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CECILIA: Ultra-Deep Rest-Optical Spectra of Faint Galaxies at Cosmic Noon

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Ultra-deep JWST spectra of nine faint z≈2.5 galaxies show low star-formation rates and low metallicities, with two Lyα emitters whose very low [OIII]/Hβ and [NII]/Hα ratios match the predicted turnover at extremely low oxygen abundance.

desk verdict Genuinely new NIRSpec data on ultra-faint z~2.5 galaxies, with a careful reduction; the very-low-metallicity turnover claim for two sources is plausible but not uniquely constrained by the data. read the letter →

arxiv 2507.22237 v1 pith:KDPXZPQL submitted 2025-07-29 astro-ph.GA

Menelaos Raptis , Ryan F. Trainor , Allison L. Strom , Gwen C. Rudie , Noah S. J. Rogers , Charles C. Steidel , Michael V. Maseda , Caroline von Raesfeld
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Nathalie A. Korhonen Cuestas
This is my paper
classification astro-ph.GA
keywords rest-opticalspectroscopyfaintgalaxiesLy-alphaemittersgas-phasemetallicityBPTdiagnosticdiagramsCosmicNoonlow-massJWSTNIRSpec
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 argues that intrinsically faint galaxies at z≈2.5, previously out of reach for ground-based rest-optical spectroscopy, can now be characterized individually with ultra-deep JWST/NIRSpec exposures, and that these low-mass systems are systematically less dusty, less actively star-forming, and more metal-poor than the brighter galaxies that dominate current Cosmic Noon samples. If the interpretation is right, the faint Lyα-selected population is a distinct regime of galaxy physics and a closer analog to the galaxies that reionized the universe. The paper further argues that selection based on high [OIII]/Hβ, which works at intermediate metallicity, misses the most metal-poor sources because the ratio turns over and declines at very low oxygen abundance—an effect seen in two galaxies with high Lyα equivalent widths and very low [NII]/Hα upper limits. It also reports the first [O I]-based BPT constraints in such faint galaxies.

What carries the argument

The argument hinges on rest-optical emission-line ratio diagrams—the N2, S2, and O1 BPT planes—that plot O3 ≡ log([O III] λ5007/Hβ) against N2 ≡ log([N II] λ6583/Hα), S2 ≡ log([S II] λλ6717,6731/Hα), or O1 ≡ log([O I] λ6300/Hα). These diagrams separate star-forming galaxies from AGN and, within the star-forming locus, track gas-phase metallicity. The paper interprets its points with a grid of photoionization models computed with a synthetic stellar population at stellar metallicity $Z_* = 0.001$, gas density $n_H = 300$ cm$^{-3}$, ionization parameters log U from −3.0 to −1.5, and nebular metallicities $Z_{\rm neb}/Z_\odot$ from 0.05 to 0.70, plus an empirical N/O–O/H scaling $\log({\rm N/O}) = 1.64\log({\rm O/H}) - 0.86$. The grid predicts that O3 rises as metallicity falls, peaks near 12+log(O/H) ≈ 8.0, and then turns over and declines at even lower oxygen abundances because the [O III] emissivity drops; the paper argues that NB2089 and NB2875 sit on that low-metallicity declining branch, while the stacked and other individual points lie near the peak.

What would settle it

Measure the temperature-sensitive auroral line [O III] λ4363 (or [N II] λ5755) in NB2089 and NB2875 to obtain direct electron-temperature oxygen abundances; if 12+log(O/H) for either galaxy is at or above about 8.0, the turnover interpretation of their low [OIII]/Hβ fails.

Watch

Extended reading notes

Core claim

The paper reports the most sensitive rest-optical spectra of individual faint galaxies at z~2.5 to date: nine low-luminosity systems from the CECILIA program, built from about 29.5 hours of G235M/F170LP and 1 hour of G395M/F290LP NIRSpec observations. It finds star-formation rates of 0.63–5.43 $M_\odot$ yr$^{-1}$, dust reddening $E(B-V)$ between 0.05 and 0.95, and electron densities below ~200 cm$^{-3}$. Emission-line diagnostics place the sample at low [NII]/Hα and high [OIII]/Hβ, corresponding to metallicities 12+log(O/H) ≲ 8.0, and the paper provides the first O1-BPT constraints in such faint high-redshift galaxies. The standout claim is that two Lyα emitters show low [OIII]/Hβ despite very high Lyα equivalent widths (73 and 320 Å) and very low [NII]/Hα upper limits; in the adopted photoionization models this combination is the signature of the O3 turnover at very low metallicity, with 12+log(O/H) ≲ 7.6, and comparison with Te-based samples suggests they are more metal-poor than the most metal-poor galaxy in a z=2–6 comparison sample.

Load-bearing premise

The metallicity interpretation rests on the adopted photoionization model grid and an empirical nitrogen-to-oxygen scaling, and if either does not describe these galaxies, low [OIII]/Hβ would not necessarily mean very low oxygen abundance.

Editorial extensions

If this is right

  • Faint Lyα-selected galaxies at z≈2–3 can be studied galaxy by galaxy, so the scatter in their star-formation rates, dust content, and ionization conditions becomes measurable rather than being averaged away in stacked spectra.
  • The two candidate turnover objects imply that O3-based selection, as used in some high-redshift analog and Lyman-continuum-leaker searches, systematically excludes the lowest-metallicity emitters; surveys should add complementary diagnostics such as N2 and O32.
  • The first O1-BPT constraints are consistent with star formation, and the upper limits leave room for shock-heated gas, which deeper [O I] measurements could confirm or exclude.
  • Because these galaxies have masses below $10^9\,M_\odot$ and star-formation rates of roughly 1–5 $M_\odot$ yr$^{-1}$, they are closer analogs to reionization-era galaxies than the brighter galaxies in existing Cosmic Noon samples.

Reading between the lines

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

  • A direct Te-based abundance measurement of NB2089 or NB2875 would settle whether the O3 turnover is real; if the adopted nitrogen-to-oxygen scaling is wrong for these galaxies, their inferred oxygen abundances could be substantially higher.
  • The apparent correlation between E(B-V) and star-formation rate in the sample may be partly induced by deriving both quantities from the same Hα/Hβ pair; an independent star-formation estimate from the UV continuum or SED fitting would test this.
  • If the turnover interpretation holds, the O32 ratio ([OIII]/[OII]) should rise monotonically for these two galaxies even as O3 falls, providing a check that does not require auroral lines.
  • The two serendipitous detections hint that ultra-deep MSA observations of faint targets will routinely uncover offset companions at similar redshifts, enlarging faint-galaxy samples without additional observing time.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper presents ultra-deep JWST/NIRSpec rest-optical spectroscopy of nine faint, low-mass galaxies at z~2-3 from the CECILIA program, including narrowband-selected LAEs, faint LBGs, and two serendipitous sources. It measures Balmer decrements, dust-corrected H-alpha star formation rates, [S II] electron densities, and emission-line ratios, and places the galaxies on N2-, S2-, and O1-BPT diagrams. The samples are interpreted with Cloudy/BPASS photoionization models and compared to Te-based metallicity samples. The headline claims are that these are the most sensitive rest-optical spectra of individual faint galaxies at this epoch, that the galaxies are low-mass and mostly low-metallicity (12+log(O/H)~8.0), and that two LAEs (NB2089, NB2875) show low [O III]/H-beta with very low [N II]/H-alpha upper limits, consistent with a predicted turnover in O3 at metallicities below ~0.1 Z_sun.

Significance. If the central interpretation holds, the paper provides a valuable anchor for the faint end of the z~2-3 galaxy population: individual, not stacked, measurements of nine extremely faint sources, with Monte Carlo and bootstrap uncertainty estimates, public data through MAST, and first [O I]-BPT constraints in this regime. The comparison of CECILIA-faint galaxies with T16, Sanders+24, and Bian+18 is useful and goes beyond simply reporting line fluxes. However, the most novel and heavily advertised result, the very-low-metallicity turnover in NB2089 and NB2875, rests on upper limits and a model grid that does not exclude an alternative high-ionization branch; the paper's own conclusions overstate the evidence for 12+log(O/H) << 8. The descriptive measurements are careful, but the interpretive claim needs either additional diagnostics or substantial reframing.

major comments (3)
  1. [§4.1, Fig. 9, and §5 item 4] The claim that NB2089 and NB2875 are in the predicted very-low-metallicity turnover regime (Z_neb/Z_sun < 0.1, 12+log(O/H) << 8) is not uniquely supported by the data. For both galaxies, [N II]/H-alpha and [S II]/H-alpha are only 2-sigma upper limits (Table 3), and no O32 or [S II]-based density diagnostic is available. The Cloudy/BPASS grid in Fig. 9 is truncated at log U = -1.5, so the high-ionization branch is not shown. With the very hard Z*=0.001 BPASS spectrum, [O III]/H-beta can also decline at sufficiently high ionization parameter when O++ is further ionized to O3+, while N+ and S+ are suppressed; a galaxy at Z_neb ~ 0.2-0.3 Z_sun could then mimic the observed low O3, low N2, and low S2 without being extremely metal-poor. The abstract and Section 5 item 4 state the very-low-metallicity interpretation as the likely explanation, which overreaches the evidence. I recommend either expanding the model grid to higher log U and showing that the high-U branch is excluded by the limits, obtaining a diagnostic that separates the branches, or softening the claim to explicitly present the high-U degeneracy.
  2. [§2.3 and Table 3] The flux-correction systematics are not propagated into the line fluxes used for the diagnostic diagrams. Section 2.3 states that the flux correction functions vary in absolute scaling by a factor of ~2 at H-alpha and produce ~10% uncertainty in the H-alpha/H-beta ratio, and that these systematics are 'not included in the uncertainties quoted for the individual line flux measurements.' Table 3 confirms that only statistical uncertainties are shown. Since the N2 upper limits for NB2089 and NB2875 (e.g., [N II]/H-alpha < 0.06 and < 0.12) are comparable to or smaller than the plausible wavelength-dependent calibration uncertainty, the central turnover interpretation is sensitive to this systematic. The paper says the systematics are included in derived quantities such as SFR and E(B-V), but it does not specify how; I ask the authors to state the propagation procedure explicitly and to quantify the impact of the flux-correction uncertainty on the BPT positions and limits.
  3. [§3.4.1 and Table 1] Three of the nine sample galaxies (fBM40, fBM47, fC23) do not have their [O III]/H-beta and [N II]/H-alpha ratios measured from the new NIRSpec data, because these lines fall outside the NIRSpec coverage at their redshifts; their E(B-V) and SFR values are also taken from earlier Keck/MOSFIRE measurements (S17). The paper is clear about this in Section 3.1 and 3.4.1, but the abstract's general claim of 'the most sensitive rest-optical spectra of individual faint galaxies at this epoch to date' and the sample framing in the introduction could leave the impression that all nine galaxies have uniform NIRSpec-based rest-optical measurements. I recommend making the heterogeneous origin of the fLBG values explicit in the abstract or in the sample-summary table, and flagging which points in Figures 5-8 are from Keck/MOSFIRE rather than NIRSpec.
minor comments (4)
  1. [§4.2 and Fig. 10] The sentence stating that NB2089 and NB2875 'exhibit lower O3 ratios and lower N2 and S2 limits than even the most metal-poor galaxy in the Sanders et al. (2024) sample' should be reworded: upper limits do not establish that the actual ratios are lower than a detection in another sample, only that the limits are lower. This distinction matters for the claim of a population offset.
  2. [§2.3] The phrase 'the absolute flux calibration for the serendipitous sources is uncertain since their centering in the slit is unknown' is important, but no quantitative estimate of this uncertainty is given for the derived quantities. A brief quantitative statement would help the reader assess the robustness of the reported E(B-V) and SFR values for C31b and BX587b.
  3. [§3.2 and Eq. (1)] The SFR calibration is a single BPASS-based, metal-poor conversion applied to all sources, including the fLBGs and serendipitous sources. The paper correctly notes that this may not apply to more metal-rich populations, but it would be useful to state explicitly what change in the reported median SFR would result from using the Kennicutt (1998) calibration, since the abstract's 'SFRs systematically below continuum-selected galaxies' is calibration-dependent.
  4. [Throughout] There are several small typographical and formatting issues: 'S2-NPT' should be 'S2-BPT' in the Section 4.2 text; 'in in Figure 10' has a duplicated 'in'; and the Table 3 note should clarify whether the quoted [O III]/H-beta values in Figures 6-8 are observed or dust-corrected, given that the table says the fluxes are not dust-corrected.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the CECILIA measurements are independent, the Cloudy/BPASS model grid is not fit to the target data, and the very-low-metallicity turnover claim is supported by the paper's own forward models plus external Te-based comparison samples.

full rationale

The derivation chain is: measured line fluxes -> Balmer decrement E(B-V) -> H-alpha SFRs -> [S II] densities -> BPT ratios -> comparison to photoionization models and Te-based samples. Each step uses independent inputs: an assumed intrinsic Balmer ratio and Cardelli extinction law; an externally calibrated SFR relation from Korhonen Cuestas et al. 2025 (based on BPASS models, not fitted to these nine galaxies); a fixed Te=10^4 K for [S II]; and a Cloudy/BPASS grid with fixed Z*=0.001, n_H=300 cm^-3, log U=-3.0 to -1.5, and Z_neb=0.05-0.70 Zsun. The grid is not tuned to the CECILIA data; the two low-O3 galaxies are simply overplotted and read off the model tracks. The 'predicted turnover' in O3 at low metallicity is reproduced by the paper's own Figure 9 forward models, not merely imported from T16, so the same-group citations are not load-bearing. External anchors also exist: the T16 stack, R24's D40 with 12+log(O/H)=8.07, and Sanders et al. 2024 Te-based galaxies. The paper explicitly acknowledges model dependencies (n_H=100-200 cm^-3 shifts O3 slightly; direct Te-based abundances are still needed; the S17 N/O scaling is adopted) and even warns that the E(B-V)-SFR correlation may partly reflect the common H-alpha/H-beta input. These are ordinary model-assumption and measurement caveats, not definitional circularity, fitted-input-as-prediction, or a self-citation chain that forces the central result.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central quantities rest on the empirical flux correction, the adopted SFR calibration, and the CLOUDY/BPASS model parameters listed above; the metallicity inference is therefore only as good as those inputs.

free parameters (5)
  • Average flux correction function f_corr(λ) = factor ~2 scaling at Hα; ~10% Hα/Hβ shape uncertainty
    Fit to SEDs of brighter CECILIA galaxies and applied to LAEs and serendipitous sources whose own SEDs are unavailable (Section 2.3, Figure 2).
  • SFR calibration constant = 10^-41.68 L_Hα/(erg/s) in M_sun/yr
    Adopted from metal-poor BPASS models at Z*=0.001 (Korhonen Cuestas et al. 2025); all reported SFRs scale with this constant (Section 3.2, Equation 1).
  • CLOUDY grid gas density = n_H = 300 cm^-3
    Fixed in the photoionization grid; the authors note that 100-200 cm^-3 shifts model O3 slightly, so the metallicity contours are density-dependent (Section 4.1).
  • N/O vs O/H scaling = log(N/O)=1.64 log(O/H)-0.86, floor -1.5
    Applied to model [NII] fluxes to build the N2-BPT grid; an empirical relation from Strom et al. 2017, not measured for this sample (Section 4.1).
  • Electron temperature for density estimate = T_e = 10^4 K
    Assumed for the [S II] ratio to n_e conversion, following Rogers et al. 2024; densities are insensitive in the low-density regime (Section 3.3).
assumptions (4)
  • domain assumption Intrinsic Hα/Hβ = 2.89 and the Cardelli et al. (1989) extinction law with R_V = 3.1 apply to these galaxies
    Used to convert observed Balmer decrements into E(B-V) and dust-corrected SFRs (Section 3.1); alternative attenuation laws give similar results according to the text.
  • domain assumption Local-universe BPT classification curves (Kauffmann 2003, Kewley 2001/2006) remain meaningful at z~2.5 after the known high-z offset
    The SF/AGN boundaries are used throughout Section 3.4 to classify the sample; the paper notes high-z galaxies are offset but still use the local curves for reference.
  • domain assumption The serendipitous sources are physically separate galaxies from their primary targets
    C31b and BX587b are identified from line emission at redshift separations greater than 2500 km/s and spatial offsets below 1 arcsecond, but lack continuum detections and mass estimates (Section 2.1).
  • domain assumption The custom background subtraction and bar-shadow correction do not bias emission-line fluxes
    These steps are described by Strom et al. 2023 and Rogers et al. (in prep.) and are not independently validated in this paper (Section 2.1).

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Cite this review

Pith. "Pith review of CECILIA: Ultra-Deep Rest-Optical Spectra of Faint Galaxies at Cosmic Noon." pith.science (2026). https://pith.science/paper/KDPXZPQL

@misc{pith2026250722237,
  author       = {Pith},
  title        = {Pith review of: CECILIA: Ultra-Deep Rest-Optical Spectra of Faint Galaxies at Cosmic Noon},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KDPXZPQL}},
  note         = {Machine review of arXiv:2507.22237}
}
abstract

Intrinsically faint galaxies at $z\sim2-3$ offer critical insights into early galaxy formation, tracing low-metallicity, low-mass systems during Cosmic Noon and serving as analogs to reionization-era galaxies. We present ultra-deep JWST/NIRSpec spectroscopy of nine low-luminosity galaxies ($-17 \lesssim M_{\rm UV} \lesssim -20$, $M_\star \lesssim 10^9\,M_\odot$) at $z\sim2.5$ from the CECILIA program, with $\sim$29.5 hr in G235M/F170LP and 1 hr in G395M/F290LP. Our sample includes four LAEs, three rest-UV color-selected galaxies, and two serendipitous detections -- providing the most sensitive rest-optical spectra of individual faint galaxies at this epoch to date. Balmer-line measurements reveal low SFRs ($0.63 < \mathrm{SFR}/(M_\odot\,\mathrm{yr}^{-1}) < 5.43$) and a broad range of dust reddening ($0 < E(B-V) < 1$), with SFRs systematically below those of continuum-selected galaxies. Electron densities are low ($n_e \lesssim 200$cm$^{-3}$), and emission-line diagnostics indicate low [NII]/H$\alpha$, high [OIII]/H$\beta$, suggesting metallicities $12+\log({\rm O/H})\lesssim8.0$. We also present the first O1-BPT constraints in such faint high-redshift galaxies. Notably, two galaxies show low [OIII]/H$\beta$ despite high Ly$\alpha$ EWs and very low [NII]/H$\alpha$, consistent with the predicted turnover in this ratio at very low metallicities -- highlighting the need for complementary diagnostics (e.g., N2, O32) to identify metal-poor systems. Direct $T_e$-based abundances and expanded samples are needed to further trace metallicity and ionization trends in low-mass galaxies.

Figures

Figures reproduced from arXiv: 2507.22237 by the authors.

Figure 1
Figure 1. The rest-frame NIRSpec spectrum of Q2343-NB2929. Top: 2D spectrogram of the source, with key emission lines denoted by red vertical lines. The panel on its right shows the 1D spatial distribution of the emission lines (orange line) and the gaussian fit used for optimal extraction. Middle: Full spectral range of the G235M spectrum for the source. Dashed lines and pink shaded bands indicate the positions of emission l… view at source ↗
Figure 2
Figure 2. Flux correction functions fcorr(λ) for galaxies in the over￾all CECILIA sample with well-measured SEDs, below-median lu￾minosities, and below-median sizes. The black curves show the individual flux correction functions for these galaxies, while the thick orange curve shows the average flux correction function, con￾structed as the arithmetic mean of the individual fcorr(λ) curves. For fitting the emission lines, we u… view at source ↗
Figure 3
Figure 3. The rest-frame NIRSpec G235M stack spectrum (NB, fLBGs, and serendipitous sources). The purple line represents the 1D extracted spectrum, while the blue line illustrates the Gaussian+linear continuum fit to the emission lines. The gray shaded area indicates the error margin. A horizontal dashed black line at y = 0 marks the zero level. Black dashed vertical lines indicate the positions of key spectral features — mos… view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: The rest-frame NIRSpec stack spectrum for the G395M segment. The spectrum is presented using the same scaling as in [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Log(SFR) versus E(B−V) for the CECILIA-faint sample (pink circles), the T16 KBSS-Lyα stack point (brown circle), and KBSS LBGs from S17 (gray circles). The horizontal dashed pink line indicates the median SFR of the CECILIA-faint sample, while the dashed black line mar…
Figure 6
Figure 6. Figure 6: Left: N2-BPT diagram (Baldwin et al. 1981) with SDSS z ∼ 0 galaxies (gray, contour lines), KBSS LBGs (S17; gray dots with 3 σ detections for every line), a lensed dwarf galaxy (Gburek et al. 2019), stacks of faint LAEs (T16; Matthee et al. 2021; Maseda et al. 2023), st…
Figure 7
Figure 7. Figure 7: S2-BPT (Veilleux & Osterbrock 1987) showing SDSS z ∼ 0 galaxies (gray contour lines), KBSS LBGs from (S17; gray dots with 3σ detections for every line), a stack of high-z galaxies from Sanders et al. (2023), CECILIA faint LAEs (pink circles with 2σ limits), CECILIA D40…
Figure 8
Figure 8. Figure 8: O1-BPT (Veilleux & Osterbrock 1987) showing SDSS z ∼ 0 galaxies (gray contour lines), CECILIA faint LAEs (pink circles with 2σ limits), CECILIA faint LBGs (pink squares), CECILIA D40 (purple circle), Lyman Break galaxies from Cameron et al. (2023) (green diamonds), and…
Figure 9
Figure 9. Figure 9: The N2-BPT predictions from the Cloudy photoionization models are shown, using input spectra from BPASS stellar populations. The pink lines represent tracks of fixed logU, where higher logU values result in higher O3 ratios. The model points are color-coded by O/H as i…
Figure 10
Figure 10. Figure 10: N2 (left) and S2-BPT (right) diagrams. Our data points are compared to 11 galaxies at z ∼ 2–6 from Sanders et al. (2024) (diamond markers) and the stacked points from Bian et al. (2018) (stars), both color-coded by their direct metallicities, as indicated by the color…
Figure 11
Figure 11. Figure 11: N2-BPT diagram with the same features as [PITH_FULL_IMAGE:figures/full_fig_p015_11.png]
Figure 12
Figure 12. Figure 12: The rest-frame NIRSpec spectrum of the serendipitous source Q2343-C31b. Top: 2D spectrogram of the source, with the emission lines marked by red vertical lines and the two white dashed lines indicating the centers of the main and serendipitous sources. Adjacent to the…
Figure 13
Figure 13. Figure 13: The rest-frame NIRSpec spectrum of the serendipitous source Q2343-BX587b. Legend names are the same as in [PITH_FULL_IMAGE:figures/full_fig_p018_13.png]

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Works this paper leans on

97 extracted references · 7 canonical work pages

  1. [1]

    N., Adelman-McCarthy , J

    Abazajian , K. N., Adelman-McCarthy , J. K., Ag \"u eros , M. A., et al. 2009, , 182, 543, 10.1088/0067-0049/182/2/543

    doi:10.1088/0067-0049/182/2/543 2009

  2. [2]

    H., & Martini , P

    Andrews , B. H., & Martini , P. 2013, , 765, 140, 10.1088/0004-637X/765/2/140

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

  3. [3]

    M., & Grevesse , N

    Asplund , M., Amarsi , A. M., & Grevesse , N. 2021, , 653, A141, 10.1051/0004-6361/202140445

    doi:10.1051/0004-6361/202140445 2021

  4. [4]

    A., Phillips , M

    Baldwin , J. A., Phillips , M. M., & Terlevich , R. 1981, , 93, 5, 10.1086/130766

    doi:10.1086/130766 1981

  5. [5]

    J., & Dopita , M

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

    doi:10.3847/1538-4357/aabd74 2018

  6. [6]

    2022 a , msaexp: NIRSpec analyis tools , 0.3.4, Zenodo, Zenodo, 10.5281/zenodo.7299500

    Brammer , G. 2022 a , msaexp: NIRSpec analyis tools , 0.3.4, Zenodo, Zenodo, 10.5281/zenodo.7299500

    doi:10.5281/zenodo.7299500 2022

  7. [7]

    2022 b , msaexp: NIRSpec analyis tools , 0.3.4, Zenodo, Zenodo, 10.5281/zenodo.7313329

    ---. 2022 b , msaexp: NIRSpec analyis tools , 0.3.4, Zenodo, Zenodo, 10.5281/zenodo.7313329

    doi:10.5281/zenodo.7313329 2022

  8. [8]

    2023 a , grizli , 1.8.2, Zenodo, Zenodo, 10.5281/zenodo.7712834

    ---. 2023 a , grizli , 1.8.2, Zenodo, Zenodo, 10.5281/zenodo.7712834

    work page doi:10.5281/zenodo.7712834 2023

Show all 97 references
  1. [9]

    2023 b , grizli , 1.9.11, Zenodo, Zenodo, 10.5281/zenodo.1146904

    ---. 2023 b , grizli , 1.9.11, Zenodo, Zenodo, 10.5281/zenodo.1146904

    2023 doi

  2. [10]

    M., et al

    Brinchmann , J., Charlot , S., Heckman , T. M., et al. 2004, arXiv e-prints, astro, 10.48550/arXiv.astro-ph/0406220

    2004 doi arXiv

  3. [11]

    2023, JWST Calibration Pipeline, 1.12.5, Zenodo, 10.5281/zenodo.10022973

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2023, JWST Calibration Pipeline, 1.12.5, Zenodo, 10.5281/zenodo.10022973

    2023 doi

  4. [12]

    J., Saxena , A., Bunker , A

    Cameron , A. J., Saxena , A., Bunker , A. J., et al. 2023, , 677, A115, 10.1051/0004-6361/202346107

    2023 doi

  5. [13]

    A., Clayton , G

    Cardelli , J. A., Clayton , G. C., & Mathis , J. S. 1989, , 345, 245, 10.1086/167900

    1989 doi

  6. [14]

    C., Cullen , F., McLure , R

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

    2024 doi

  7. [15]

    2025, arXiv e-prints, arXiv:2504.03839, 10.48550/arXiv.2504.03839

    Cataldi , E., Belfiore , F., Curti , M., et al. 2025, arXiv e-prints, arXiv:2504.03839, 10.48550/arXiv.2504.03839

    2025 doi

  8. [16]

    2003, , 115, 763, 10.1086/376392

    Chabrier , G. 2003, , 115, 763, 10.1086/376392

    2003 doi

  9. [17]

    L., et al

    Clarke , L., Shapley , A., Sanders , R. L., et al. 2023, , 957, 81, 10.3847/1538-4357/acfedb

    2023 doi

  10. [18]

    J., Dunlop , J

    Cullen , F., McLure , R. J., Dunlop , J. S., et al. 2019, , 487, 2038, 10.1093/mnras/stz1402

    2019 doi

  11. [19]

    2020, , 495, 1501, 10.1093/mnras/staa1260

    ---. 2020, , 495, 1501, 10.1093/mnras/staa1260

    2020 doi

  12. [20]

    2016, , 585, A51, 10.1051/0004-6361/201527046

    de Barros , S., Vanzella , E., Amor \' n , R., et al. 2016, , 585, A51, 10.1051/0004-6361/201527046

    2016 doi

  13. [21]

    2016, , 828, 71, 10.3847/0004-637X/828/2/71

    Dijkstra , M., Gronke , M., & Venkatesan , A. 2016, , 828, 71, 10.3847/0004-637X/828/2/71

    2016 doi

  14. [22]

    E., Topping , M

    Du , X., Shapley , A. E., Topping , M. W., et al. 2021, , 920, 95, 10.3847/1538-4357/ac1273

    2021 doi

  15. [23]

    J., Porter , R

    Ferland , G. J., Porter , R. L., van Hoof , P. A. M., et al. 2013, , 49, 137. 1302.4485

    2013 arXiv

  16. [24]

    J., Tang , M., Robertson , B

    Fletcher , T. J., Tang , M., Robertson , B. E., et al. 2019, , 878, 87, 10.3847/1538-4357/ab2045

    2019 doi

  17. [25]

    2022, , 926, 80, 10.3847/1538-4357/ac43b8

    Garg , P., Narayanan , D., Byler , N., et al. 2022, , 926, 80, 10.3847/1538-4357/ac43b8

    2022 doi

  18. [26]

    2019, , 887, 168, 10.3847/1538-4357/ab5713

    Gburek , T., Siana , B., Alavi , A., et al. 2019, , 887, 168, 10.3847/1538-4357/ab5713

    2019 doi

  19. [27]

    2011, , 733, 114, 10.1088/0004-637X/733/2/114

    Guaita , L., Acquaviva , V., Padilla , N., et al. 2011, , 733, 114, 10.1088/0004-637X/733/2/114

    2011 doi

  20. [28]

    R., Millman , K

    Harris , C. R., Millman , K. J., van der Walt , S. J., et al. 2020, , 585, 357, 10.1038/s41586-020-2649-2

    2020 doi

  21. [29]

    1986, , 98, 609, 10.1086/131801

    Horne , K. 1986, , 98, 609, 10.1086/131801

    1986 doi

  22. [30]

    2017, , 845, L16, 10.3847/2041-8213/aa8401

    Hu , W., Wang , J., Zheng , Z.-Y., et al. 2017, , 845, L16, 10.3847/2041-8213/aa8401

    2017 doi

  23. [31]

    Hunter , J. D. 2007, Computing in Science and Engineering, 9, 90, 10.1109/MCSE.2007.55

    2007 doi

  24. [32]

    Ilyushin , B. B. 2024, Journal of Engineering Thermophysics, 33, 1, 10.1134/S1810232824010016

    2024 doi

  25. [33]

    I., Orlitov \'a , I., Schaerer , D., et al

    Izotov , Y. I., Orlitov \'a , I., Schaerer , D., et al. 2016, , 529, 178, 10.1038/nature16456

    2016 doi

  26. [34]

    I., Schaerer , D., Worseck , G., et al

    Izotov , Y. I., Schaerer , D., Worseck , G., et al. 2018, , 474, 4514, 10.1093/mnras/stx3115

    2018 doi

  27. [35]

    M., White , S

    Kauffmann , G., Heckman , T. M., White , S. D. M., et al. 2003, , 341, 33, 10.1046/j.1365-8711.2003.06291.x

    2003

  28. [36]

    1998, , 36, 189, 10.1146/annurev.astro.36.1.189

    Kennicutt , Robert C., J. 1998, , 36, 189, 10.1146/annurev.astro.36.1.189

    1998 doi

  29. [37]

    J., Dopita , M

    Kewley , L. J., Dopita , M. A., Sutherland , R. S., Heisler , C. A., & Trevena , J. 2001, , 556, 121, 10.1086/321545

    2001 doi

  30. [38]

    J., Groves , B., Kauffmann , G., & Heckman , T

    Kewley , L. J., Groves , B., Kauffmann , G., & Heckman , T. 2006, , 372, 961, 10.1111/j.1365-2966.2006.10859.x

    2006

  31. [39]

    J., Nicholls , D

    Kewley , L. J., Nicholls , D. C., & Sutherland , R. S. 2019, , 57, 511, 10.1146/annurev-astro-081817-051832

    2019 doi

  32. [40]

    A., Strom , A

    Korhonen Cuestas , N. A., Strom , A. L., Miller , T. B., et al. 2025, arXiv e-prints, arXiv:2503.10800, 10.48550/arXiv.2503.10800

    2025 doi arXiv

  33. [41]

    J., Ilbert , O., et al

    Laigle , C., McCracken , H. J., Ilbert , O., et al. 2016, , 224, 24, 10.3847/0067-0049/224/2/24

    2016 doi

  34. [42]

    R., Ji , X., Belfiore , F., et al

    Law , D. R., Ji , X., Belfiore , F., et al. 2021, , 915, 35, 10.3847/1538-4357/abfe0a

    2021 doi

  35. [43]

    2014, , 52, 415, 10.1146/annurev-astro-081811-125615

    Madau , P., & Dickinson , M. 2014, , 52, 415, 10.1146/annurev-astro-081811-125615

    2014 doi

  36. [44]

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

    Maseda , M. V., Lewis , Z., Matthee , J., et al. 2023, , 956, 11, 10.3847/1538-4357/acf12b

    2023 doi

  37. [45]

    2016, , 828, 18, 10.3847/0004-637X/828/1/18

    Masters , D., Faisst , A., & Capak , P. 2016, , 828, 18, 10.3847/0004-637X/828/1/18

    2016 doi

  38. [46]

    2018, , 479, L34, 10.1093/mnrasl/sly093

    Matthee , J., & Schaye , J. 2018, , 479, L34, 10.1093/mnrasl/sly093

    2018 doi

  39. [47]

    2021, , 505, 1382, 10.1093/mnras/stab1304

    Matthee , J., Sobral , D., Hayes , M., et al. 2021, , 505, 1382, 10.1093/mnras/stab1304

    2021 doi

  40. [48]

    S., Steidel , C

    McLean , I. S., Steidel , C. C., Epps , H. W., et al. 2012, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 8446, Ground-based and Airborne Instrumentation for Astronomy IV, ed. I. S. McLean , S. K. Ramsay , & H. Takami , 84460J, 10.1117/12.924794

    2012 doi

  41. [49]

    2025, , 694, A59, 10.1051/0004-6361/202451695

    Messa , M., Vanzella , E., Loiacono , F., et al. 2025, , 694, A59, 10.1051/0004-6361/202451695

    2025 doi

  42. [50]

    2012, , 745, 12, 10.1088/0004-637X/745/1/12

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

    2012 doi

  43. [51]

    B., Cohen , J

    Oke , J. B., Cohen , J. G., Carr , M., et al. 1995, , 107, 375, 10.1086/133562

    1995 doi

  44. [52]

    E., & Ferland , G

    Osterbrock , D. E., & Ferland , G. J. 2006, Astrophysics of gaseous nebulae and active galactic nuclei

    2006

  45. [53]

    2014, , 797, 11, 10.1088/0004-637X/797/1/11

    \"O stlin , G., Hayes , M., Duval , F., et al. 2014, , 797, 11, 10.1088/0004-637X/797/1/11

    2014 doi

  46. [54]

    J., et al

    Oteo , I., Sobral , D., Ivison , R. J., et al. 2015, , 452, 2018, 10.1093/mnras/stv1284

    2015 doi

  47. [55]

    2011, , 743, 132, 10.1088/0004-637X/743/2/132

    Pentericci , L., Fontana , A., Vanzella , E., et al. 2011, , 743, 132, 10.1088/0004-637X/743/2/132

    2011 doi

  48. [56]

    Rauscher , B. J. 2023, arXiv e-prints, arXiv:2306.03250, 10.48550/arXiv.2306.03250

    2023 doi arXiv

  49. [57]

    A., & Steidel , C

    Reddy , N. A., & Steidel , C. C. 2009, , 692, 778, 10.1088/0004-637X/692/1/778

    2009 doi

  50. [58]

    A., Shapley , A

    Reddy , N. A., Shapley , A. E., Kriek , M., et al. 2020, , 902, 123, 10.3847/1538-4357/abb674

    2020 doi

  51. [59]

    Rogers , N. S. J., Strom , A. L., Rudie , G. C., et al. 2024, , 964, L12, 10.3847/2041-8213/ad2f37

    2024 doi

  52. [60]

    C., Steidel , C

    Rudie , G. C., Steidel , C. C., Trainor , R. F., et al. 2012, , 750, 67, 10.1088/0004-637X/750/1/67

    2012 doi

  53. [61]

    2020, , 892, 48, 10.3847/1538-4357/ab7a91

    Runnholm , A., Hayes , M., Melinder , J., et al. 2020, , 892, 48, 10.3847/1538-4357/ab7a91

    2020 doi

  54. [62]

    J., Mehta , V., et al

    Runnholm , A., Hayes , M. J., Mehta , V., et al. 2025, arXiv e-prints, arXiv:2502.19174, 10.48550/arXiv.2502.19174

    2025 doi arXiv

  55. [63]

    L., Shapley , A

    Sanders , R. L., Shapley , A. E., Topping , M. W., Reddy , N. A., & Brammer , G. B. 2023, , 955, 54, 10.3847/1538-4357/acedad

    2023 doi

  56. [64]

    2024, , 962, 24, 10.3847/1538-4357/ad15fc

    ---. 2024, , 962, 24, 10.3847/1538-4357/ad15fc

    2024 doi

  57. [65]

    L., Shapley , A

    Sanders , R. L., Shapley , A. E., Kriek , M., et al. 2016, , 816, 23, 10.3847/0004-637X/816/1/23

    2016 doi

  58. [66]

    L., Shapley , A

    Sanders , R. L., Shapley , A. E., Reddy , N. A., et al. 2020, , 491, 1427, 10.1093/mnras/stz3032

    2020 doi

  59. [67]

    L., Shapley , A

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

    2021 doi

  60. [68]

    A., Stark , D

    Schenker , M. A., Stark , D. P., Ellis , R. S., et al. 2012, , 744, 179, 10.1088/0004-637X/744/2/179

    2012 doi

  61. [69]

    2023, arXiv e-prints, arXiv:2311.18731, 10.48550/arXiv.2311.18731

    Scholtz , J., Maiolino , R., D'Eugenio , F., et al. 2023, arXiv e-prints, arXiv:2311.18731, 10.48550/arXiv.2311.18731

    2023 doi arXiv

  62. [70]

    E., Reddy , N

    Shapley , A. E., Reddy , N. A., Kriek , M., et al. 2015, , 801, 88, 10.1088/0004-637X/801/2/88

    2015 doi

  63. [71]

    E., Sanders , R

    Shapley , A. E., Sanders , R. L., Shao , P., et al. 2019, , 881, L35, 10.3847/2041-8213/ab385a

    2019 doi

  64. [72]

    E., Sanders , R., Berg , D., et al

    Shapley , A. E., Sanders , R., Berg , D., et al. 2021, The AURORA Survey: First Direct Metallicity Calibrations at High Redshift , JWST Proposal. Cycle 1, ID. \#1914

    2021

  65. [73]

    R., & Eldridge , J

    Stanway , E. R., & Eldridge , J. J. 2018, , 479, 75, 10.1093/mnras/sty1353

    2018 doi

  66. [74]

    P., Ellis , R

    Stark , D. P., Ellis , R. S., Chiu , K., Ouchi , M., & Bunker , A. 2010, , 408, 1628, 10.1111/j.1365-2966.2010.17227.x

    2010

  67. [75]

    P., Ellis , R

    Stark , D. P., Ellis , R. S., & Ouchi , M. 2011, , 728, L2, 10.1088/2041-8205/728/1/L2

    2011 doi

  68. [76]

    C., Adelberger , K

    Steidel , C. C., Adelberger , K. L., Shapley , A. E., et al. 2003, , 592, 728, 10.1086/375772

    2003 doi

  69. [77]

    C., Bogosavljevi \'c , M., Shapley , A

    Steidel , C. C., Bogosavljevi \'c , M., Shapley , A. E., et al. 2018, , 869, 123, 10.3847/1538-4357/aaed28

    2018 doi

  70. [78]

    C., Shapley , A

    Steidel , C. C., Shapley , A. E., Pettini , M., et al. 2004, , 604, 534, 10.1086/381960

    2004 doi

  71. [79]

    C., Strom , A

    Steidel , C. C., Strom , A. L., Pettini , M., et al. 2016, , 826, 159, 10.3847/0004-637X/826/2/159

    2016 doi

  72. [80]

    C., Rudie , G

    Steidel , C. C., Rudie , G. C., Strom , A. L., et al. 2014, , 795, 165, 10.1088/0004-637X/795/2/165

    2014 doi

  73. [81]

    L., Rudie , G

    Strom , A. L., Rudie , G. C., Steidel , C. C., & Trainor , R. F. 2022, , 925, 116, 10.3847/1538-4357/ac38a3

    2022 doi

  74. [82]

    L., Steidel , C

    Strom , A. L., Steidel , C. C., Rudie , G. C., Trainor , R. F., & Pettini , M. 2018, , 868, 117, 10.3847/1538-4357/aae1a5

    2018 doi

  75. [83]

    L., Steidel , C

    Strom , A. L., Steidel , C. C., Rudie , G. C., et al. 2017, , 836, 164, 10.3847/1538-4357/836/2/164

    2017 doi

  76. [84]

    L., Rudie , G

    Strom , A. L., Rudie , G. C., Trainor , R. F., et al. 2023, , 958, L11, 10.3847/2041-8213/ad07dc

    2023 doi

  77. [85]

    S., & Dopita , M

    Sutherland , R. S., & Dopita , M. A. 2017, , 229, 34, 10.3847/1538-4365/aa6541

    2017 doi

  78. [86]

    P., Chevallard , J., & Charlot , S

    Tang , M., Stark , D. P., Chevallard , J., & Charlot , S. 2019, , 489, 2572, 10.1093/mnras/stz2236

    2019 doi

  79. [87]

    W., Shapley , A

    Topping , M. W., Shapley , A. E., Reddy , N. A., et al. 2020, , 499, 1652, 10.1093/mnras/staa2941

    2020 doi

  80. [88]

    F., Lamb , N

    Trainor , R. F., Lamb , N. R., Steidel , C. C., et al. 2025, arXiv e-prints, arXiv:2505.15881, 10.48550/arXiv.2505.15881

    2025 doi arXiv

  81. [89]

    F., Steidel , C

    Trainor , R. F., Steidel , C. C., Strom , A. L., & Rudie , G. C. 2015, , 809, 89, 10.1088/0004-637X/809/1/89

    2015 doi

  82. [90]

    F., Strom , A

    Trainor , R. F., Strom , A. L., Steidel , C. C., & Rudie , G. C. 2016, , 832, 171, 10.3847/0004-637X/832/2/171

    2016 doi

  83. [91]

    F., Strom , A

    Trainor , R. F., Strom , A. L., Steidel , C. C., et al. 2019, , 887, 85, 10.3847/1538-4357/ab4993

    2019 doi

  84. [92]

    A., Heckman , T

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

    2004 doi

  85. [93]

    Veilleux , S., & Osterbrock , D. E. 1987, , 63, 295, 10.1086/191166

    1987 doi

  86. [94]

    2015, , 578, A7, 10.1051/0004-6361/201423978

    Verhamme , A., Orlitov \'a , I., Schaerer , D., & Hayes , M. 2015, , 578, A7, 10.1051/0004-6361/201423978

    2015 doi

  87. [95]

    E., et al

    Virtanen , P., Gommers , R., Oliphant , T. E., et al. 2020, Nature Methods, 17, 261, 10.1038/s41592-019-0686-2

    2020 doi

  88. [96]

    L., Shen , S.-Y., et al

    Wang , L.-L., Luo , A. L., Shen , S.-Y., et al. 2018, , 474, 1873, 10.1093/mnras/stx2798

    2018 doi

  89. [97]

    J., Asada , Y., Iyer , K

    Willott , C. J., Asada , Y., Iyer , K. G., et al. 2025, arXiv e-prints, arXiv:2502.07733, 10.48550/arXiv.2502.07733

    2025 doi arXiv

Pith tools

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