Pith. sign in

REVIEW 3 major objections 6 minor 5 cited by

The JWST EXCELS survey: Probing strong-line diagnostics and the chemical evolution of galaxies over cosmic time using Te-metallicities

T0 review · 3 major / 6 minor · reviewed 2026-08-07 · deepseek-v4-flash

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

Pith's one-line read A new neon-based line ratio can measure galaxy metallicities at z~11.2.

desk verdict Solid calibration paper: useful DESI Te-metallicity benchmark, a sensible bR recalibration, and a clever RNe diagnostic that extends JWST metallicity work to z~11 — but that headline extension rests on unverified coefficient transfer. read the letter →

arxiv 2502.10499 v1 pith:BZ4TJVCK submitted 2025-02-14 astro-ph.GA

D. Scholte , F. Cullen , A. C. Carnall , K. Z. Arellano-Córdova , T. M. Stanton , L. Barrufet , C. T. Donnan , J. S. Dunlop
show 8 more authors
H. -H. Leung D. J. McLeod R. J. McLure J. M. Moustakas C. L. Pollock A. E. Shapley S. Stevenson H. Zou
This is my paper · ORCID
classification astro-ph.GA
keywords Te-metallicitystrong-linediagnosticsionizationparameterJWST/NIRSpec[NeIII]3869fundamentalmetallicityrelationmass-metallicityN/Oabundance
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 tests which strong-line metallicity diagnostics remain trustworthy in the early Universe by comparing 22 JWST/NIRSpec galaxies with direct electron-temperature metallicities at z = 1.65–7.92 against 782 local galaxies with the same quality of measurement. It argues that the recently introduced $\hat{R}$ ratio, a weighted combination of [OII]/Hβ and [OIII]/Hβ, is largely insensitive to ionization parameter and therefore nearly redshift-independent, and it recalibrates that relation at the low-metallicity end. Its central new contribution is $\widehat{RNe}$, the same two-coefficient projection applied to [OII]/Hγ and [NeIII]/Hγ; because those lines sit in the blue rest-frame optical, the diagnostic remains observable with JWST/NIRSpec up to z~11.2, where [OIII]5007 has left the wavelength range. The paper calibrates $\widehat{RNe}$ on the local sample and shows out-of-sample residuals of 0.11 dex in the line ratio and 0.16 dex in oxygen abundance for the high-redshift galaxies. It also finds that nitrogen-based calibrations are biased at high redshift by enhanced N/O ratios, and reports tentative (about 1.3σ) evidence that galaxies at z>4 deviate from the local fundamental metallicity relation.

What carries the argument

The central object is a weighted-projection strong-line ratio. $\hat{R}=0.47\log([OII]/H\beta)+0.88\log([OIII]/H\beta)$ is a linear combination chosen so the opposite ionization-parameter dependencies of the two ratios nearly cancel, yielding a tight metallicity sequence. $\widehat{RNe}$ reuses the same coefficients but replaces [OIII]/Hβ with [NeIII]/Hγ and normalizes both terms to Hγ; the very strong empirical correlation between [NeIII]3869 and [OIII]5007 is what makes the borrowed projection plausible. The transfer is what carries the argument: it converts a local electron-temperature calibration into a high-redshift tool whose lines remain in the JWST/NIRSpec band when the usual oxygen strong lines are redshifted out.

What would settle it

Compare metallicities from $\widehat{RNe}$ and $\hat{R}$ for the same galaxies over the range where both line sets are detected (roughly z=1.6–8); if the residual difference grows systematically with redshift beyond the quoted 0.11–0.16 dex scatter, the transferred-weight assumption fails. Alternatively, measuring [NeIII]/[OII] against direct $T_e$ metallicities at z>9.5 would directly test for Ne/O evolution in the regime where $\widehat{RNe}$ is meant to be used.

Watch

Extended reading notes

Core claim

The paper's central claim is that the ionization-parameter insensitivity of $\hat{R}$ transfers to a neon-based analog, $\widehat{RNe} = 0.47\log([OII]/H\gamma)+0.88\log([NeIII]/H\gamma)$, without re-deriving the two weights. The justification is the very strong correlation between [NeIII]3869/Hβ and [OIII]5007/Hβ seen in the local sample, which implies that the same projection that cancels ionization dependence for the oxygen pair should cancel it for the oxygen-neon pair. Fitting a third-order polynomial in $x=12+\log(O/H)-8.69$ to 782 local galaxies gives $\widehat{RNe}=0.04-0.78x-0.82x^2-0.14x^3$, and applying this calibration to the 22 high-redshift galaxies not used in the fit gives 1σ scatter of 0.11 dex in the $\widehat{RNe}$ direction and 0.16 dex in $\Delta\log(O/H)$. The paper presents the diagnostic as a way to obtain Te-anchored metallicities in the gap $9.5 \lesssim z \lesssim 11.2$, where the lines needed for $\hat{R}$ are no longer observable.

Load-bearing premise

The new diagnostic assumes that the weight coefficients that cancel ionization dependence for the [OII]+[OIII] pair also cancel it for the [OII]+[NeIII] pair, and that neon-to-oxygen ratios do not evolve with redshift or metallicity.

Editorial extensions

If this is right

  • Metallicities of galaxies at z~9.5–11.2 can be estimated from [OII], [NeIII], and Hγ alone, without relying on [OIII]5007 or auroral lines.
  • The $\hat{R}$ and $\widehat{RNe}$ diagnostics can be applied across essentially the whole observable history of star-forming galaxies with a single, redshift-independent calibration.
  • Nitrogen-based strong-line diagnostics (N2, O3N2, N2O2) applied to high-redshift galaxies will overestimate oxygen abundance unless the enhanced N/O ratio at fixed O/H is modelled.
  • If the FMR offset at z>4 is confirmed with larger $T_e$ samples, it would indicate that gas accretion, star formation, and metal enrichment are not yet balanced in early galaxies.
  • The recalibrated $\hat{R}$ relation improves low-metallicity metallicity estimates compared with the original version, with out-of-sample scatter of about 0.11 dex in oxygen abundance for the high-redshift sample.

Reading between the lines

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

  • The same coefficient-transfer trick could be tested on other pairs of lines with similar ionization-potential matching, such as [SII] and [OII] or [ArIII] and [NeIII], yielding additional redshift-resilient diagnostics with different line strengths.
  • If $\widehat{RNe}$ performs as claimed on existing z~9.5–11 spectra, it will become a practical way to push mass-metallicity relation measurements into the first billion years without waiting for auroral-line detections.
  • A crucial independent check is to compare $\widehat{RNe}$- and $\hat{R}$-based metallicities in the same galaxies wherever both line sets are detected; a redshift-dependent residual difference would indicate Ne/O evolution rather than simple projection transfer.
  • The FMR deviations at z>4 reported here will become decisive once homogeneous local and high-redshift $T_e$ samples are analysed with identical abundance pipelines, rather than comparing separately calibrated samples.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper presents electron-temperature (Te) metallicity measurements for 22 JWST/EXCELS galaxies at 1.65 < z < 7.92 and 782 DESI EDR galaxies at low redshift, and uses these to test and recalibrate strong-line metallicity diagnostics. The authors find that many commonly used diagnostics (R2, R3, O32, N2-based ratios, etc.) are biased at high redshift because of systematic evolution in ionisation parameter and in N/O abundance ratio. They recalibrate the bR diagnostic introduced by Laseter et al. (2024), and propose a new neon-based diagnostic, RNe = 0.47 log([OII]/Hgamma) + 0.88 log([NeIII]/Hgamma), which they argue is insensitive to ionisation parameter and applicable up to z~11.2. They also examine the mass-metallicity relation and the fundamental metallicity relation, reporting tentative evidence for a z>4 deviation from the local FMR. The paper includes detailed forward-model abundance measurements, residual tables for numerous calibrations, and a leave-one-out KDE calibration.

Significance. If the RNe diagnostic is valid, it fills a real wavelength-coverage gap for JWST/NIRSpec at 9.5 < z < 11.2, where [OIII]5007 is no longer observable but [OII], [NeIII] and Hgamma remain in band. The paper's Te measurements and its comparison between local and high-redshift auroral-line samples are valuable empirical contributions, and the explicit out-of-sample validation on the EXCELS set (0.11 dex scatter for bR, 0.16 dex for RNe in O/H) is a strength. The authors also provide machine-readable tables of line ratios, metallicities, and residual diagnostics, which will be useful for future calibration work. The main significance hinges on whether the RNe projection truly inherits the ionisation-parameter cancellation of bR, and on whether Ne/O remains constant to z~11; these are the load-bearing points that need strengthening.

major comments (3)
  1. [6.3.1, Eq. (16)] The central claim that RNe is insensitive to ionisation parameter rests on transferring the bR weights (0.47, 0.88) from the [OII]+[OIII] combination to the [OII]+[NeIII] combination. The justification given in Section 6.3, namely a Pearson correlation of r=0.85 between R3 and Ne3, establishes that the two line ratios are strongly correlated in flux, but it does not establish that their partial derivatives with respect to log U at fixed O/H are proportional over the relevant EW(Hbeta) range. Because Ne++ has a higher ionisation potential than O++, the optimal projection that cancels the ionisation-parameter dependence need not be identical for [NeIII] and [OIII]. The paper should either fit the two coefficients directly to the DESI sample and compare the resulting projection with the imported values, or demonstrate that the RNe residuals for both samples do not correlate with EW(Hbeta); the reported 0.16 dex scatter in O/H alone does not rule out a residual ionisation dependence.
  2. [6.3 and 8.1.1 (z~11.2 claim)] The applicability of RNe at z~9.5-11.2 assumes that Ne/O does not evolve at fixed O/H over that interval. The paper states that alpha-element abundances evolve in tandem with oxygen and cites Henry (1989), Garnett (2002), Stanton et al. (2025), Arellano-Cordova et al. (2024b) and Esteban et al. (2025), but those empirical confirmations are explicitly described as extending only to z=5.3. The EXCELS validation sample itself reaches only z=7.92, and no Te metallicity anchors exist in the proposed z>9.5 regime. An unmodelled Ne/O evolution at these redshifts translates directly into a systematic metallicity bias in exactly the regime where the diagnostic is proposed as the main tool. Please quantify the allowed Ne/O variation from the current sample or from photoionisation-model grids, or temper the wording in the abstract and Section 6.3.1 to distinguish accessibility of the line ratio from demonstrated accuracy.
  3. [6.3.1, Eq. (17) and Figure 9] The RNe calibration polynomial is fitted to the DESI sample using RNe values computed with the imported bR weights, so the fit coefficients can partially absorb a suboptimal projection for the local sample. However, the EXCELS validation at z~4 is the only high-redshift test, and it contains only 19 galaxies with [NeIII] measurements. The paper reports the out-of-sample scatter but not the uncertainty on that scatter, nor does it show the residuals split by EW(Hbeta) or by redshift. Given that the claimed advantage of RNe over Ne3O2 is precisely its insensitivity to ionisation parameter, a binned residual plot against EW(Hbeta) and against redshift would make the claim substantially more convincing and is a natural, inexpensive addition.
minor comments (6)
  1. [Appendix A, Figures A1 and A2] The notation 'bias +/- scatter' should define which statistics are used (e.g., mean or median residual, and 1-sigma or 16-84 percentile scatter); without this definition the residual tables are difficult to reproduce or compare across diagnostics.
  2. [Section 3.3] The rejection criterion for AGN activity is described as 'no abnormal measurements in 12+log(O/H) versus Te space', but the threshold for 'abnormal' is not quantified; a brief operational definition would improve reproducibility.
  3. [Eq. (11)] The phrase 'with a correction which reduces Te([OII]) by 1500 K compared to the original relation' is slightly misleading because the correction modifies the intercept of the T2-T3 relation; rephrasing as 'reduces Te([OII]) by 1500 K at fixed Te([OIII])' would be clearer.
  4. [Section 8.1.1 and Conclusions] The statement that RNe can be used with JWST/NIRSpec at z~11.2 would benefit from an explicit wavelength check: Hgamma at z=11.2 is near the long-wavelength edge of NIRSpec, so the practical sensitivity limit deserves a brief quantitative discussion.
  5. [Table C1] The paper notes that [NeIII] is missing for three targets because of detector gaps; it would help readers if the caption of Table C1 explicitly listed those targets (45393, 93897, 123837) so that missing RNe values are not mistaken for non-detections.
  6. [Data availability] The data availability statement says the derived products 'will be made available' at a personal URL; please provide the final persistent link or DOI at the time of acceptance.

Circularity Check

0 steps flagged · score 2.0 of 10

No circular reduction: the strong-line calibrations are fitted to DESI EDR and tested on the external EXCELS sample; the RNe coefficient transfer from Laseter et al. is an unverified assumption, not a self-definitional step.

full rationale

The paper's central derivations are not circular. The bR recalibration (Eq. 15), the new RNe calibration (Eq. 17), and the KDE-based calibration are all fitted to the DESI EDR Te-metallicity sample and then applied to the EXCELS sample, which was not used in the fits. Section 6.3.1 explicitly reports the out-of-sample residuals: 'The residual scatter for the EXCELS sample which was not used in the fitting of the line ratio is 0.11 dex and 0.16 dex' in Delta-RNe and Delta-log(O/H), respectively. The KDE treatment uses a leave-one-out approach for the DESI calibration sample, so its DESI residuals are not in-sample predictions. The RNe diagnostic reuses the bR coefficients (0.47, 0.88) from Laseter et al. (2024) rather than re-deriving them for the neon-based ratio; this is justified by the empirical R3-Ne3 correlation. This is a transfer assumption and a scientific validity risk, but it is not a circular reduction: no equation makes RNe equal to bR by construction, and the coefficients are not fitted to the validation data. The statements that sulfur and neon evolve in tandem with oxygen cite self-authored works (Stanton et al. 2025; Arellano-Cordova et al. 2024b) but also independent references (Henry 1989; Garnett 2002; Esteban et al. 2025), so the self-citation is not load-bearing. The z~11.2 applicability is an extrapolation and the transferability of the optimal ionization-parameter-insensitive projection is not demonstrated, but these are concerns about correctness, not circularity. Score 2 reflects only the presence of minor self-citations in supporting arguments.

Assumptions & free parameters 3 free parameters · 7 assumptions · 0 invented entities

The central new calibrations require five fitted coefficients, and the RNe diagnostic inherits two weighting coefficients from Laseter et al. The Te-metallicity measurements themselves rely on standard astrophysical assumptions: the T2-T3 temperature relation, the two-zone ionization model, case-B recombination, and the N/O = N+/O+ approximation. No new physical entities are introduced.

free parameters (3)
  • bR recalibration coefficients c0..c3 = c0=0.59, c1=-0.64, c2=-0.70, c3=-0.10 (low-metallicity branch, Eq. 15)
    Orthogonal distance regression fit to 782 DESI EDR Te-metallicity galaxies; defines the paper's bR calibration in the low-metallicity regime.
  • RNe calibration coefficients c0..c3 = c0=0.04, c1=-0.78, c2=-0.82, c3=-0.14 (Eq. 17)
    ODR fit to the DESI EDR sample; defines the new RNe metallicity calibration.
  • RNe line-ratio weights 0.47 and 0.88 = 0.47, 0.88 (from Laseter et al. 2024)
    Chosen by hand from prior work, not re-fit for RNe; the paper assumes these weights are optimal for the new [OII]/Hgamma plus [NeIII]/Hgamma combination.
assumptions (7)
  • domain assumption Te([OII]) = 0.7 * Te([OIII]) + 1500 K (T2-T3 relation)
    Used in the two-zone PyNeb model to set the low-ionization zone temperature; based on Campbell et al. (1986) and Garnett (1992) with a 1500 K empirical correction from Andrews & Martini (2013). Section 4.3, Eq. 11.
  • domain assumption Total oxygen abundance equals O+/H+ + O++/H+
    Assumes higher ionization states, such as O3+, contribute negligibly, citing Berg et al. (2021). Section 4.3, Eq. 12.
  • domain assumption N/O equals N+/H+ divided by O+/H+
    Assumes the [NII]/[OII] ratio traces the total N/O ratio because of similar ionization potentials. Section 4.3, Eq. 13.
  • domain assumption Neon and sulfur abundances evolve in tandem with oxygen at fixed O/H
    Used to argue that neon- and sulfur-based diagnostics are not biased by abundance-ratio evolution, and to justify RNe. Cited support exists up to z=5.3, but is assumed at z>9.5. Section 6.3.
  • ad hoc to paper The optimal bR weights (0.47, 0.88) transfer to the RNe combination
    The paper does not derive or fit the weights for the [OII]/Hgamma plus [NeIII]/Hgamma combination; it assumes the strong R3-Ne3 correlation makes the bR projection optimal for RNe. Section 6.3.1.
  • domain assumption Case-B recombination with Balmer ratios computed at the model electron temperature
    Used to dust-correct line fluxes and to convert Hgamma/Hbeta constraints; Section 4.3.
  • domain assumption Balmer absorption correction uses an emission filling fraction of 30 per cent
    Applied to Balmer lines based on Reddy et al. (2018); affects flux measurements by a few per cent. Section 3.2.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The JWST EXCELS survey: Probing strong-line diagnostics and the chemical evolution of galaxies over cosmic time using Te-metallicities." pith.science (2026). https://pith.science/paper/BZ4TJVCK

@misc{pith2026250210499,
  author       = {Pith},
  title        = {Pith review of: The JWST EXCELS survey: Probing strong-line diagnostics and the chemical evolution of galaxies over cosmic time using Te-metallicities},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BZ4TJVCK}},
  note         = {Machine review of arXiv:2502.10499}
}
abstract

We present an analysis of the rest-frame optical spectra of 22 [OIII]$\lambda$4363 detected galaxies in the redshift range $1.65 < z < 7.92$ (with $\langle z \rangle$ = 4.05) from JWST/NIRSpec medium-resolution observations taken as part of the EXCELS survey. To supplement these high-redshift sources, we also consider a sample of 782 local [OIII]$\lambda$4363 detected galaxies from the DESI Early Data Release. Our analysis demonstrates that many strong-line calibrations are biased in the early Universe due to the systematic evolution in ionization conditions with redshift. However, the recently introduced $\widehat{R}$ calibration mostly removes the dependence on ionization state and can be considered a largely redshift-independent calibration. In a similar spirit, we introduce a new strong-line diagnostic, $\widehat{RNe}$, which can be used to robustly estimate metallicities when the [OIII]$\lambda$5007 is redshifted out of the wavelength range of JWST/NIRSpec at $z > 9.5$. We also show that strong-line diagnostics using the [NII]$\lambda$6584 emission line are likely to be biased at high-redshift due to a moderate enhancement in the average N/O abundance ratios (at fixed O/H) in these sources. Finally, we discuss the location of our new [OIII]$\lambda$4363 detected galaxies at $z \simeq 4$ on the mass-metallicity plane and investigate the redshift evolution of the fundamental metallicity relation (FMR). We find tentative evidence for an increasing deviation from the FMR at $z > 4$ which might indicate fundamental differences in the baryon cycle at these redshifts. However, more data are required as our high-redshift constraints are still based on a relatively small sample of galaxies and the significance of the deviation is strongly dependent on the assumed form of the fundamental metallicity relation.

Figures

Figures reproduced from arXiv: 2502.10499 by the authors.

Figure 1
Figure 1. An example of a JWST EXCELS spectrum (black, grey 1𝜎 uncertainties) of EXCELS-121806 (see also Arellano-Córdova et al. 2024a) shown together with the fitted continuum and emission line measurements (red). The three panels show the observed flux in the NIRSpec G140M (top), G235M (middle), G395M (bottom) gratings. Inset panels zoom in on the strongest emission lines observed in each grating. Due to overlap in the wave… view at source ↗
Figure 2
Figure 2. The posterior distribution of our abundance measurements for EXCELS target 40081. The dimensions shown are electron density (𝑛𝑒), electron temperature (𝑇𝑒), singly and doubly ionised oxygen (O+ /H+ and O ++/H+ ), singly ionised nitrogen (N+ /H+ ) and dust attenuation (𝐴𝑉 ). The observed (red) and modelled line ratios are shown in the 5 panels in the top￾right corner of the figure. by Sanders et al. (2024a) the dust … view at source ↗
Figure 3
Figure 3. Left: The EXCELS and DESI EDR galaxies in the [Nii]-BPT diagram (Baldwin et al. 1981). We show the EXCELS (maroon-hexagons for [Oiii]𝜆4363 detections, cream squares for non-detections of [Oiii]𝜆4363), AURORA (purple circles, no selection on [Oiii]𝜆4363; Shapley et al. 2024) and our sample of [Oiii]𝜆4363 detected DESI EDR galaxies (white circles). EXCELS galaxies which were not observed in H𝛼 or [Nii]6584 are display… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: The relation between 𝑇𝑒-metallicity and strong-line ratios of the JWST EXCELS (hexagons, maroon edges) and the local sample of DESI EDR galaxies (circles, grey edges). The R2, R3, O32, R23, 𝑅b, (left-to-right and top-to-bottom) strong-line ratios are shown in the indiv…
Figure 5
Figure 5. Figure 5: Left: An enlarged version of the 𝑅b panel in [PITH_FULL_IMAGE:figures/full_fig_p012_5.png]
Figure 6
Figure 6. Figure 6: The relation between 𝑇𝑒-metallicity and nitrogen based strong-line ratios of the JWST EXCELS (hexagons, maroon edges) and the local sample of DESI EDR galaxies (circles, grey edges). N2, O3N2 and N2O2 (left-to-right and top-to-bottom) strong-line ratios are shown in th…
Figure 7
Figure 7. Figure 7: The same as [PITH_FULL_IMAGE:figures/full_fig_p014_7.png]
Figure 8
Figure 8. Figure 8: The relation between 𝑇𝑒-metallicity and the 𝑆2 (left), 𝑁 𝑒3𝑂2 (middle) and 𝑅𝑁 𝑒 š (right) strong-line ratios of the JWST EXCELS (hexagons, maroon edges) and the local sample of DESI EDR galaxies (circles, grey edges). The data points are coloured according to their H𝛽 …
Figure 9
Figure 9. Figure 9: Left: An enlarged version of the 𝑅𝑁 𝑒 š panel in [PITH_FULL_IMAGE:figures/full_fig_p015_9.png]
Figure 10
Figure 10. Figure 10: [Oiii]𝜆4363 detected galaxies on the mass-metallicity plane. The mass-metallicity relation for our EXCELS measurements (black outlined hexagons and diamonds), DESI measurements (grey outlined circles) and 𝑧 > 2 literature values (crosses; Sanders et al. 2023a; Nakajim…
Figure 11
Figure 11. Figure 11: Our sample of EXCELS galaxies (hexagons and diamonds) on the mass-metallicity plane coloured by star formation rate, shown together with 𝑧 > 2 literature values (crosses; Sanders et al. 2023a; Nakajima et al. 2023; Curti et al. 2023; Morishita et al. 2024; Cullen et a…
Figure 12
Figure 12. Figure 12: The redshift dependence of the residuals of the EXCELS (hexagons and diamonds) and literature (crosses) measurements with respect to the Andrews & Martini (2013) parametrisation of the FMR in the top panel and the Curti et al. (2020) FMR in the bottom panel. We also s…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 5 Pith papers

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

  1. First joint absorption and T$_e$-based metallicity measured in a GRB host galaxy at $z=4.28$ using JWST/NIRSpec

    astro-ph.GA 2025-06 conditional novelty 7.0 of 10

    The first joint absorption and electron-temperature-based metallicity measurement in a high-redshift GRB host galaxy shows agreement between cold and warm gas probes.

  2. ChemZz I: Comparing Oxygen and Iron Abundance Patterns in the Milky Way, the Local Group and Cosmic Noon

    astro-ph.GA 2025-07 conditional novelty 6.0 of 10

    After placing local and distant galaxy abundances on a common scale, the authors find Milky Way high-alpha disc patterns at z~2-3, evidence for alpha-bimodality in M31, and place the MW and GSE on the z~3 mass-metalli...

  3. The Interstellar Medium in I Zw 18 seen with JWST/MIRI: III. Spatially Resolved Three Ionization State Oxygen Abundance

    astro-ph.GA 2025-07 conditional novelty 6.0 of 10

    Spatially resolved direct-method oxygen abundances in I Zw 18 reveal 60 pc-scale chemical inhomogeneities and an oxygen ionization correction factor that underestimates O3+/H+ by ~2.

  4. Explaining the Weak Evolution of the High-Redshift Mass-Metallicity Relation with Galaxy Burst Cycles

    astro-ph.GA 2025-05 conditional novelty 6.0 of 10

    A simplified burst-cycle model shows the constant high-redshift MZR in FIRE-2 arises from a balance between rising inflow metallicity and falling metal production efficiency.

  5. First IFU observations of two GRB host galaxies at cosmic noon with JWST/NIRSpec

    astro-ph.GA 2025-05 conditional novelty 6.0 of 10

    First JWST/NIRSpec IFU resolved spectroscopy of two GRB hosts at z~2-2.6 shows each is a multi-component interacting system, with spatially resolved SFRs and metallicities that differ from integrated values.

Reference graph

Works this paper leans on

177 extracted references · 8 canonical work pages · cited by 5 Pith papers

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    M., Keenan F

    Aggarwal K. M., Keenan F. P., 1999, , 123, 311

    1999

  3. [3]

    H., 1984, Physics of thermal gaseous nebulae , @doi 10.1007/978-94-010-9639-3

    Aller L. H., 1984, Physics of thermal gaseous nebulae , @doi 10.1007/978-94-010-9639-3

    doi:10.1007/978-94-010-9639-3 1984

  4. [4]

    Alloin D., Collin-Souffrin S., Joly M., Vigroux L., 1979, , https://ui.adsabs.harvard.edu/abs/1979A&A....78..200A 78, 200

    1979

  5. [5]

    Amayo A., Delgado-Inglada G., Stasi \'n ska G., 2021, @doi [ ] 10.1093/mnras/stab1467 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.2361A 505, 2361

    doi:10.1093/mnras/stab1467 2021

  6. [6]

    O., P \'e rez-Montero E., V \' lchez J

    Amor \' n R. O., P \'e rez-Montero E., V \' lchez J. M., 2010, @doi [ ] 10.1088/2041-8205/715/2/L128 , https://ui.adsabs.harvard.edu/abs/2010ApJ...715L.128A 715, L128

    doi:10.1088/2041-8205/715/2/l128 2010

  7. [7]

    H., Martini P., 2013, @doi [ ] 10.1088/0004-637X/765/2/140 , https://ui.adsabs.harvard.edu/abs/2013ApJ...765..140A 765, 140

    Andrews B. H., Martini P., 2013, @doi [ ] 10.1088/0004-637X/765/2/140 , https://ui.adsabs.harvard.edu/abs/2013ApJ...765..140A 765, 140

    doi:10.1088/0004-637x/765/2/140 2013

  8. [8]

    Z., Rodr \' guez M., 2020, @doi [ ] 10.1093/mnras/staa1759 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497..672A 497, 672

    Arellano-C \'o rdova K. Z., Rodr \' guez M., 2020, @doi [ ] 10.1093/mnras/staa1759 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497..672A 497, 672

    doi:10.1093/mnras/staa1759 2020

Show all 177 references
  1. [9]

    Z., et al., 2022, @doi [ ] 10.3847/2041-8213/ac9ab2 , https://ui.adsabs.harvard.edu/abs/2022ApJ...940L..23A 940, L23

    Arellano-C \'o rdova K. Z., et al., 2022, @doi [ ] 10.3847/2041-8213/ac9ab2 , https://ui.adsabs.harvard.edu/abs/2022ApJ...940L..23A 940, L23

    2022 doi

  2. [10]

    Z., et al., 2024a, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2024arXiv241210557A p

    Arellano-C \'o rdova K. Z., et al., 2024a, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2024arXiv241210557A p. arXiv:2412.10557

    arXiv

  3. [11]

    Z., et al., 2024b, @doi [ ] 10.3847/1538-4357/ad34cf , https://ui.adsabs.harvard.edu/abs/2024ApJ...968...98A 968, 98

    Arellano-C \'o rdova K. Z., et al., 2024b, @doi [ ] 10.3847/1538-4357/ad34cf , https://ui.adsabs.harvard.edu/abs/2024ApJ...968...98A 968, 98

    doi

  4. [12]

    M., Grevesse N., 2021, @doi [ ] 10.1051/0004-6361/202140445 , https://ui.adsabs.harvard.edu/abs/2021A&A...653A.141A 653, A141

    Asplund M., Amarsi A. M., Grevesse N., 2021, @doi [ ] 10.1051/0004-6361/202140445 , https://ui.adsabs.harvard.edu/abs/2021A&A...653A.141A 653, A141

    2021 doi

  5. [13]

    A., Phillips M

    Baldwin J. A., Phillips M. M., Terlevich R., 1981, @doi [ ] 10.1086/130766 , https://ui.adsabs.harvard.edu/abs/1981PASP...93....5B 93, 5

    1981 doi

  6. [14]

    A., Chisholm J., Erb D

    Berg D. A., Chisholm J., Erb D. K., Skillman E. D., Pogge R. W., Olivier G. M., 2021, @doi [ ] 10.3847/1538-4357/ac141b , https://ui.adsabs.harvard.edu/abs/2021ApJ...922..170B 922, 170

    2021 doi

  7. [15]

    Bertin E., Arnouts S., 1996, @doi [ ] 10.1051/aas:1996164 , https://ui.adsabs.harvard.edu/abs/1996A&AS..117..393B 117, 393

    1996 doi

  8. [16]

    J., Dopita M

    Bian F., Kewley L. J., Dopita M. A., 2018, @doi [ ] 10.3847/1538-4357/aabd74 , https://ui.adsabs.harvard.edu/abs/2018ApJ...859..175B 859, 175

    2018 doi

  9. [17]

    A., Kewley L., Vogt F

    Blanc G. A., Kewley L., Vogt F. P. A., Dopita M. A., 2015, @doi [ ] 10.1088/0004-637X/798/2/99 , https://ui.adsabs.harvard.edu/abs/2015ApJ...798...99B 798, 99

    2015 doi

  10. [18]

    T., Donaldson J

    Boggs P. T., Donaldson J. R., Byrd R. H., Schnabel R. B., 1981, ACM Transaction on Mathematical Software, 15, 348

    1981

  11. [19]

    K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

    Boquien M., Burgarella D., Roehlly Y., Buat V., Ciesla L., Corre D., Inoue A. K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

    2019 doi

  12. [20]

    S., Maiolino R., Kennicutt R., Cresci G., Mannucci F., Marconi A., Cicone C., 2013, @doi [ ] 10.1093/mnras/stt817 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.433.1425B 433, 1425

    Bothwell M. S., Maiolino R., Kennicutt R., Cresci G., Mannucci F., Marconi A., Cicone C., 2013, @doi [ ] 10.1093/mnras/stt817 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.433.1425B 433, 1425

    2013 doi

  13. [21]

    S., Maiolino R., Cicone C., Peng Y., Wagg J., 2016, @doi [ ] 10.1051/0004-6361/201527918 , https://ui.adsabs.harvard.edu/abs/2016A&A...595A..48B 595, A48

    Bothwell M. S., Maiolino R., Cicone C., Peng Y., Wagg J., 2016, @doi [ ] 10.1051/0004-6361/201527918 , https://ui.adsabs.harvard.edu/abs/2016A&A...595A..48B 595, A48

    2016 doi

  14. [22]

    A., Coleman T

    Branch M. A., Coleman T. F., Li Y., 1999, @doi [SIAM Journal on Scientific Computing] 10.1137/S1064827595289108 , https://ui.adsabs.harvard.edu/abs/1999SJSC...21....1B 21, 1

    1999 doi

  15. [24]

    Brinchmann J., Charlot S., Kauffmann G., Heckman T., White S. D. M., Tremonti C., 2013, @doi [ ] 10.1093/mnras/stt551 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.432.2112B 432, 2112

    2013 doi

  16. [25]

    Brown T., Cortese L., Catinella B., Kilborn V., 2018, @doi [ ] 10.1093/mnras/stx2452 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473.1868B 473, 1868

    2018 doi

  17. [26]

    Bruzual G., Charlot S., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06897.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.344.1000B 344, 1000

    2003

  18. [27]

    J., Conroy C., Johnson B

    Byler N., Dalcanton J. J., Conroy C., Johnson B. D., 2017, @doi [ ] 10.3847/1538-4357/aa6c66 , https://ui.adsabs.harvard.edu/abs/2017ApJ...840...44B 840, 44

    2017 doi

  19. [28]

    J., Katz H., Rey M

    Cameron A. J., Katz H., Rey M. P., Saxena A., 2023, @doi [ ] 10.1093/mnras/stad1579 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.3516C 523, 3516

    2023 doi

  20. [29]

    Campbell A., Terlevich R., Melnick J., 1986, @doi [ ] 10.1093/mnras/223.4.811 , https://ui.adsabs.harvard.edu/abs/1986MNRAS.223..811C 223, 811

    1986 doi

  21. [30]

    A., Clayton G

    Cardelli J. A., Clayton G. C., Mathis J. S., 1989, @doi [ ] 10.1086/167900 , https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C 345, 245

    1989 doi

  22. [31]

    C., McLure R

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

    2018 doi

  23. [32]

    C., et al., 2019, @doi [ ] 10.1093/mnras/stz2544 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490..417C 490, 417

    Carnall A. C., et al., 2019, @doi [ ] 10.1093/mnras/stz2544 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490..417C 490, 417

    2019 doi

  24. [33]

    C., et al., 2024, @doi [ ] 10.1093/mnras/stae2092 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.534..325C 534, 325

    Carnall A. C., et al., 2024, @doi [ ] 10.1093/mnras/stae2092 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.534..325C 534, 325

    2024 doi

  25. [34]

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

    2003 doi

  26. [35]

    arXiv:2412.15435

    Chakraborty P., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2412.15435 , https://ui.adsabs.harvard.edu/abs/2024arXiv241215435C p. arXiv:2412.15435

    2024 doi

  27. [36]

    Charlot S., Longhetti M., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04260.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.323..887C 323, 887

    2001

  28. [37]

    B., Rudie G

    Chartab N., Newman A. B., Rudie G. C., Blanc G. A., Kelson D. D., 2024, @doi [ ] 10.3847/1538-4357/ad0554 , https://ui.adsabs.harvard.edu/abs/2024ApJ...960...73C 960, 73

    2024 doi

  29. [38]

    E., Sanders R

    Clarke L., Shapley A. E., Sanders R. L., Topping M. W., Brammer G. B., Bento T., Reddy N. A., Kehoe E., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.05178 , https://ui.adsabs.harvard.edu/abs/2024arXiv240605178C p. arXiv:2406.05178

    2024 doi arXiv

  30. [39]

    J., Dunlop J

    Cullen F., Cirasuolo M., McLure R. J., Dunlop J. S., Bowler R. A. A., 2014, @doi [ ] 10.1093/mnras/stu443 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.440.2300C 440, 2300

    2014 doi

  31. [40]

    Cullen F., et al., 2019, @doi [ ] 10.1093/mnras/stz1402 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2038C 487, 2038

    2019 doi

  32. [41]

    Cullen F., et al., 2021, @doi [ ] 10.1093/mnras/stab1340 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505..903C 505, 903

    2021 doi

  33. [42]

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

    2024 doi

  34. [43]

    arXiv:2501.11099

    Cullen F., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2501.11099 , https://ui.adsabs.harvard.edu/abs/2025arXiv250111099C p. arXiv:2501.11099

    2025 doi arXiv

  35. [44]

    Curti M., Cresci G., Mannucci F., Marconi A., Maiolino R., Esposito S., 2017, @doi [ ] 10.1093/mnras/stw2766 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.465.1384C 465, 1384

    2017 doi

  36. [45]

    Curti M., Mannucci F., Cresci G., Maiolino R., 2020, @doi [ ] 10.1093/mnras/stz2910 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491..944C 491, 944

    2020 doi

  37. [46]

    Curti M., et al., 2023, @doi [ ] 10.1093/mnras/stac2737 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518..425C 518, 425

    2023 doi

  38. [47]

    Curti M., et al., 2024, @doi [ ] 10.1051/0004-6361/202346698 , https://ui.adsabs.harvard.edu/abs/2024A&A...684A..75C 684, A75

    2024 doi

  39. [48]

    DESI Collaboration et al., 2022, @doi [ ] 10.3847/1538-3881/ac882b , https://ui.adsabs.harvard.edu/abs/2022AJ....164..207D 164, 207

    2022 doi

  40. [49]

    arXiv:2306.06307

    DESI Collaboration et al., 2023a, @doi [arXiv e-prints] 10.48550/arXiv.2306.06307 , https://ui.adsabs.harvard.edu/abs/2023arXiv230606307D p. arXiv:2306.06307

    doi arXiv

  41. [50]

    arXiv:2306.06308

    DESI Collaboration et al., 2023b, @doi [arXiv e-prints] 10.48550/arXiv.2306.06308 , https://ui.adsabs.harvard.edu/abs/2023arXiv230606308D p. arXiv:2306.06308

    doi arXiv

  42. [51]

    Darragh-Ford E., et al., 2023, @doi [ ] 10.3847/1538-4357/ace902 , https://ui.adsabs.harvard.edu/abs/2023ApJ...954..149D 954, 149

    2023 doi

  43. [52]

    D., 2012, @doi [ ] 10.1111/j.1365-2966.2011.20148.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.421...98D 421, 98

    Dav \'e R., Finlator K., Oppenheimer B. D., 2012, @doi [ ] 10.1111/j.1365-2966.2011.20148.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.421...98D 421, 98

    2012

  44. [53]

    Denicol \'o G., Terlevich R., Terlevich E., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05041.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.330...69D 330, 69

    2002

  45. [54]

    Dey A., et al., 2019, @doi [ ] 10.3847/1538-3881/ab089d , https://ui.adsabs.harvard.edu/abs/2019AJ....157..168D 157, 168

    2019 doi

  46. [55]

    A., 1981, @doi [ ] 10.1007/BF00652928 , https://ui.adsabs.harvard.edu/abs/1981Ap&SS..80..267D 80, 267

    Dottori H. A., 1981, @doi [ ] 10.1007/BF00652928 , https://ui.adsabs.harvard.edu/abs/1981Ap&SS..80..267D 80, 267

    1981 doi

  47. [56]

    S., et al., 2021, PRIMER: Public Release IMaging for Extragalactic Research , JWST Proposal

    Dunlop J. S., et al., 2021, PRIMER: Public Release IMaging for Extragalactic Research , JWST Proposal. Cycle 1, ID. \#1837

    2021

  48. [57]

    L., Patton D

    Ellison S. L., Patton D. R., Simard L., McConnachie A. W., 2008, @doi [ ] 10.1086/527296 , https://ui.adsabs.harvard.edu/abs/2008ApJ...672L.107E 672, L107

    2008 doi

  49. [59]

    Esteban C., Bresolin F., Peimbert M., Garc \' a-Rojas J., Peimbert A., Mesa-Delgado A., 2009, @doi [ ] 10.1088/0004-637X/700/1/654 , https://ui.adsabs.harvard.edu/abs/2009ApJ...700..654E 700, 654

    2009 doi

  50. [60]

    R., Mesa-Delgado A., 2014, @doi [ ] 10.1093/mnras/stu1177 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..624E 443, 624

    Esteban C., Garc \' a-Rojas J., Carigi L., Peimbert M., Bresolin F., L \'o pez-S \'a nchez A. R., Mesa-Delgado A., 2014, @doi [ ] 10.1093/mnras/stu1177 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..624E 443, 624

    2014 doi

  51. [61]

    arXiv:2501.13586

    Esteban C., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2501.13586 , https://ui.adsabs.harvard.edu/abs/2025arXiv250113586E p. arXiv:2501.13586

    2025 doi

  52. [62]

    J., 1996, Hazy, A Brief Introduction to Cloudy 90

    Ferland G. J., 1996, Hazy, A Brief Introduction to Cloudy 90

    1996

  53. [63]

    J., et al., 2017, , https://ui.adsabs.harvard.edu/abs/2017RMxAA..53..385F 53, 385

    Ferland G. J., et al., 2017, , https://ui.adsabs.harvard.edu/abs/2017RMxAA..53..385F 53, 385

    2017

  54. [64]

    Ferruit P., et al., 2022, @doi [ ] 10.1051/0004-6361/202142673 , https://ui.adsabs.harvard.edu/abs/2022A&A...661A..81F 661, A81

    2022 doi

  55. [65]

    Finlator K., Dav \'e R., 2008, @doi [ ] 10.1111/j.1365-2966.2008.12991.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.385.2181F 385, 2181

    2008

  56. [66]

    Froese Fischer C., Tachiev G., 2004, @doi [Atomic Data and Nuclear Data Tables] 10.1016/j.adt.2004.02.001 , https://ui.adsabs.harvard.edu/abs/2004ADNDT..87....1F 87, 1

    2004 doi

  57. [67]

    Galametz A., et al., 2013, @doi [ ] 10.1088/0067-0049/206/2/10 , https://ui.adsabs.harvard.edu/abs/2013ApJS..206...10G 206, 10

    2013 doi

  58. [68]

    Gallazzi A., Charlot S., Brinchmann J., White S. D. M., Tremonti C. A., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09321.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.362...41G 362, 41

    2005

  59. [69]

    M., et al., 2024, @doi [ ] 10.1093/mnras/stae1252 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.1398G 531, 1398

    Garcia A. M., et al., 2024, @doi [ ] 10.1093/mnras/stae1252 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.1398G 531, 1398

    2024 doi

  60. [70]

    R., 1992, @doi [ ] 10.1086/116146 , https://ui.adsabs.harvard.edu/abs/1992AJ....103.1330G 103, 1330

    Garnett D. R., 1992, @doi [ ] 10.1086/116146 , https://ui.adsabs.harvard.edu/abs/1992AJ....103.1330G 103, 1330

    1992 doi

  61. [71]

    R., 2002, @doi [arXiv e-prints] 10.48550/arXiv.astro-ph/0211148 , https://ui.adsabs.harvard.edu/abs/2002astro.ph.11148G pp astro--ph/0211148

    Garnett D. R., 2002, @doi [arXiv e-prints] 10.48550/arXiv.astro-ph/0211148 , https://ui.adsabs.harvard.edu/abs/2002astro.ph.11148G pp astro--ph/0211148

    2002 doi arXiv

  62. [72]

    D., et al., 2022, @doi [ ] 10.3847/1538-3881/ac66dc , https://ui.adsabs.harvard.edu/abs/2022AJ....163..267G 163, 267

    Gordon K. D., et al., 2022, @doi [ ] 10.3847/1538-3881/ac66dc , https://ui.adsabs.harvard.edu/abs/2022AJ....163..267G 163, 267

    2022 doi

  63. [73]

    Hahn C., et al., 2023, @doi [ ] 10.3847/1538-3881/accff8 , https://ui.adsabs.harvard.edu/abs/2023AJ....165..253H 165, 253

    2023 doi

  64. [74]

    C., Johnson B

    Hao C.-N., Kennicutt R. C., Johnson B. D., Calzetti D., Dale D. A., Moustakas J., 2011, @doi [ ] 10.1088/0004-637X/741/2/124 , https://ui.adsabs.harvard.edu/abs/2011ApJ...741..124H 741, 124

    2011 doi

  65. [75]

    E., et al., 2023, @doi [Nature Astronomy] 10.1038/s41550-023-02078-7 , https://ui.adsabs.harvard.edu/abs/2023NatAs...7.1517H 7, 1517

    Heintz K. E., et al., 2023, @doi [Nature Astronomy] 10.1038/s41550-023-02078-7 , https://ui.adsabs.harvard.edu/abs/2023NatAs...7.1517H 7, 1517

    2023 doi

  66. [76]

    Henry R. B. C., 1989, @doi [ ] 10.1093/mnras/241.3.453 , https://ui.adsabs.harvard.edu/abs/1989MNRAS.241..453H 241, 453

    1989 doi

  67. [77]

    Horne K., 1986, @doi [ ] 10.1086/131801 , https://ui.adsabs.harvard.edu/abs/1986PASP...98..609H 98, 609

    1986 doi

  68. [78]

    M., Cortese L., Boselli A., Gavazzi G., Davies J

    Hughes T. M., Cortese L., Boselli A., Gavazzi G., Davies J. I., 2013, @doi [ ] 10.1051/0004-6361/201218822 , https://ui.adsabs.harvard.edu/abs/2013A&A...550A.115H 550, A115

    2013 doi

  69. [79]

    Isobe Y., Ouchi M., Nakajima K., Harikane Y., Ono Y., Xu Y., Zhang Y., Umeda H., 2023, @doi [ ] 10.3847/1538-4357/acf376 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956..139I 956, 139

    2023 doi

  70. [80]

    I., Stasi \'n ska G., Meynet G., Guseva N

    Izotov Y. I., Stasi \'n ska G., Meynet G., Guseva N. G., Thuan T. X., 2006, @doi [ ] 10.1051/0004-6361:20053763 , https://ui.adsabs.harvard.edu/abs/2006A&A...448..955I 448, 955

    2006 doi

  71. [81]

    Jakobsen P., et al., 2022, @doi [ ] 10.1051/0004-6361/202142663 , https://ui.adsabs.harvard.edu/abs/2022A&A...661A..80J 661, A80

    2022 doi

  72. [82]

    Juneau S., et al., 2014, @doi [ ] 10.1088/0004-637X/788/1/88 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...88J 788, 88

    2014 doi

  73. [83]

    Kashino D., et al., 2017, @doi [ ] 10.3847/1538-4357/835/1/88 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835...88K 835, 88

    2017 doi

  74. [84]

    Kashino D., et al., 2022, @doi [ ] 10.3847/1538-4357/ac399e , https://ui.adsabs.harvard.edu/abs/2022ApJ...925...82K 925, 82

    2022 doi

  75. [85]

    Kauffmann G., et al., 2003, @doi [ ] 10.1111/j.1365-2966.2003.07154.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.346.1055K 346, 1055

    2003

  76. [86]

    J., Dopita M

    Kewley L. J., Dopita M. A., 2002, @doi [ ] 10.1086/341326 , https://ui.adsabs.harvard.edu/abs/2002ApJS..142...35K 142, 35

    2002 doi

  77. [87]

    J., Ellison S

    Kewley L. J., Ellison S. L., 2008, @doi [ ] 10.1086/587500 , https://ui.adsabs.harvard.edu/abs/2008ApJ...681.1183K 681, 1183

    2008 doi

  78. [88]

    J., Dopita M

    Kewley L. J., Dopita M. A., Sutherland R. S., Heisler C. A., Trevena J., 2001, @doi [ ] 10.1086/321545 , https://ui.adsabs.harvard.edu/abs/2001ApJ...556..121K 556, 121

    2001 doi

  79. [89]

    J., Nicholls D

    Kewley L. J., Nicholls D. C., Sutherland R. S., 2019, @doi [ ] 10.1146/annurev-astro-081817-051832 , https://ui.adsabs.harvard.edu/abs/2019ARA&A..57..511K 57, 511

    2019 doi

  80. [91]

    I., Lugaro M., 2020, @doi [ ] 10.3847/1538-4357/abae65 , https://ui.adsabs.harvard.edu/abs/2020ApJ...900..179K 900, 179

    Kobayashi C., Karakas A. I., Lugaro M., 2020, @doi [ ] 10.3847/1538-4357/abae65 , https://ui.adsabs.harvard.edu/abs/2020ApJ...900..179K 900, 179

    2020 doi

  81. [92]

    A., Kewley L

    Kobulnicky H. A., Kewley L. J., 2004, @doi [ ] 10.1086/425299 , https://ui.adsabs.harvard.edu/abs/2004ApJ...617..240K 617, 240

    2004 doi

  82. [93]

    Koposov S., et al., 2022, joshspeagle/dynesty: v2.0.3 , @doi 10.5281/zenodo.7388523

    2022 doi

  83. [94]

    arXiv:2409.07455

    Langeroodi D., Hjorth J., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2409.07455 , https://ui.adsabs.harvard.edu/abs/2024arXiv240907455L p. arXiv:2409.07455

    2024 doi

  84. [95]

    A., et al., 2010, @doi [ ] 10.1051/0004-6361/201014803 , https://ui.adsabs.harvard.edu/abs/2010A&A...521L..53L 521, L53

    Lara-L \'o pez M. A., et al., 2010, @doi [ ] 10.1051/0004-6361/201014803 , https://ui.adsabs.harvard.edu/abs/2010A&A...521L..53L 521, L53

    2010 doi

  85. [96]

    A., et al., 2013, @doi [ ] 10.1093/mnrasl/slt054 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.433L..35L 433, L35

    Lara-Lopez M. A., et al., 2013, @doi [ ] 10.1093/mnrasl/slt054 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.433L..35L 433, L35

    2013 doi

  86. [97]

    H., et al., 2024, @doi [ ] 10.1051/0004-6361/202347133 , https://ui.adsabs.harvard.edu/abs/2024A&A...681A..70L 681, A70

    Laseter I. H., et al., 2024, @doi [ ] 10.1051/0004-6361/202347133 , https://ui.adsabs.harvard.edu/abs/2024A&A...681A..70L 681, A70

    2024 doi

  87. [98]

    F., Serrano A., Torres-Peimbert S., 1979, , https://ui.adsabs.harvard.edu/abs/1979A&A....80..155L 80, 155

    Lequeux J., Peimbert M., Rayo J. F., Serrano A., Torres-Peimbert S., 1979, , https://ui.adsabs.harvard.edu/abs/1979A&A....80..155L 80, 155

    1979

  88. [99]

    Li M., et al., 2023, @doi [ ] 10.3847/2041-8213/acf470 , https://ui.adsabs.harvard.edu/abs/2023ApJ...955L..18L 955, L18

    2023 doi

  89. [100]

    J., Carollo C

    Lilly S. J., Carollo C. M., Pipino A., Renzini A., Peng Y., 2013, @doi [ ] 10.1088/0004-637X/772/2/119 , https://ui.adsabs.harvard.edu/abs/2013ApJ...772..119L 772, 119

    2013 doi

  90. [101]

    A., 2015, @doi [ ] 10.1051/0004-6361/201323152 , https://ui.adsabs.harvard.edu/abs/2015A&A...573A..42L 573, A42

    Luridiana V., Morisset C., Shaw R. A., 2015, @doi [ ] 10.1051/0004-6361/201323152 , https://ui.adsabs.harvard.edu/abs/2015A&A...573A..42L 573, A42

    2015 doi

  91. [102]

    Maiolino R., Mannucci F., 2019, @doi [ ] 10.1007/s00159-018-0112-2 , https://ui.adsabs.harvard.edu/abs/2019A&ARv..27....3M 27, 3

    2019 doi

  92. [103]

    Mannucci F., Cresci G., Maiolino R., Marconi A., Gnerucci A., 2010, @doi [ ] 10.1111/j.1365-2966.2010.17291.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.408.2115M 408, 2115

    2010

  93. [104]

    Marconi A., et al., 2024, @doi [ ] 10.1051/0004-6361/202449240 , https://ui.adsabs.harvard.edu/abs/2024A&A...689A..78M 689, A78

    2024 doi

  94. [105]

    Marques-Chaves R., et al., 2024, @doi [ ] 10.1051/0004-6361/202347411 , https://ui.adsabs.harvard.edu/abs/2024A&A...681A..30M 681, A30

    2024 doi

  95. [106]

    V., et al., 2023, @doi [ ] 10.3847/1538-4357/acf12b , https://ui.adsabs.harvard.edu/abs/2023ApJ...956...11M 956, 11

    Maseda M. V., et al., 2023, @doi [ ] 10.3847/1538-4357/acf12b , https://ui.adsabs.harvard.edu/abs/2023ApJ...956...11M 956, 11

    2023 doi

  96. [107]

    Mazzolari G., et al., 2024, @doi [ ] 10.1051/0004-6361/202450407 , https://ui.adsabs.harvard.edu/abs/2024A&A...691A.345M 691, A345

    2024 doi

  97. [108]

    S., 1991, @doi [ ] 10.1086/170569 , https://ui.adsabs.harvard.edu/abs/1991ApJ...380..140M 380, 140

    McGaugh S. S., 1991, @doi [ ] 10.1086/170569 , https://ui.adsabs.harvard.edu/abs/1991ApJ...380..140M 380, 140

    1991 doi

  98. [109]

    J., et al., 2024, @doi [ ] 10.1093/mnras/stad3471 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.5004M 527, 5004

    McLeod D. J., et al., 2024, @doi [ ] 10.1093/mnras/stad3471 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.5004M 527, 5004

    2024 doi

  99. [110]

    J., et al., 2018, @doi [ ] 10.1093/mnras/sty1213 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479...25M 479, 25

    McLure R. J., et al., 2018, @doi [ ] 10.1093/mnras/sty1213 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479...25M 479, 25

    2018 doi

  100. [111]

    Morishita T., et al., 2024, @doi [ ] 10.3847/1538-4357/ad5290 , https://ui.adsabs.harvard.edu/abs/2024ApJ...971...43M 971, 43

    2024 doi

  101. [112]

    J., Tremonti C

    Moustakas J., Kennicutt Robert C. J., Tremonti C. A., Dale D. A., Smith J.-D. T., Calzetti D., 2010, @doi [ ] 10.1088/0067-0049/190/2/233 , https://ui.adsabs.harvard.edu/abs/2010ApJS..190..233M 190, 233

    2010 doi

  102. [113]

    arXiv:1112.3300

    Moustakas J., et al., 2011, @doi [arXiv e-prints] 10.48550/arXiv.1112.3300 , https://ui.adsabs.harvard.edu/abs/2011arXiv1112.3300M p. arXiv:1112.3300

    2011 doi arXiv

  103. [114]

    Moustakas J., Buhler J., Scholte D., Dey B., Khederlarian A., 2023, FastSpecFit: Fast spectral synthesis and emission-line fitting of DESI spectra , Astrophysics Source Code Library, record ascl:2308.005

    2023

  104. [115]

    Nakajima K., et al., 2022, @doi [ ] 10.3847/1538-4365/ac7710 , https://ui.adsabs.harvard.edu/abs/2022ApJS..262....3N 262, 3

    2022 doi

  105. [116]

    Nakajima K., Ouchi M., Isobe Y., Harikane Y., Zhang Y., Ono Y., Umeda H., Oguri M., 2023, @doi [ ] 10.3847/1538-4365/acd556 , https://ui.adsabs.harvard.edu/abs/2023ApJS..269...33N 269, 33

    2023 doi

  106. [117]

    Nava A., Casebeer D., Henry R. B. C., Jevremovic D., 2006, @doi [ ] 10.1086/504416 , https://ui.adsabs.harvard.edu/abs/2006ApJ...645.1076N 645, 1076

    2006 doi

  107. [118]

    C., Dopita M

    Nicholls D. C., Dopita M. A., Sutherland R. S., Jerjen H., Kewley L. J., Basurah H., 2014, @doi [ ] 10.1088/0004-637X/786/2/155 , https://ui.adsabs.harvard.edu/abs/2014ApJ...786..155N 786, 155

    2014 doi

  108. [119]

    Pagel B. E. J., Edmunds M. G., Blackwell D. E., Chun M. S., Smith G., 1979, @doi [ ] 10.1093/mnras/189.1.95 , https://ui.adsabs.harvard.edu/abs/1979MNRAS.189...95P 189, 95

    1979 doi

  109. [120]

    Pagel B. E. J., Simonson E. A., Terlevich R. J., Edmunds M. G., 1992, @doi [ ] 10.1093/mnras/255.2.325 , https://ui.adsabs.harvard.edu/abs/1992MNRAS.255..325P 255, 325

    1992 doi

  110. [121]

    A., 2018, @doi [ ] 10.1093/mnras/sty2508 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.3520P 481, 3520

    Patr \' cio V., Christensen L., Rhodin H., Ca \ n ameras R., Lara-L \'o pez M. A., 2018, @doi [ ] 10.1093/mnras/sty2508 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.3520P 481, 3520

    2018 doi

  111. [122]

    Peimbert M., 1967, @doi [ ] 10.1086/149385 , https://ui.adsabs.harvard.edu/abs/1967ApJ...150..825P 150, 825

    1967 doi

  112. [124]

    Pettini M., Pagel B. E. J., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07591.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.348L..59P 348, L59

    2004

  113. [125]

    S., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0004032 , https://ui.adsabs.harvard.edu/abs/2000A&A...362..325P 362, 325

    Pilyugin L. S., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0004032 , https://ui.adsabs.harvard.edu/abs/2000A&A...362..325P 362, 325

    2000 doi arXiv

  114. [126]

    S., 2001, @doi [ ] 10.1051/0004-6361:20010079 , https://ui.adsabs.harvard.edu/abs/2001A&A...369..594P 369, 594

    Pilyugin L. S., 2001, @doi [ ] 10.1051/0004-6361:20010079 , https://ui.adsabs.harvard.edu/abs/2001A&A...369..594P 369, 594

    2001 doi

  115. [127]

    S., Thuan T

    Pilyugin L. S., Thuan T. X., 2005, @doi [ ] 10.1086/432408 , https://ui.adsabs.harvard.edu/abs/2005ApJ...631..231P 631, 231

    2005 doi

  116. [128]

    S., Mattsson L., V \' lchez J

    Pilyugin L. S., Mattsson L., V \' lchez J. M., Cedr \'e s B., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15182.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.398..485P 398, 485

    2009

  117. [129]

    S., V \' lchez J

    Pilyugin L. S., V \' lchez J. M., Thuan T. X., 2010, @doi [ ] 10.1088/0004-637X/720/2/1738 , https://ui.adsabs.harvard.edu/abs/2010ApJ...720.1738P 720, 1738

    2010 doi

  118. [130]

    M., et al., 2022, @doi [ ] 10.3847/2041-8213/ac8a4e , https://ui.adsabs.harvard.edu/abs/2022ApJ...936L..14P 936, L14

    Pontoppidan K. M., et al., 2022, @doi [ ] 10.3847/2041-8213/ac8a4e , https://ui.adsabs.harvard.edu/abs/2022ApJ...936L..14P 936, L14

    2022 doi

  119. [131]

    Popesso P., et al., 2023, @doi [ ] 10.1093/mnras/stac3214 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.1526P 519, 1526

    2023 doi

  120. [132]

    A., 2008, @doi [ ] 10.1051/0004-6361:200809879 , https://ui.adsabs.harvard.edu/abs/2008A&A...489..555R 489, 555

    Recchi S., Spitoni E., Matteucci F., Lanfranchi G. A., 2008, @doi [ ] 10.1051/0004-6361:200809879 , https://ui.adsabs.harvard.edu/abs/2008A&A...489..555R 489, 555

    2008 doi

  121. [133]

    A., et al., 2018, @doi [ ] 10.3847/1538-4357/aaed1e , https://ui.adsabs.harvard.edu/abs/2018ApJ...869...92R 869, 92

    Reddy N. A., et al., 2018, @doi [ ] 10.3847/1538-4357/aaed1e , https://ui.adsabs.harvard.edu/abs/2018ApJ...869...92R 869, 92

    2018 doi

  122. [134]

    A., et al., 2023a, @doi [ ] 10.3847/1538-4357/acd0b1 , https://ui.adsabs.harvard.edu/abs/2023ApJ...951...56R 951, 56

    Reddy N. A., et al., 2023a, @doi [ ] 10.3847/1538-4357/acd0b1 , https://ui.adsabs.harvard.edu/abs/2023ApJ...951...56R 951, 56

    doi

  123. [135]

    A., Topping M

    Reddy N. A., Topping M. W., Sanders R. L., Shapley A. E., Brammer G., 2023b, @doi [ ] 10.3847/1538-4357/acd754 , https://ui.adsabs.harvard.edu/abs/2023ApJ...952..167R 952, 167

    doi

  124. [136]

    Rogers N. S. J., Strom A. L., Rudie G. C., Trainor R. F., Raptis M., von Raesfeld C., 2024, @doi [ ] 10.3847/2041-8213/ad2f37 , https://ui.adsabs.harvard.edu/abs/2024ApJ...964L..12R 964, L12

    2024 doi

  125. [137]

    Saintonge A., et al., 2017, @doi [ ] 10.3847/1538-4365/aa97e0 , https://ui.adsabs.harvard.edu/abs/2017ApJS..233...22S 233, 22

    2017 doi

  126. [138]

    C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

    Salim S., Boquien M., Lee J. C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

    2018 doi

  127. [139]

    L., et al., 2016, @doi [ ] 10.3847/0004-637X/816/1/23 , https://ui.adsabs.harvard.edu/abs/2016ApJ...816...23S 816, 23

    Sanders R. L., et al., 2016, @doi [ ] 10.3847/0004-637X/816/1/23 , https://ui.adsabs.harvard.edu/abs/2016ApJ...816...23S 816, 23

    2016 doi

  128. [140]

    L., Shapley A

    Sanders R. L., Shapley A. E., Zhang K., Yan R., 2017, @doi [ ] 10.3847/1538-4357/aa93e4 , https://ui.adsabs.harvard.edu/abs/2017ApJ...850..136S 850, 136

    2017 doi

  129. [141]

    L., et al., 2021, @doi [ ] 10.3847/1538-4357/abf4c1 , https://ui.adsabs.harvard.edu/abs/2021ApJ...914...19S 914, 19

    Sanders R. L., et al., 2021, @doi [ ] 10.3847/1538-4357/abf4c1 , https://ui.adsabs.harvard.edu/abs/2021ApJ...914...19S 914, 19

    2021 doi

  130. [142]

    L., et al., 2023a, @doi [ ] 10.3847/1538-4357/aca9cc , https://ui.adsabs.harvard.edu/abs/2023ApJ...943...75S 943, 75

    Sanders R. L., et al., 2023a, @doi [ ] 10.3847/1538-4357/aca9cc , https://ui.adsabs.harvard.edu/abs/2023ApJ...943...75S 943, 75

    doi

  131. [143]

    L., Shapley A

    Sanders R. L., Shapley A. E., Topping M. W., Reddy N. A., Brammer G. B., 2023b, @doi [ ] 10.3847/1538-4357/acedad , https://ui.adsabs.harvard.edu/abs/2023ApJ...955...54S 955, 54

    doi

  132. [144]

    L., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2408.05273 , https://ui.adsabs.harvard.edu/abs/2024arXiv240805273S p

    Sanders R. L., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2408.05273 , https://ui.adsabs.harvard.edu/abs/2024arXiv240805273S p. arXiv:2408.05273

    doi arXiv

  133. [145]

    L., Shapley A

    Sanders R. L., Shapley A. E., Topping M. W., Reddy N. A., Brammer G. B., 2024b, @doi [ ] 10.3847/1538-4357/ad15fc , https://ui.adsabs.harvard.edu/abs/2024ApJ...962...24S 962, 24

    doi

  134. [146]

    Savaglio S., et al., 2005, @doi [ ] 10.1086/497331 , https://ui.adsabs.harvard.edu/abs/2005ApJ...635..260S 635, 260

    2005 doi

  135. [147]

    Scholte D., Saintonge A., 2023, @doi [ ] 10.1093/mnras/stac3134 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.518..353S 518, 353

    2023 doi

  136. [148]

    Scholte D., et al., 2024, @doi [ ] 10.1093/mnras/stae2477 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.535.2341S 535, 2341

    2024 doi

  137. [149]

    W., 1992, Multivariate Density Estimation

    Scott D. W., 1992, Multivariate Density Estimation

    1992

  138. [150]

    E., et al., 2015, @doi [ ] 10.1088/0004-637X/801/2/88 , https://ui.adsabs.harvard.edu/abs/2015ApJ...801...88S 801, 88

    Shapley A. E., et al., 2015, @doi [ ] 10.1088/0004-637X/801/2/88 , https://ui.adsabs.harvard.edu/abs/2015ApJ...801...88S 801, 88

    2015 doi

  139. [151]

    E., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.00157 , https://ui.adsabs.harvard.edu/abs/2024arXiv240700157S p

    Shapley A. E., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.00157 , https://ui.adsabs.harvard.edu/abs/2024arXiv240700157S p. arXiv:2407.00157

    2024 doi arXiv

  140. [152]

    A., Dufour R

    Shaw R. A., Dufour R. J., 1995, @doi [ ] 10.1086/133637 , https://ui.adsabs.harvard.edu/abs/1995PASP..107..896S 107, 896

    1995 doi

  141. [153]

    W., 1986, Density estimation for statistics and data analysis

    Silverman B. W., 1986, Density estimation for statistics and data analysis

    1986

  142. [154]

    S., 2020, @doi [ ] 10.1093/mnras/staa278 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S 493, 3132

    Speagle J. S., 2020, @doi [ ] 10.1093/mnras/staa278 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S 493, 3132

    2020 doi

  143. [155]

    S., Steinhardt C

    Speagle J. S., Steinhardt C. L., Capak P. L., Silverman J. D., 2014, @doi [ ] 10.1088/0067-0049/214/2/15 , https://ui.adsabs.harvard.edu/abs/2014ApJS..214...15S 214, 15

    2014 doi

  144. [156]

    M., et al., 2024, @doi [ ] 10.1093/mnras/stae1705 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.3102S 532, 3102

    Stanton T. M., et al., 2024, @doi [ ] 10.1093/mnras/stae1705 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.3102S 532, 3102

    2024 doi

  145. [157]

    M., et al., 2025, @doi [ ] 10.1093/mnras/staf106 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537.1735S 537, 1735

    Stanton T. M., et al., 2025, @doi [ ] 10.1093/mnras/staf106 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537.1735S 537, 1735

    2025 doi

  146. [158]

    Stasi \'n ska G., 1982, , https://ui.adsabs.harvard.edu/abs/1982A&AS...48..299S 48, 299

    1982

  147. [159]

    R., Charlot S., eds, 0 Vol

    Stasi \'n ska G., 2010, in Bruzual G. R., Charlot S., eds, 0 Vol. 262, Stellar Populations - Planning for the Next Decade. pp 93--96 ( @eprint arXiv 0910.0175 ), @doi 10.1017/S1743921310002590

    2010 arXiv

  148. [160]

    C., et al., 2014, @doi [ ] 10.1088/0004-637X/795/2/165 , https://ui.adsabs.harvard.edu/abs/2014ApJ...795..165S 795, 165

    Steidel C. C., et al., 2014, @doi [ ] 10.1088/0004-637X/795/2/165 , https://ui.adsabs.harvard.edu/abs/2014ApJ...795..165S 795, 165

    2014 doi

  149. [161]

    L., 1994, @doi [ ] 10.1086/174345 , https://ui.adsabs.harvard.edu/abs/1994ApJ...429..572S 429, 572

    Storchi-Bergmann T., Calzetti D., Kinney A. L., 1994, @doi [ ] 10.1086/174345 , https://ui.adsabs.harvard.edu/abs/1994ApJ...429..572S 429, 572

    1994 doi

  150. [162]

    Stoughton C., et al., 2002, @doi [ ] 10.1086/324741 , https://ui.adsabs.harvard.edu/abs/2002AJ....123..485S 123, 485

    2002 doi

  151. [163]

    L., Steidel C

    Strom A. L., Steidel C. C., Rudie G. C., Trainor R. F., Pettini M., Reddy N. A., 2017, @doi [ ] 10.3847/1538-4357/836/2/164 , https://ui.adsabs.harvard.edu/abs/2017ApJ...836..164S 836, 164

    2017 doi

  152. [164]

    L., Steidel C

    Strom A. L., Steidel C. C., Rudie G. C., Trainor R. F., Pettini M., 2018, @doi [ ] 10.3847/1538-4357/aae1a5 , https://ui.adsabs.harvard.edu/abs/2018ApJ...868..117S 868, 117

    2018 doi

  153. [165]

    L., et al., 2023, @doi [ ] 10.3847/2041-8213/ad07dc , https://ui.adsabs.harvard.edu/abs/2023ApJ...958L..11S 958, L11

    Strom A. L., et al., 2023, @doi [ ] 10.3847/2041-8213/ad07dc , https://ui.adsabs.harvard.edu/abs/2023ApJ...958L..11S 958, L11

    2023 doi

  154. [166]

    J., Genzel R., Sternberg A., 2020, @doi [ ] 10.1146/annurev-astro-082812-141034 , https://ui.adsabs.harvard.edu/abs/2020ARA&A..58..157T 58, 157

    Tacconi L. J., Genzel R., Sternberg A., 2020, @doi [ ] 10.1146/annurev-astro-082812-141034 , https://ui.adsabs.harvard.edu/abs/2020ARA&A..58..157T 58, 157

    2020 doi

  155. [167]

    S., 2011, @doi [ ] 10.1088/0067-0049/195/2/12 , https://ui.adsabs.harvard.edu/abs/2011ApJS..195...12T 195, 12

    Tayal S. S., 2011, @doi [ ] 10.1088/0067-0049/195/2/12 , https://ui.adsabs.harvard.edu/abs/2011ApJS..195...12T 195, 12

    2011 doi

  156. [168]

    W., Shapley A

    Topping M. W., Shapley A. E., Reddy N. A., Sanders R. L., Coil A. L., Kriek M., Mobasher B., Siana B., 2020, @doi [ ] 10.1093/mnras/staa1410 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.495.4430T 495, 4430

    2020 doi

  157. [169]

    W., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2407.19009 , https://ui.adsabs.harvard.edu/abs/2024arXiv240719009T p

    Topping M. W., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2407.19009 , https://ui.adsabs.harvard.edu/abs/2024arXiv240719009T p. arXiv:2407.19009

    doi arXiv

  158. [170]

    W., et al., 2024b, @doi [ ] 10.1093/mnras/stae682 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.529.3301T 529, 3301

    Topping M. W., et al., 2024b, @doi [ ] 10.1093/mnras/stae682 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.529.3301T 529, 3301

    doi

  159. [171]

    A., et al., 2004, @doi [ ] 10.1086/423264 , https://ui.adsabs.harvard.edu/abs/2004ApJ...613..898T 613, 898

    Tremonti C. A., et al., 2004, @doi [ ] 10.1086/423264 , https://ui.adsabs.harvard.edu/abs/2004ApJ...613..898T 613, 898

    2004 doi

  160. [172]

    S., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2410.18980 , https://ui.adsabs.harvard.edu/abs/2024arXiv241018980V p

    Vink J. S., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2410.18980 , https://ui.adsabs.harvard.edu/abs/2024arXiv241018980V p. arXiv:2410.18980

    2024 doi arXiv

  161. [173]

    Virtanen P., et al., 2020, @doi [Nature Methods] 10.1038/s41592-019-0686-2 , https://rdcu.be/b08Wh 17, 261

    2020 doi

  162. [174]

    arXiv:2405.06631

    Welch B., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2405.06631 , https://ui.adsabs.harvard.edu/abs/2024arXiv240506631W p. arXiv:2405.06631

    2024 doi arXiv

  163. [175]

    E., Wang J., 2017, @doi [ ] 10.3847/1538-4357/aa8809 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847...38Y 847, 38

    Yang H., Malhotra S., Rhoads J. E., Wang J., 2017, @doi [ ] 10.3847/1538-4357/aa8809 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847...38Y 847, 38

    2017 doi

  164. [176]

    M., Schady P., Chen T

    Yates R. M., Schady P., Chen T. W., Schweyer T., Wiseman P., 2020, @doi [ ] 10.1051/0004-6361/201936506 , https://ui.adsabs.harvard.edu/abs/2020A&A...634A.107Y 634, A107

    2020 doi

  165. [177]

    G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

    York D. G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

    2000 doi

  166. [178]

    J., Geller M

    Zahid H. J., Geller M. J., Kewley L. J., Hwang H. S., Fabricant D. G., Kurtz M. J., 2013, @doi [ ] 10.1088/2041-8205/771/2/L19 , https://ui.adsabs.harvard.edu/abs/2013ApJ...771L..19Z 771, L19

    2013 doi

  167. [179]

    Zou H., et al., 2024, @doi [ ] 10.3847/1538-4357/ad1409 , https://ui.adsabs.harvard.edu/abs/2024ApJ...961..173Z 961, 173

    2024 doi

  168. [180]

    P., 2006, @doi [ ] 10.1086/498017 , https://ui.adsabs.harvard.edu/abs/2006ApJ...636..214V 636, 214

    van Zee L., Haynes M. P., 2006, @doi [ ] 10.1086/498017 , https://ui.adsabs.harvard.edu/abs/2006ApJ...636..214V 636, 214

    2006 doi

  169. [181]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.