figure 7: The BPT diagram of our sample. This includes all the galaxies used in our four methods. 0.75 0.50 0.25 0.00 0.25 0.50 0.75 log(O/H) 0.75 0.50 0.25 0.00 0.25 0.50 0.75 lo g R e N2S2H p value = 0.0437 r = 0.4442 0.2 0.1 0.0 0.1 0.2 log(O/H) 0.75 0.50 0.25 0.00 0.25 0.50 …
Figure 8
Figure 8. Figure 8: Similar to [PITH_FULL_IMAGE:figures/full_fig_p011_8.png]

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Works this paper leans on

59 extracted references · 1 canonical work pages

  1. [1]

    J., & Dopita, M

    Bian, F., Kewley, L. J., & Dopita, M. A. 2018, ApJ, 859, 175, doi: 10.3847/1538-4357/aabd74

    doi:10.3847/1538-4357/aabd74 2018

  2. [2]

    2020, in American Astronomical Society Meeting Abstracts, Vol

    Boquien, M. 2020, in American Astronomical Society Meeting Abstracts, Vol. 235, American Astronomical Society Meeting Abstracts #235, 228.01 Bouch´ e, N., Dekel, A., Genzel, R., et al. 2010, ApJ, 718, 1001, doi: 10.1088/0004-637X/718/2/1001

    doi:10.1088/0004-637x/718/2/1001 2020

  3. [3]

    2023, grizli, Zenodo, doi: 10.5281/ZENODO.1146904

    Brammer, G. 2023, grizli, Zenodo, doi: 10.5281/ZENODO.1146904

    doi:10.5281/zenodo.1146904 2023

  4. [4]

    2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    arXiv 2003

  5. [5]

    A., Law, D

    Bundy, K., Bershady, M. A., Law, D. R., et al. 2015, ApJ, 798, 7, doi: 10.1088/0004-637X/798/1/7

    doi:10.1088/0004-637x/798/1/7 2015

  6. [6]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682, doi: 10.1086/308692 10 0 1 2 3 4 5 6 7 z 5 6 7 8 9 10 11log (M* /M ) all N2S2H (AGN) N2S2H (SF) 0 1 2 3 4 5 6 7 z 5 6 7 8 9 10 11log (M* /M ) all N2(AGN) N2(SF) 0 1 2 3 4 5 6 7 z 5 6 7 8 9 10 11log (M* /M ) all R23(AGN) R23(SF) 0 1 2 3 4 5 6 7 z 5 6 7 8 9 10 11log (M* /M ) all O3N2(AGN) O...

    doi:10.1086/308692 2000

  7. [7]

    C., McLure, R

    Carnall, A. C., McLure, R. J., Dunlop, J. S., & Dav´ e, R. 2018, Monthly Notices of the Royal Astronomical Society, 480, 4379–4401, doi: 10.1093/mnras/sty2169

    doi:10.1093/mnras/sty2169 2018

  8. [8]

    2024, Unveiling the Cosmic Chemistry II: ”direct”T e-based metallicity of galaxies at 3<z <10 with JWST/NIRSpec

    Chakraborty, P., Sarkar, A., Smith, R., et al. 2024, Unveiling the Cosmic Chemistry II: ”direct”T e-based metallicity of galaxies at 3<z <10 with JWST/NIRSpec. https://arxiv.org/abs/2412.15435

    arXiv 2024

Show all 59 references
  1. [9]

    2024, The Astrophysical Journal Letters, 976, L15, doi: 10.3847/2041-8213/ad8dc9

    Chemerynska, I., Atek, H., Dayal, P., et al. 2024, The Astrophysical Journal Letters, 976, L15, doi: 10.3847/2041-8213/ad8dc9

    2024 doi

  2. [10]

    2025, ApJ, 981, 81, doi: 10.3847/1538-4357/ada942

    Chen, Z., Wang, E., Zou, H., et al. 2025, ApJ, 981, 81, doi: 10.3847/1538-4357/ada942

    2025 doi

  3. [11]

    2018, The Astrophysical Journal, 867, 142, doi: 10.3847/1538-4357/aae374

    Shen, S. 2018, The Astrophysical Journal, 867, 142, doi: 10.3847/1538-4357/aae374

    2018 doi

  4. [12]

    Cuestas, N. A. K., Strom, A. L., Miller, T. B., et al. 2025, Exploring the Relationship Between Stellar Mass, Metallicity, and Star Formation Rate atz∼2.3 in KBSS-MOSFIRE. https://arxiv.org/abs/2503.10800

    2025 arXiv

  5. [13]

    2020, MNRAS, 491, 944, doi: 10.1093/mnras/stz2910

    Curti, M., Mannucci, F., Cresci, G., & Maiolino, R. 2020, MNRAS, 491, 944, doi: 10.1093/mnras/stz2910

    2020 doi

  6. [14]

    2024, A&A, 684, A75, doi: 10.1051/0004-6361/202346698 D’Eugenio, F., Colless, M., Groves, B., Bian, F., & Barone, T

    Curti, M., Maiolino, R., Curtis-Lake, E., et al. 2024, A&A, 684, A75, doi: 10.1051/0004-6361/202346698 D’Eugenio, F., Colless, M., Groves, B., Bian, F., & Barone, T. M. 2018, MNRAS, 479, 1807, doi: 10.1093/mnras/sty1424 D’Eugenio, F., Cameron, A. J., Scholtz, J., et al. 2024, ...

    2024 arXiv

  7. [15]

    A., Kewley, L

    Dopita, M. A., Kewley, L. J., Sutherland, R. S., & Nicholls, D. C. 2016, Astrophysics and Space Science, 361, doi: 10.1007/s10509-016-2657-8

    2016 doi

  8. [16]

    2023, Optimal metallicity diagnostics for MUSE observations of low-z galaxies

    Easeman, B., Schady, P., Wuyts, S., & Yates, R. 2023, Optimal metallicity diagnostics for MUSE observations of low-z galaxies. https://arxiv.org/abs/2311.03514

    2023 arXiv

  9. [17]

    J., Johnson, B

    Eisenstein, D. J., Johnson, B. D., Robertson, B., et al. 2023a, The JADES Origins Field: A New JWST Deep Field in the JADES Second NIRCam Data Release. https://arxiv.org/abs/2310.12340

  10. [18]

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

    Eisenstein, D. J., Willott, C., Alberts, S., et al. 2023b, Overview of the JWST Advanced Deep Extragalactic Survey (JADES). https://arxiv.org/abs/2306.02465 11 2.0 1.5 1.0 0.5 0.0 0.5 log ([NII]/[H ]) 1.0 0.5 0.0 0.5 1.0 1.5 log ([OIII]/[H ]) Kewley et al. 2001 2 3 4 5 6 redsh...

    2001 arXiv

  11. [19]

    L., Patton, D

    Ellison, S. L., Patton, D. R., Simard, L., & McConnachie, A. W. 2008, ApJL, 672, L107, doi: 10.1086/527296

    2008 doi

  12. [20]

    2019, ApJ, 886, 31, doi: 10.3847/1538-4357/ab4902

    Huang, C., Zou, H., Kong, X., et al. 2019, ApJ, 886, 31, doi: 10.3847/1538-4357/ab4902

    2019 doi

  13. [22]

    2024, Size Growth on Short Timescales of Star-Forming Galaxies: Insights from Size Variation with Rest-Frame Wavelength with JADES

    Jia, C., Wang, E., Wang, H., et al. 2024, Size Growth on Short Timescales of Star-Forming Galaxies: Insights from Size Variation with Rest-Frame Wavelength with JADES. https://arxiv.org/abs/2411.07458

    2024 arXiv

  14. [23]

    2014, ApJ, 788, 88, doi: 10.1088/0004-637X/788/1/88

    Juneau, S., Bournaud, F., Charlot, S., et al. 2014, ApJ, 788, 88, doi: 10.1088/0004-637X/788/1/88

    2014 doi

  15. [24]

    J., & Dopita, M

    Kewley, L. J., & Dopita, M. A. 2002, ApJS, 142, 35, doi: 10.1086/341326 12 NIRSpec ID RA Dec z logM∗/M⊙ Re [kpc] 12 + log(O + H)N2S2Hα 12 + log(O + H)N2 12 + log(O + H)R23 12 + log(O + H)O3N2 110 189.146 62.216 4.064 9.268±0.200 1.165 8.499±0.054 8.263±0.008 8.359±0.027 8.184±...

    2002 doi

  16. [25]

    J., & Ellison, S

    Kewley, L. J., & Ellison, S. L. 2008, ApJ, 681, 1183, doi: 10.1086/587500

    2008 doi

  17. [26]

    A., & Kewley, L

    Kobulnicky, H. A., & Kewley, L. J. 2004, ApJ, 617, 240, doi: 10.1086/425299

    2004 doi

  18. [27]

    2023, arXiv e-prints, arXiv:2307.06336, doi: 10.48550/arXiv.2307.06336

    Langeroodi, D., & Hjorth, J. 2023, arXiv e-prints, arXiv:2307.06336, doi: 10.48550/arXiv.2307.06336

    2023 doi arXiv

  19. [28]

    2023, The Astrophysical Journal, 957, 39, doi: 10.3847/1538-4357/acdbc1 Lara-L´ opez, M

    Langeroodi, D., Hjorth, J., Chen, W., et al. 2023, The Astrophysical Journal, 957, 39, doi: 10.3847/1538-4357/acdbc1 Lara-L´ opez, M. A., Cepa, J., Bongiovanni, A., et al. 2010, A&A, 521, L53, doi: 10.1051/0004-6361/201014803

    2023 doi

  20. [29]

    1979, A&A, 80, 155

    Torres-Peimbert, S. 1979, A&A, 80, 155

    1979

  21. [30]

    2025, arXiv e-prints, arXiv:2502.18785, doi: 10.48550/arXiv.2502.18785

    Li, H., Wang, E., Lyu, C., et al. 2025, arXiv e-prints, arXiv:2502.18785, doi: 10.48550/arXiv.2502.18785

    2025 doi arXiv

  22. [31]

    J., Carollo, C

    Lilly, S. J., Carollo, C. M., Pipino, A., Renzini, A., & Peng, Y. 2013, ApJ, 772, 119, doi: 10.1088/0004-637X/772/2/119

    2013 doi

  23. [32]

    N., Xue, Y

    Luo, B., Brandt, W. N., Xue, Y. Q., et al. 2016, The Astrophysical Journal Supplement Series, 228, 2, doi: 10.3847/1538-4365/228/1/2

    2016 doi

  24. [33]

    2025, ApJL, 981, L6, doi: 10.3847/2041-8213/adb4ed

    Lyu, C., Wang, E., Zhang, H., et al. 2025, ApJL, 981, L6, doi: 10.3847/2041-8213/adb4ed

    2025 doi

  25. [34]

    2024, The Astrophysical Journal Letters, 971, L14, doi: 10.3847/2041-8213/ad675f

    Ma, C., Wang, K., Wang, E., et al. 2024, The Astrophysical Journal Letters, 971, L14, doi: 10.3847/2041-8213/ad675f

    2024 doi

  26. [35]

    2008, A&A, 488, 463, doi: 10.1051/0004-6361:200809678

    Maiolino, R., Nagao, T., Grazian, A., et al. 2008, A&A, 488, 463, doi: 10.1051/0004-6361:200809678

    2008 doi

  27. [36]

    2010, MNRAS, 408, 2115, doi: 10.1111/j.1365-2966.2010.17291.x

    Gnerucci, A. 2010, MNRAS, 408, 2115, doi: 10.1111/j.1365-2966.2010.17291.x

    2010

  28. [38]

    D., Blaizot, J., Devriendt, J., et al

    Mitchell, P. D., Blaizot, J., Devriendt, J., et al. 2018, MNRAS, 474, 4279, doi: 10.1093/mnras/stx3017

    2018 doi

  29. [39]

    L., Kereˇ s, D., Faucher-Gigu` ere, C.-A., et al

    Muratov, A. L., Kereˇ s, D., Faucher-Gigu` ere, C.-A., et al. 2017, MNRAS, 468, 4170, doi: 10.1093/mnras/stx667

    2017 doi

  30. [40]

    2023, JWST Census for the Mass-Metallicity Star-Formation Relations at z=4-10 with the Self-Consistent Flux Calibration and the Proper Metallicity Calibrators

    Nakajima, K., Ouchi, M., Isobe, Y., et al. 2023, JWST Census for the Mass-Metallicity Star-Formation Relations at z=4-10 with the Self-Consistent Flux Calibration and the Proper Metallicity Calibrators. https://arxiv.org/abs/2301.12825

    2023 arXiv

  31. [41]

    2012, ApJ, 745, 12, doi: 10.1088/0004-637X/745/1/12

    Nakajima, K., Ouchi, M., Shimasaku, K., et al. 2012, ApJ, 745, 12, doi: 10.1088/0004-637X/745/1/12

    2012 doi

  32. [42]

    2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040 O’Donnell, J

    Nelson, D., Pillepich, A., Springel, V., et al. 2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040 O’Donnell, J. E. 1994, ApJ, 422, 158, doi: 10.1086/173713

    2018 doi

  33. [43]

    Y., Ho, L

    Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266, doi: 10.1086/340952 —. 2010, AJ, 139, 2097, doi: 10.1088/0004-6256/139/6/2097

    2002 doi

  34. [44]

    2014, MNRAS, 443, 3643, doi: 10.1093/mnras/stu1288

    Peng, Y.-j., & Maiolino, R. 2014, MNRAS, 443, 3643, doi: 10.1093/mnras/stu1288

    2014 doi

  35. [45]

    2018, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656 Planck Collaboration, Ade, P

    Pillepich, A., Springel, V., Nelson, D., et al. 2018, MNRAS, 473, 4077, doi: 10.1093/mnras/stx2656 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830

    2018 doi

  36. [46]

    J., Robertson, B., Tacchella, S., et al

    Rieke, M. J., Robertson, B., Tacchella, S., et al. 2023, ApJS, 269, 16, doi: 10.3847/1538-4365/acf44d S´ anchez Almeida, J., & Dalla Vecchia, C. 2018, ApJ, 859, 109, doi: 10.3847/1538-4357/aac086 S´ anchez-Menguiano, L., S´ anchez, S. F., S´ anchez Almeida, J., & Mu˜ noz-Tu˜ n...

    2023 doi

  37. [47]

    L., Shapley, A

    Sanders, R. L., Shapley, A. E., Topping, M. W., Reddy, N. A., & Brammer, G. B. 2023a, DirectT e-based Metallicities of z=2-9 Galaxies with JWST/NIRSpec: Empirical Metallicity Calibrations Applicable from Reionization to Cosmic Noon. https://arxiv.org/abs/2303.08149 —. 2023b, E...

    arXiv

  38. [48]

    L., Shapley, A

    Sanders, R. L., Shapley, A. E., Jones, T., et al. 2021, ApJ, 914, 19, doi: 10.3847/1538-4357/abf4c1

    2021 doi

  39. [49]

    2005, MNRAS, 364, 552, doi: 10.1111/j.1365-2966.2005.09574.x

    Springel, V. 2005, MNRAS, 364, 552, doi: 10.1111/j.1365-2966.2005.09574.x

    2005

  40. [50]

    D., Booth, C

    Schaye, J., Vecchia, C. D., Booth, C. M., et al. 2010, Monthly Notices of the Royal Astronomical Society, 402, 1536–1560, doi: 10.1111/j.1365-2966.2009.16029.x

    2010

  41. [51]

    C., Rudie, G

    Steidel, C. C., Rudie, G. C., Strom, A. L., et al. 2014, The Astrophysical Journal, 795, 165, doi: 10.1088/0004-637x/795/2/165

    2014 doi

  42. [52]

    A., & Heckman, T

    Thompson, T. A., & Heckman, T. M. 2024, Theory and Observation of Winds from Star-Forming Galaxies. https://arxiv.org/abs/2406.08561

    2024 arXiv

  43. [53]

    A., Heckman, T

    Tremonti, C. A., Heckman, T. M., Kauffmann, G., et al. 2004, ApJ, 613, 898, doi: 10.1086/423264

    2004 doi

  44. [54]

    Valentino, F., Brammer, G., Gould, K. M. L., et al. 2023, ApJ, 947, 20, doi: 10.3847/1538-4357/acbefa van de Voort, F., Schaye, J., Booth, C. M., Haas, M. R., & Dalla Vecchia, C. 2011, MNRAS, 414, 2458, doi: 10.1111/j.1365-2966.2011.18565.x

    2023

  45. [55]

    D., & Aalto, S

    Veilleux, S., Maiolino, R., Bolatto, A. D., & Aalto, S. 2020, A&A Rv, 28, 2, doi: 10.1007/s00159-019-0121-9

    2020 doi

  46. [56]

    Wang, E., Kong, X., & Pan, Z. 2018, ApJ, 865, 49, doi: 10.3847/1538-4357/aadb9e 14 NIRSpec ID RA Dec z logM∗/M⊙ Re [kpc] 12 + log(O + H)N2S2Hα 12 + log(O + H)N2 12 + log(O + H)R23 12 + log(O + H)O3N2 26544 189.103 62.265 2.973 10.035±0.216 2.272 8.590±0.057 8.401±0.010 8.754±0...

    2018 doi

  47. [57]

    Wang, E., & Lilly, S. J. 2021, ApJ, 910, 137, doi: 10.3847/1538-4357/abe413 —. 2022a, ApJ, 929, 95, doi: 10.3847/1538-4357/ac5e31 —. 2022b, ApJ, 927, 217, doi: 10.3847/1538-4357/ac49ed

    2021 doi

  48. [58]

    J., Pezzulli, G., & Matthee, J

    Wang, E., Lilly, S. J., Pezzulli, G., & Matthee, J. 2019, ApJ, 877, 132, doi: 10.3847/1538-4357/ab1c5b

    2019 doi

  49. [59]

    M., Vijayan, A

    Wilkins, S. M., Vijayan, A. P., Lovell, C. C., et al. 2022, Monthly Notices of the Royal Astronomical Society, 518, 3935–3948, doi: 10.1093/mnras/stac3281

    2022 doi

  50. [60]

    M., et al

    Wuyts, E., Kurk, J., F¨ orster Schreiber, N. M., et al. 2014, ApJL, 789, L40, doi: 10.1088/2041-8205/789/2/L40

    2014 doi

  51. [61]

    J., Dima, G

    Zahid, H. J., Dima, G. I., Kudritzki, R.-P., et al. 2014, ApJ, 791, 130, doi: 10.1088/0004-637X/791/2/130 16 NIRSpec ID RA Dec z logM∗/M⊙ Re [kpc] 12 + log(O + H)N2S2Hα 12 + log(O + H)N2 12 + log(O + H)R23 12 + log(O + H)O3N2 79203 189.307 62.206 2.270 9.619±0.136 2.456 8.573±...

    2014 doi

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