Pith. sign in

REVIEW 3 major objections 7 minor 6 cited by

EMPRESS. X. Spatially resolved mass-metallicity relation in extremely metal-poor galaxies: evidence of episodic star-formation fueled by a metal-poor gas infall

T0 review · 3 major / 7 minor · reviewed 2026-08-11 · deepseek-v4-flash

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

Pith's one-line read Half of extremely metal-poor galaxies show fresh metal-poor cores inside metal-enriched surroundings, evidence that infalling gas drives their star formation in bursts.

desk verdict First resolved mass-metallicity relation for extremely metal-poor galaxies, with a plausible but not yet bulletproof anti-correlation with star-formation surface density. read the letter →

arxiv 2412.04541 v1 pith:RCAWZC7L submitted 2024-12-05 astro-ph.GA

Kimihiko Nakajima , Masami Ouchi , Yuki Isobe , Yi Xu , Shinobu Ozaki , Tohru Nagao , Akio K. Inoue , Michael Rauch
show 42 more authors
Haruka Kusakabe Masato Onodera Moka Nishigaki Yoshiaki Ono Yuma Sugahara Takashi Hattori Yutaka Hirai Takuya Hashimoto Ji Hoon Kim Takashi J. Moriya Hiroto Yanagisawa Shohei Aoyama Seiji Fujimoto Hajime Fukushima Keita Fukushima Yuichi Harikane Shun Hatano Kohei Hayashi Tsuyoshi Ishigaki Masahiro Kawasaki Takashi Kojima Yutaka Komiyama Shuhei Koyama Yusei Koyama Chien-Hsiu Lee Akinori Matsumoto Ken Mawatari Kentaro Motohara Kai Murai Kentaro Nagamine Minami Nakane Tomoki Saito Rin Sasaki Takatoshi Shibuya Akihiro Suzuki Tsutomu T. Takeuchi Hiroya Umeda Masayuki Umemura Kuria Watanabe Kiyoto Yabe Hidenobu Yajima Yechi Zhang
This is my paper · ORCID
classification astro-ph.GA
keywords extremelymetal-poorgalaxiesspatiallyresolvedmetallicitymass-metallicityrelationstarformationsurfacedensitygasinfallepisodicintegralfieldspectroscopylocaldwarf
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

The paper maps gas-phase oxygen abundance pixel by pixel across 24 of the most metal-poor galaxies known, then asks whether those maps match the usual picture of chemically young galaxies. It finds instead that metallicity falls where star-formation surface density rises at fixed stellar-mass surface density, and that in 11 of 22 resolved galaxies the metal-poorest gas sits at the star-forming core while the surrounding gas is more enriched. The authors read this "metal-poor horizontal branch" pattern as evidence that infalling metal-poor gas dilutes galactic centers and triggers episodic star formation. If correct, the resolved mass-metallicity relation reaches $12+\log(\mathrm{O/H})\approx 6.9$–$7.9$, and local extremely metal-poor galaxies split into at least two chemical histories: recent-infall bursts and possibly first-light systems.

What carries the argument

The analysis rests on the R3 metallicity indicator, $R_3=[\mathrm{O\,III}]\,\lambda5007/\mathrm{H}\beta$, applied per spaxel and corrected for ionization using the H$\beta$ equivalent width; this is the tool that turns emission-line maps into metallicity maps in a regime where $[\mathrm{O\,II}]$ and $[\mathrm{O\,III}]\.\lambda4363$ are often undetected. The other central object is the "metal-poor horizontal branch" on the resolved mass-metallicity diagram, a flat or slightly rising sequence of low-metallicity spaxels that reaches the $\Sigma_\star$ and $\Sigma_{\rm SFR}$ peaks and is surrounded by more metal-rich gas; this spatial pattern is the diagnostic through which infall and episodic star formation are inferred.

What would settle it

Measure spaxel-level metallicities in the same galaxies with an independent, direct method, using electron temperatures from $[\mathrm{O\,III}]\.\lambda4363$ where it is detected, and compare the metallicity versus $\Sigma_{\rm SFR}$ trend at fixed $\Sigma_\star$; if the trend and the metal-poor branch disappear under direct metallicities, the central claim is a calibration artifact.

Watch

Extended reading notes

Core claim

Using the R3 strong-line index, $R_3=[\mathrm{O\,III}]\,\lambda5007/\mathrm{H}\beta$, calibrated on extremely metal-poor galaxies with the H$\beta$ equivalent width as an ionization correction, the paper maps metallicities across 9,177 spatial pixels (spaxels) in 24 EMPGs. At fixed local stellar-mass surface density, spaxel metallicity decreases as local star-formation surface density increases, and the scatter of the resolved mass-metallicity relation is largely absorbed by a relation of the form $y=a+b(\mu_\alpha-c)e^{-(\mu_\alpha-c)}$ with $\mu_\alpha=\log\Sigma_\star-\alpha\log\Sigma_{\rm SFR}$ and $\alpha=0.66\pm0.04$. Half of the resolved galaxies show a distinct, nearly horizontal metal-poor branch at the peaks of $\Sigma_\star$ and $\Sigma_{\rm SFR}$, surrounded by gas enriched to about 0.1–0.2 solar metallicity; four galaxies with $Z\lesssim0.03\,Z_\odot$ show only the metal-poor branch. The paper interprets the branch-plus-envelope pattern as recent metal-poor gas infall that dilutes the center and fuels a starburst, consistent with turbulence-dominated kinematics and gas fractions near unity, and identifies the isolated-branch galaxies as likely first-phase chemical evolution systems.

Load-bearing premise

The argument assumes that the metallicity calibration returns unbiased oxygen abundances for every pixel, with no residual hidden dependence on star-formation intensity; if star-forming pixels are systematically read as more metal-poor, the anti-correlation and the flat branch could be artifacts.

Editorial extensions

If this is right

  • The resolved mass-metallicity relation now reaches $12+\log(\mathrm{O/H})\approx6.9$–$7.9$ and $\Sigma_\star\approx10^5$–$10^7\,M_\odot\,\mathrm{kpc}^{-2}$, and its low-mass scatter is nearly closed by $\Sigma_{\rm SFR}$.
  • If infalling metal-poor gas dilutes cores and fuels bursts, many EMPGs are not chemically young; selection on strong Balmer lines preferentially catches post-infall starbursts.
  • The four Category B galaxies with isolated metal-poor clumps at $Z\lesssim0.03\,Z_\odot$ are the best local analogues of early-universe galaxies.
  • Kinematic evidence ($v_{\rm rot}/\sigma<1$, gas fraction $\approx0.9$–$1.0$) supports the infall-triggered starburst picture and implies detectable kinematic discontinuities at branch locations.

Reading between the lines

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

  • A direct test would compare spaxel-level R3 metallicities against auroral-line metallicities in galaxies where $[\mathrm{O\,III}]\.\lambda4363$ is detected: the reported metallicity–$\Sigma_{\rm SFR}$ anti-correlation should persist if it is physical rather than a calibration artifact.
  • The Category A/B split predicts correlated abundance signatures, such as low N/O and high gas fraction concentrated in the metal-poor branch regions; the paper notes that forthcoming N/O work will test this.
  • The same rMZR–$\Sigma_{\rm SFR}$ dependence could be sought in JWST/NIRSpec resolved observations of $z>3$ galaxies, where rapid gas accretion should produce similar cold, low-metallicity cores surrounded by more enriched envelopes.
  • Mapping velocity and metallicity simultaneously in these systems could reveal whether the metal-poor branch gas is actually moving inward, giving a kinematic test of the infall interpretation.
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 / 7 minor

Summary. This paper presents Subaru/FOCAS IFU observations of 24 extremely metal-poor galaxies (EMPGs), mapping gas-phase metallicity (via the R3 index with an EW(Hβ) ionization correction), stellar mass surface density (from 6500–7000 Å continuum), and SFR surface density (from dust-corrected Hα). The authors report that the resolved mass–metallicity relation (rMZR) shows large scatter at low Σ* and that this scatter is strongly correlated with Σ_SFR, with metallicity decreasing as Σ_SFR increases at fixed Σ*. They further identify a 'metal-poor horizontal branch' in 11 of 22 spatially resolved EMPGs, located at the peaks of Σ* and Σ_SFR and surrounded by more metal-enriched gas, which they interpret as evidence for episodic star formation fueled by metal-poor gas infall. Four of the most metal-poor galaxies show only a metal-poor clump, proposed as candidates for a first phase of chemical evolution. The paper extends the rMZR to metallicities 12+log(O/H) ≈ 6.9–7.9 and includes a comparison of the classification with kinematic properties from Isobe et al. (2023).

Significance. If the central results hold, this is the first systematic spatially resolved study of the mass–metallicity relation in the extremely metal-poor regime, a parameter space barely explored by MaNGA/CALIFA and high-redshift IFU surveys. The reported anti-correlation between metallicity and Σ_SFR at fixed Σ*, and the existence of metal-poor horizontal branches, would provide direct observational evidence for metal-poor gas infall driving episodic star formation in low-mass galaxies. The four Category B objects (Z ≲ 0.03 Z☉) are potentially valuable local analogs of early galaxy formation. The paper benefits from careful data reduction, a cross-check of R3 metallicities against direct Te abundances (Figure 1), BPT-based exclusion of evolved AGN, and the use of existing high-resolution kinematics to support the inflow scenario. However, the astrophysical conclusions rest heavily on the assumption that spaxel-level metallicity differences are not dominated by systematic trends in the strong-line calibration with SFR or ionization.

major comments (3)
  1. [§3.1, Figure 4(c), Eq. (2)] The R3 metallicity calibration uses EW(Hβ) as the ionization proxy, while Σ_SFR is independently derived from dust-corrected Hα. Because Hα and Hβ both trace recent star formation, EW(Hβ) and Σ_SFR are strongly correlated. If the R3 calibration retains any residual dependence on ionization or SFR beyond the EW(Hβ) correction, the inferred metallicities will be systematically lower in high-Σ_SFR spaxels, artificially producing or inflating the anti-correlation in Figure 4(c) and the derived α = 0.66 in Equation (2). The validation in Figure 1 uses only integrated central spectra and does not test the per-spaxel calibration trend. The authors should quantify this residual dependence, for example by comparing R3 metallicities to Te-based metallicities in spaxels where [OIII]λ4363 is detected, or by demonstrating that the offset–Σ_SFR correlation persists when the sample is restricted to a narrow EW(Hβ) range or when an alternative ionization correction (e.g., from [OIII]/[OII] where available) is adopted.
  2. [§3.3, Figure 4] The statistical significance of the offset–Σ_SFR correlation and the uncertainties on the fitted parameters are computed by treating the 9,177 spaxels as independent samples. However, spaxels within a single galaxy are spatially correlated, so the effective number of independent measurements is far smaller than the spaxel count. This likely overstates the significance of the trend and underestimates the uncertainties on α in Equation (2). Please re-analyze the correlation and fit using a bootstrap resampled at the galaxy level, or a hierarchical model, and report the significance at the number of independent galaxies (24, or 22 for the resolved subsample).
  3. [§3.5, Figures 7–12] The classification of the 22 resolved EMPGs into Categories A–D, and particularly the identification of the 'metal-poor horizontal branch' in 11 objects, appears to be based on visual inspection of rMZR plots. Since this classification is the basis for the central claim of episodic star formation fueled by metal-poor gas infall, the criteria should be made quantitative and reproducible. Please provide a clear operational definition of the branch (e.g., a minimum number of spaxels forming a flat sequence at low metallicity, a threshold on the metallicity drop near the Σ_SFR peak, or a quantitative measure of the contrast with surrounding spaxels) and demonstrate that the 11/22 classification is robust to reasonable variations of those criteria.
minor comments (7)
  1. [§3.1] The sentence beginning 'Note that we do not apply slit-loss corrections...' would be clearer if the authors stated exactly which lines are used for the R3 metallicity and the continuum, since R3 = [OIII]λ5007/Hβ is a line ratio but EW(Hβ) also requires continuum.
  2. [§2.2] The phrase 'The FOCAS IFU data was reduced' should read 'The FOCAS IFU data were reduced'.
  3. [Figure 4 and related panels] The color bars in several figures (e.g., Figures 7–11) appear to be labeled 'log SFR' rather than 'log Σ_SFR'; please make the notation consistent and ensure the units (M☉ yr⁻¹ kpc⁻²) are always shown.
  4. [§3.3, Eq. (2)] Please state explicitly how the uncertainties on the best-fit parameters a, b, c, and α were computed, and whether the binning of spaxels or the added 0.15 dex systematic uncertainty was included in those uncertainties.
  5. [§3.3, Eq. (1)] The dependent variable y is not explicitly defined in the text; please state that y = 12 + log(O/H) in both Equations (1) and (2).
  6. [§3.4] The classification of metallicity gradients into negative, positive, and flat appears to be qualitative; please specify the threshold (e.g., slope uncertainty) used to assign each category.
  7. [§4.1, Figure 13] The histogram in Figure 13 uses literature central metallicities from Table 1, not the resolved metallicity maps; this is not immediately clear from the caption and should be stated more prominently.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central anti-correlation is measured directly from spaxel data, and the fitted alpha is a descriptive parameter, not an input renamed as a prediction.

full rationale

The paper's central claim — that metallicity decreases with increasing Sigma_SFR at fixed Sigma_star — is established empirically from 9,177 spaxels before any model fit is introduced (Section 3.3, Figure 4a,c). The R3 metallicity calibration is adopted from Nakajima et al. (2022) and validated against direct-Te metallicities in Figure 1; although the calibration uses EW(H-beta) as an ionization proxy and Sigma_SFR is derived from H-alpha, no equation in this paper defines the metallicity in terms of Sigma_SFR or vice versa. A residual calibration bias correlated with EW(H-beta) could in principle mimic or inflate the trend, but that is a systematic-uncertainty concern, not a circular reduction: the R3-Te comparison is an external anchor, and the paper does not fit the calibration to the spaxel data it then interprets. The parameter alpha in Equation (2) is fit to the same binned data, but the paper does not present alpha as a prediction; it compares its value to independent global relations (Andrews & Martini 2013; Sanders et al. 2021; Nakajima et al. 2023), and the qualitative anti-correlation exists independently of the fit. Self-citations to EMPRESS companion papers provide sample selection, stellar masses, and kinematics, but these are published external datasets or calibrations, not the target conclusion. The categorical identification of 'metal-poor horizontal branches' is a description of the measured spaxel distribution, not an output forced by the fitting procedure.

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

The central results rest on an empirical calibration chain: R3 with EW(H-beta) correction, a mass-to-light relation, and an H-alpha SFR conversion. The most fragile piece is the R3-EW(H-beta) calibration, because the independent variable Sigma_SFR is derived from H-alpha and is correlated with the EW(H-beta) used in the metallicity calibration. The visual classification into categories A through D is another non-quantitative input.

free parameters (5)
  • R3-index metallicity calibration coefficients (Nakajima et al. 2022) = not listed in this paper
    All spaxel metallicities come from R3 = [OIII]5007/H-beta with an EW(H-beta) ionization correction, an empirical calibration from a prior paper with overlapping authorship; it includes fitted coefficients and is the main route from line ratios to 12+log(O/H).
  • Mass-to-light ratio for stellar mass from 6500-7000 A continuum = from Kojima et al. 2020, Isobe et al. 2021, Xu et al. 2022
    Sigma_star is computed from a mass-to-optical-luminosity relation obtained by linear fitting SED-based masses and luminosities for EMPGs; this relation is applied to every spaxel without individual SED fits.
  • Equation (2) parameters a, b, c, alpha = a=8.61 +/- 0.06, b=0.004 +/- 0.013, c=11.3 +/- 2.7, alpha=0.66 +/- 0.04
    Fitted to binned EMPG spaxels plus high-metallicity reference data; alpha measures the Sigma_SFR dependence that is central to the paper's interpretation.
  • H-alpha to SFR conversion (Kennicutt 1998a, Chabrier IMF) = standard conversion
    Sigma_SFR is derived from dust-corrected H-alpha flux using a standard conversion from the literature, not re-derived in this paper.
  • Systematic metallicity uncertainty added to binned points = 0.15 dex
    A hand-chosen 0.15 dex systematic is added to binned metallicity uncertainties during the fit to account for calibration systematics.
assumptions (5)
  • domain assumption All spaxels are dominated by star formation, with no significant AGN contribution.
    Used to select the low-metallicity branch of the R3 indicator and to apply star-forming calibrations. Section 3.2 acknowledges that low-metallicity AGNs could overlap with star-forming regions on the BPT diagram.
  • domain assumption The R3-index is single-valued and monotonic over the probed metallicity range after selecting the low-metallicity branch.
    Section 3.1 states that R3 is two-valued around 12+log(O/H)=8.0 and the low branch is chosen based on prior central metallicities. If some spaxels lie on the other branch, the metallicity maps would be incorrect.
  • domain assumption EW(H-beta) is an adequate proxy for the ionization parameter in the metallicity calibration.
    Section 3.1 adopts EW(H-beta) following Nakajima et al. (2022) because [OII] is not detected across the full field, precluding the direct [OIII]/[OII] ratio.
  • domain assumption The mass-to-light ratio for EMPGs assumes constant star formation, age about 5 Myr, dust-free conditions, and a Chabrier IMF.
    Section 3.3 applies the same simple mass-to-light relation to all spaxels rather than fitting individual SEDs, which may be inaccurate in quiescent or mixed-age regions.
  • ad hoc to paper Metallicity differences between spaxels are physical and not dominated by the strong-line calibration's dependence on SFR proxies.
    This is the crux assumption that the Sigma_SFR-metallicity anti-correlation is real rather than a calibration artifact; the paper does not test for this degeneracy.

how reviews work

0 comments
Cite this review

Pith. "Pith review of EMPRESS. X. Spatially resolved mass-metallicity relation in extremely metal-poor galaxies: evidence of episodic star-formation fueled by a metal-poor gas infall." pith.science (2026). https://pith.science/paper/RCAWZC7L

@misc{pith2026241204541,
  author       = {Pith},
  title        = {Pith review of: EMPRESS. X. Spatially resolved mass-metallicity relation in extremely metal-poor galaxies: evidence of episodic star-formation fueled by a metal-poor gas infall},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RCAWZC7L}},
  note         = {Machine review of arXiv:2412.04541}
}
read the original abstract

Using the Subaru/FOCAS IFU capability, we examine the spatially resolved relationships between gas-phase metallicity, stellar mass, and star-formation rate surface densities (Sigma_* and Sigma_SFR, respectively) in extremely metal-poor galaxies (EMPGs) in the local universe. Our analysis includes 24 EMPGs, comprising 9,177 spaxels, which span a unique parameter space of local metallicity (12+log(O/H) = 6.9 to 7.9) and stellar mass surface density (Sigma_* ~ 10^5 to 10^7 Msun/kpc^2), extending beyond the range of existing large integral-field spectroscopic surveys. Through spatially resolved emission line diagnostics based on the [NII] BPT-diagram, we verify the absence of evolved active galactic nuclei in these EMPGs. Our findings reveal that, while the resolved mass-metallicity relation exhibits significant scatter in the low-mass regime, this scatter is closely correlated with local star-formation surface density. Specifically, metallicity decreases as Sigma_SFR increases for a given Sigma_*. Notably, half of the EMPGs show a distinct metal-poor horizontal branch on the resolved mass-metallicity relation. This feature typically appears at the peak clump with the highest Sigma_* and Sigma_SFR and is surrounded by a relatively metal-enriched ambient region. These findings support a scenario in which metal-poor gas infall fuels episodic star formation in EMPGs, consistent with the kinematic properties observed in these systems. In addition, we identify four EMPGs with exceptionally low central metallicities (12+log(O/H) <~ 7.2), which display only a metal-poor clump without a surrounding metal-rich region. This suggests that such ultra-low metallicity EMPGs, at less than a few percent of the solar metallicity, may serve as valuable analogs for galaxies in the early stages of galaxy evolution.

Figures

Figures reproduced from arXiv: 2412.04541 by the authors.

Figure 1
Figure 1. Comparison of metallicities derived from the di￾rect temperature method and the empirical R3-index, us￾ing the integrated spectrum around the central brightest re￾gion of each galaxy. Black circles represent EMPGs with well-determined temperature-based metallicities, where the [O ii]λ3727 line is detected. For EMPGs lacking [O ii]λ3727 (and thus missing a robust measurement of O+/H+), the Te￾based oxygen abundance i… view at source ↗
Figure 2
Figure 2. Gas-phase metallicity maps for the 24 EMPGs. Spaxels with measured metallicities are shown (see Sect. 3.1). Lower metallicities are represented by bluer colors, as indicated in the legend. Contours trace the Hα intensity distribution, outlining the spatial structure of each galaxy. Each panel includes a 100 pc scale bar in the bottom left corner and directional markers for North and East in the top right corner for … view at source ↗
Figure 2
Figure 2. (Continued.) A key limitation of the R3-index is that it exhibits a two-valued behavior, diminishing its diagnostic power around 12+log(O/H) = 8.0. For our objects, we consis￾tently select the low-metallicity solution, following the procedure outlined in Nakajima et al. (2022), as the cen￾tral metallicities are already known to be 12 +log(O/H) < 7.8. This choice is further supported by the low [N ii]/Hα ratios obser… view at source ↗
Figures from the paper (16 more)
Figure 3
Figure 3. Figure 3: shows that all spaxels, including those with upper limits on [N ii], fall below the demarcation curves, confirming that the emission is consistent with star-formation-dominated processes. This result aligns with previous studies of EMPGs based on integrated emission-li…
Figure 4
Figure 4. Figure 4: (a) The relationship between local stellar mass surface density (Σ⋆) and metallicity for the spaxels of EMPGs observed in this study. The spaxels are represented by colored dots, with colors indicating the local SFR surface density (ΣSFR) as shown in the color bar. Lar…
Figure 5
Figure 5. Figure 5: The best-fit relation for the Σ⋆–metallicity–ΣSFR relation (Equation 2). The four colored curves represent the best-fit relations for log ΣSFR values of −2.25 (orange), −1.75 (yellow), −1.25 (green), and −0.75 (blue). Open circles cor￾respond to the average subsample o…
Figure 6
Figure 6. Figure 6: Metallicity gradients for the 24 EMPGs. Metallicities are plotted as blue points as a function of radius along the semi-major axis, with the peak of ΣSFR used as the center. A best-fit linear function (black solid line) is derived by perturbing each blue point within i…
Figure 6
Figure 6. Figure 6: (Continued.) Σ⋆ and ΣSFR within each EMPG. These aspects will be explored in more detail in the next section. 3.5. Zooming in individual EMPG on rMZR In Sect. 3.3, we demonstrate a tight relationship be￾tween metallicity, Σ⋆, and ΣSFR by assembling the spax￾els from th…
Figure 7
Figure 7. Figure 7: An example of an EMPG in Category A, HS0822+3542, is presented on the resolved mass-metallicity relation (main panel). Symbols and color coding follow [PITH_FULL_IMAGE:figures/full_fig_p015_7.png]
Figure 8
Figure 8. Figure 8: Same as [PITH_FULL_IMAGE:figures/full_fig_p016_8.png]
Figure 8
Figure 8. Figure 8: (Continued.) low-mass clumps highlight the dynamic and efficient re￾distribution of metals within these systems. Note that sources in this category might be expected to exhibit positive metallicity gradients across their en￾tire systems. However, not all EMPGs in this …
Figure 9
Figure 9. Figure 9: The rMZR for J2104−0035, color-coded by three distinct regions as indicated in the inset map. This object is classified as Category A based on the patterns observed in the green-colored clump. In contrast, the blue-colored clump displays characteristics similar to Cate…
Figure 10
Figure 10. Figure 10: Same as [PITH_FULL_IMAGE:figures/full_fig_p019_10.png]
Figure 11
Figure 11. Figure 11: Same as [PITH_FULL_IMAGE:figures/full_fig_p020_11.png]
Figure 11
Figure 11. Figure 11: (Continued.) 5 6 7 8 log (M kpc 2 ) 7.0 7.5 8.0 8.5 12+log(O/H) 2 1 log SFR 0.0 2.0 4.0 6.0 8.0 10.0 12.0 (arcsec) 0.0 2.0 4.0 6.0 8.0 10.0 (arcsec) Offset from BB16 on rMZR 1.0 0.5 0.0 0.5 1.0 5 6 7 8 log (M kpc 2 ) 7.0 7.5 8.0 8.5 12+log(O/H) 2 1 log SFR 0.0 2.0 4.0…
Figure 12
Figure 12. Figure 12: Same as [PITH_FULL_IMAGE:figures/full_fig_p021_12.png]
Figure 13
Figure 13. Figure 13: Metallicity distributions of galaxies in the four categories (Sect. 3.5). The metallicities correspond to liter￾ature values ( [PITH_FULL_IMAGE:figures/full_fig_p022_13.png]
Figure 14
Figure 14. Figure 14: The rMZRs for six EMPGs, J1631+4426, IZw18, SBS0355-052E, HS0822+3542, J1044+0353, and J2115−1734 (from top to bottom), with kinematic properties available from high-resolution IFU observations (Isobe et al. 2023). For each galaxy, the left panel shows the rMZR color-…
Figure 14
Figure 14. Figure 14: (Continued.) [PITH_FULL_IMAGE:figures/full_fig_p024_14.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 6 Pith papers

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

  1. 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.

  2. EMPRESS. XV. A New Determination of the Primordial Helium Abundance Suggesting a Moderately Low $Y_\mathrm{P}$ Value

    astro-ph.GA 2025-06 unverdicted novelty 6.0 of 10

    New Subaru spectroscopy of extremely metal-poor galaxies yields a primordial helium abundance Y_P = 0.2402 ± 0.0040, about 1 sigma below most previous estimates and consistent with ACT CMB data.

  3. Exploring the mysterious high-ionization source powering [Ne V] in high-z analog SBS0335-052 E with JWST/MIRI

    astro-ph.GA 2025-02 conditional novelty 6.0 of 10

    JWST MIRI maps of SBS 0335-052 E reveal [Ne V] emission that standard star-formation, X-ray binary, and shock models cannot reproduce, favoring a partial 10^5 solar-mass accreting black hole.

  4. Candidate intermediate-mass black hole discovered in an extremely young low-metallicity cluster in the tadpole galaxy KUG 1138+327

    astro-ph.HE 2025-02 conditional novelty 6.0 of 10

    A 10^40 erg/s X-ray source in KUG 1138+327 is best explained as an accreting intermediate-mass black hole, with a 200 pc radio jet-like counterpart.

  5. Recovering the properties of the interstellar medium through integrated spectroscopy: application to the z~0 ECO volume-limited star-forming galaxy sample

    astro-ph.GA 2024-12 conditional novelty 6.0 of 10

    Integrated optical spectra of 2052 ECO star-forming galaxies, modeled as superpositions of many H II regions, reveal low-excitation gas with average metallicity near 0.3 solar and a mass-metallicity relation consisten...

  6. CROCODILE-DWARF: Assembly and Kinematics of Field Dwarf Galaxies with GADGET4-OSAKA

    astro-ph.GA 2025-10 conditional novelty 5.0 of 10

    In 14 simulated field dwarf galaxies, gas rotational support anti-correlates with the cumulative mass fraction accreted through mergers, indicating that assembly history rather than halo mass alone shapes dwarf galaxy...

Reference graph

Works this paper leans on

95 extracted references · 7 canonical work pages · cited by 6 Pith papers

  1. [1]

    H., & Martini, P

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

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

  2. [2]

    J., & Scott, P

    Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481, doi: 10.1146/annurev.astro.46.060407.145222

    arXiv 2009

  3. [3]

    A., Phillips, M

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

    doi:10.1086/130766 1981

  4. [4]

    K., Heckman, T

    Barrera-Ballesteros, J. K., Heckman, T. M., Zhu, G. B., et al. 2016, MNRAS, 463, 2513, doi: 10.1093/mnras/stw1984

    doi:10.1093/mnras/stw1984 2016

  5. [5]

    2017, MNRAS, 469, 151, doi: 10.1093/mnras/stx789

    Belfiore, F., Maiolino, R., Tremonti, C., et al. 2017, MNRAS, 469, 151, doi: 10.1093/mnras/stx789

    doi:10.1093/mnras/stx789 2017

  6. [6]

    A., Skillman, E

    Berg, D. A., Skillman, E. D., Marble, A. R., et al. 2012, ApJ, 754, 98, doi: 10.1088/0004-637X/754/2/98

    doi:10.1088/0004-637x/754/2/98 2012

  7. [7]

    1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    doi:10.1051/aas:1996164 1996

  8. [8]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682, doi: 10.1086/308692

    doi:10.1086/308692 2000

Show all 95 references
  1. [9]

    2016, MNRAS, 457, 2605, doi: 10.1093/mnras/stw064

    Ceverino, D., S´ anchez Almeida, J., Mu˜ noz Tu˜ n´ on, C., et al. 2016, MNRAS, 457, 2605, doi: 10.1093/mnras/stw064

    2016 doi

  2. [10]

    2003, PASP, 115, 763, doi: 10.1086/376392

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

    2003 doi

  3. [11]

    2016, MNRAS, 462, 1415, doi: 10.1093/mnras/stw1756

    Chevallard, J., & Charlot, S. 2016, MNRAS, 462, 1415, doi: 10.1093/mnras/stw1756

    2016 doi

  4. [12]

    2010, Nature, 467, 811, doi: 10.1038/nature09451

    Cresci, G., Mannucci, F., Maiolino, R., et al. 2010, Nature, 467, 811, doi: 10.1038/nature09451

    2010 doi

  5. [13]

    2017, MNRAS, 465, 1384, doi: 10.1093/mnras/stw2766

    Curti, M., Cresci, G., Mannucci, F., et al. 2017, MNRAS, 465, 1384, doi: 10.1093/mnras/stw2766

    2017 doi

  6. [14]

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

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

    doi

  7. [15]

    2020b, MNRAS, 492, 821, doi: 10.1093/mnras/stz3379

    Curti, M., Maiolino, R., Cirasuolo, M., et al. 2020b, MNRAS, 492, 821, doi: 10.1093/mnras/stz3379

    doi

  8. [16]

    2024, A&A, 684, A75, doi: 10.1051/0004-6361/202346698

    Curti, M., Maiolino, R., Curtis-Lake, E., et al. 2024, A&A, 684, A75, doi: 10.1051/0004-6361/202346698

    2024 doi

  9. [17]

    2014, MNRAS, 444, 2071, doi: 10.1093/mnras/stu1427

    Dekel, A., & Mandelker, N. 2014, MNRAS, 444, 2071, doi: 10.1093/mnras/stu1427

    2014 doi

  10. [18]

    2009, Nature, 457, 451, doi: 10.1038/nature07648 Resolved mass-metallicity relation in EMPGs 27

    Dekel, A., Birnboim, Y., Engel, G., et al. 2009, Nature, 457, 451, doi: 10.1038/nature07648 Resolved mass-metallicity relation in EMPGs 27

    2009 doi

  11. [19]

    2016, ApJ, 820, 131, doi: 10.3847/0004-637X/820/2/131

    El-Badry, K., Wetzel, A., Geha, M., et al. 2016, ApJ, 820, 131, doi: 10.3847/0004-637X/820/2/131

    2016 doi

  12. [20]

    2018, MNRAS, 477, 1536, doi: 10.1093/mnras/sty730

    El-Badry, K., Bradford, J., Quataert, E., et al. 2018, MNRAS, 477, 1536, doi: 10.1093/mnras/sty730

    2018 doi

  13. [21]

    M., Elmegreen, B

    Elmegreen, D. M., Elmegreen, B. G., S´ anchez Almeida, J., et al. 2012, ApJ, 750, 95, doi: 10.1088/0004-637X/750/2/95

    2012 doi

  14. [22]

    M., den Brok, M., et al

    Erroz-Ferrer, S., Carollo, C. M., den Brok, M., et al. 2019, MNRAS, 484, 5009, doi: 10.1093/mnras/stz194

    2019 doi

  15. [24]

    2018, ApJ, 868, 89, doi: 10.3847/1538-4357/aae9f1

    Gao, Y., Wang, E., Kong, X., et al. 2018, ApJ, 868, 89, doi: 10.3847/1538-4357/aae9f1

    2018 doi

  16. [25]

    K., Pilkington, K., Brook, C

    Gibson, B. K., Pilkington, K., Brook, C. B., Stinson, G. S., & Bailin, J. 2013, A&A, 554, A47, doi: 10.1051/0004-6361/201321239

    2013 doi

  17. [26]

    2013, PASA, 30, e056, doi: 10.1017/pasa.2013.34 Gonz´ alez Delgado, R

    Glazebrook, K. 2013, PASA, 30, e056, doi: 10.1017/pasa.2013.34 Gonz´ alez Delgado, R. M., Cid Fernandes, R., Garc ´ ıa-Benito, R., et al. 2014, ApJL, 791, L16, doi: 10.1088/2041-8205/791/1/L16

    2013 doi

  18. [27]

    2023, arXiv e-prints, arXiv:2304.03726, doi: 10.48550/arXiv.2304.03726

    Hatano, S., Ouchi, M., Nakajima, K., et al. 2023, arXiv e-prints, arXiv:2304.03726, doi: 10.48550/arXiv.2304.03726

    2023 doi

  19. [28]

    2024, ApJ, 966, 170, doi: 10.3847/1538-4357/ad335c

    Hatano, S., Ouchi, M., Umeda, H., et al. 2024, ApJ, 966, 170, doi: 10.3847/1538-4357/ad335c

    2024 doi

  20. [29]

    S., Salzer, J

    Hirschauer, A. S., Salzer, J. J., Skillman, E. D., et al. 2016, ApJ, 822, 108, doi: 10.3847/0004-637X/822/2/108

    2016 doi

  21. [30]

    T., Kudritzki, R.-P., Kewley, L

    Ho, I. T., Kudritzki, R.-P., Kewley, L. J., et al. 2015, MNRAS, 448, 2030, doi: 10.1093/mnras/stv067

    2015 doi

  22. [31]

    2021, ApJ, 918, 54, doi: 10.3847/1538-4357/ac05bf

    Isobe, Y., Ouchi, M., Kojima, T., et al. 2021, ApJ, 918, 54, doi: 10.3847/1538-4357/ac05bf

    2021 doi

  23. [32]

    2022, ApJ, 925, 111, doi: 10.3847/1538-4357/ac3509

    Isobe, Y., Ouchi, M., Suzuki, A., et al. 2022, ApJ, 925, 111, doi: 10.3847/1538-4357/ac3509

    2022 doi

  24. [33]

    2023, ApJ, 951, 102, doi: 10.3847/1538-4357/accc87

    Isobe, Y., Ouchi, M., Nakajima, K., et al. 2023, ApJ, 951, 102, doi: 10.3847/1538-4357/accc87

    2023 doi

  25. [34]

    I., Guseva, N

    Izotov, I. I., Guseva, N. G., Lipovetskii, V. A., Kniazev, A. I., & Stepanian, J. A. 1990, Nature, 343, 238, doi: 10.1038/343238a0

    1990 doi

  26. [35]

    I., Guseva, N

    Izotov, Y. I., Guseva, N. G., Fricke, K. J., & Papaderos, P. 2009, A&A, 503, 61, doi: 10.1051/0004-6361/200911965

    2009 doi

  27. [36]

    I., Thuan, T

    Izotov, Y. I., Thuan, T. X., & Guseva, N. G. 2012, A&A, 546, A122, doi: 10.1051/0004-6361/201219733 —. 2019, MNRAS, 483, 5491, doi: 10.1093/mnras/sty3472 —. 2021, MNRAS, 504, 3996, doi: 10.1093/mnras/stab1099

    2012 doi

  28. [37]

    I., Thuan, T

    Izotov, Y. I., Thuan, T. X., Guseva, N. G., & Liss, S. E. 2018, MNRAS, 473, 1956, doi: 10.1093/mnras/stx2478

    2018 doi

  29. [38]

    2010, ApJL, 725, L176, doi: 10.1088/2041-8205/725/2/L176

    Jones, T., Ellis, R., Jullo, E., & Richard, J. 2010, ApJL, 725, L176, doi: 10.1088/2041-8205/725/2/L176

    2010 doi

  30. [39]

    S., Richard, J., & Jullo, E

    Jones, T., Ellis, R. S., Richard, J., & Jullo, E. 2013, ApJ, 765, 48, doi: 10.1088/0004-637X/765/1/48

    2013 doi

  31. [40]

    K., Isobe, Y., et al

    Kashiwagi, Y., Inoue, A. K., Isobe, Y., et al. 2021, PASJ, 73, 1631, doi: 10.1093/pasj/psab100

    2021 doi

  32. [41]

    M., Tremonti, C., et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x

    2003

  33. [42]

    2022, JCAP, 2022, 041, doi: 10.1088/1475-7516/2022/08/041

    Kawasaki, M., & Murai, K. 2022, JCAP, 2022, 041, doi: 10.1088/1475-7516/2022/08/041

    2022 doi

  34. [43]

    2021, ApJL, 908, L54, doi: 10.3847/2041-8213/abe41b

    Ramos-Larios, G. 2021, ApJL, 908, L54, doi: 10.3847/2041-8213/abe41b

    2021 doi

  35. [44]

    M., Guerrero, M

    Kehrig, C., V ´ ılchez, J. M., Guerrero, M. A., et al. 2018, MNRAS, 480, 1081, doi: 10.1093/mnras/sty1920

    2018 doi

  36. [45]

    M., P´ erez-Montero, E., et al

    Kehrig, C., V ´ ılchez, J. M., P´ erez-Montero, E., et al. 2015, ApJL, 801, L28, doi: 10.1088/2041-8205/801/2/L28

    2015 doi

  37. [46]

    1989, ApJ, 344, 685, doi: 10.1086/167834 —

    Kennicutt, Robert C., J. 1989, ApJ, 344, 685, doi: 10.1086/167834 —. 1998a, ARA&A, 36, 189, doi: 10.1146/annurev.astro.36.1.189 —. 1998b, ApJ, 498, 541, doi: 10.1086/305588 Kereˇ s, D., Katz, N., Weinberg, D. H., & Dav´ e, R. 2005, MNRAS, 363, 2, doi: 10.1111/j.1365-2966.2005.09451.x

    1989

  38. [47]

    J., Dopita, M

    Kewley, L. J., Dopita, M. A., Leitherer, C., et al. 2013, ApJ, 774, 100, doi: 10.1088/0004-637X/774/2/100

    2013 doi

  39. [48]

    J., Dopita, M

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

    2001 doi

  40. [49]

    H., & Belfiore, F

    Khoram, A. H., & Belfiore, F. 2024, arXiv e-prints, arXiv:2410.22407, doi: 10.48550/arXiv.2410.22407

    2024 doi arXiv

  41. [50]

    Y., Grebel, E

    Kniazev, A. Y., Grebel, E. K., Hao, L., et al. 2003, ApJL, 593, L73, doi: 10.1086/378259

    2003 doi

  42. [51]

    2020, ApJ, 898, 142, doi: 10.3847/1538-4357/aba047 —

    Kojima, T., Ouchi, M., Rauch, M., et al. 2020, ApJ, 898, 142, doi: 10.3847/1538-4357/aba047 —. 2021, ApJ, 913, 22, doi: 10.3847/1538-4357/abec3d

    2020 doi

  43. [52]

    2000, A&A Rv, 10, 1, doi: 10.1007/s001590000005 Lara-L´ opez, M

    Kunth, D., & ¨Ostlin, G. 2000, A&A Rv, 10, 1, doi: 10.1007/s001590000005 Lara-L´ opez, M. A., Cepa, J., Bongiovanni, A., et al. 2010, A&A, 521, L53, doi: 10.1051/0004-6361/201014803

    2000 doi

  44. [53]

    J., Carollo, C

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

    2013 doi

  45. [54]

    F., Feldmann, R., et al

    Ma, X., Hopkins, P. F., Feldmann, R., et al. 2017, MNRAS, 466, 4780, doi: 10.1093/mnras/stx034

    2017 doi

  46. [55]

    2019, A&A Rv, 27, 3, doi: 10.1007/s00159-018-0112-2

    Maiolino, R., & Mannucci, F. 2019, A&A Rv, 27, 3, doi: 10.1007/s00159-018-0112-2

    2019 doi

  47. [56]

    2008, A&A, 488, 463, doi: 10.1051/0004-6361:200809678 28 Nakajima et al

    Maiolino, R., Nagao, T., Grazian, A., et al. 2008, A&A, 488, 463, doi: 10.1051/0004-6361:200809678 28 Nakajima et al

    2008 doi

  48. [57]

    C., & Ceverino, D

    Bosch, F. C., & Ceverino, D. 2018, ApJ, 861, 148, doi: 10.3847/1538-4357/aaca98

    2018 doi

  49. [58]

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

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

    2010

  50. [59]

    2024, arXiv e-prints, arXiv:2411.08627, doi: 10.48550/arXiv.2411.08627

    Marconcini, C., D’Eugenio, F., Maiolino, R., et al. 2024, arXiv e-prints, arXiv:2411.08627, doi: 10.48550/arXiv.2411.08627

    2024 doi arXiv

  51. [60]

    2022, ApJ, 941, 167, doi: 10.3847/1538-4357/ac9ea1

    Matsumoto, A., Ouchi, M., Nakajima, K., et al. 2022, ApJ, 941, 167, doi: 10.3847/1538-4357/ac9ea1

    2022 doi

  52. [61]

    2024, A&A, 691, A345, doi: 10.1051/0004-6361/202450407 Moll´ a, M., D ´ ıaz,´A

    Mazzolari, G., ¨Ubler, H., Maiolino, R., et al. 2024, A&A, 691, A345, doi: 10.1051/0004-6361/202450407 Moll´ a, M., D ´ ıaz,´A. I., Cavichia, O., et al. 2019, MNRAS, 482, 3071, doi: 10.1093/mnras/sty2877

    2024 doi

  53. [62]

    2013, MNRAS, 435, 2918, doi: 10.1093/mnras/stt1495

    Mott, A., Spitoni, E., & Matteucci, F. 2013, MNRAS, 435, 2918, doi: 10.1093/mnras/stt1495

    2013 doi

  54. [63]

    2011, arXiv e-prints, arXiv:1112.3300

    Moustakas, J., Zaritsky, D., Brown, M., et al. 2011, arXiv e-prints, arXiv:1112.3300. https://arxiv.org/abs/1112.3300

    2011 arXiv

  55. [64]

    2006, A&A, 459, 85, doi: 10.1051/0004-6361:20065216

    Nagao, T., Maiolino, R., & Marconi, A. 2006, A&A, 459, 85, doi: 10.1051/0004-6361:20065216

    2006 doi

  56. [65]

    2022, MNRAS, 513, 5134, doi: 10.1093/mnras/stac1242

    Nakajima, K., & Maiolino, R. 2022, MNRAS, 513, 5134, doi: 10.1093/mnras/stac1242

    2022 doi

  57. [66]

    2023, ApJS, 269, 33, doi: 10.3847/1538-4365/acd556

    Nakajima, K., Ouchi, M., Isobe, Y., et al. 2023, ApJS, 269, 33, doi: 10.3847/1538-4365/acd556

    2023 doi

  58. [67]

    2022, ApJS, 262, 3, doi: 10.3847/1538-4365/ac7710

    Nakajima, K., Ouchi, M., Xu, Y., et al. 2022, ApJS, 262, 3, doi: 10.3847/1538-4365/ac7710

    2022 doi

  59. [68]

    2023, ApJ, 952, 11, doi: 10.3847/1538-4357/accf14

    Nishigaki, M., Ouchi, M., Nakajima, K., et al. 2023, ApJ, 952, 11, doi: 10.3847/1538-4357/accf14

    2023 doi

  60. [69]

    D., Dav´ e, R., Katz, N., Kollmeier, J

    Oppenheimer, B. D., Dav´ e, R., Katz, N., Kollmeier, J. A., & Weinberg, D. H. 2012, MNRAS, 420, 829, doi: 10.1111/j.1365-2966.2011.20096.x

    2012

  61. [70]

    2020, PASJ, 72, 97, doi: 10.1093/pasj/psaa092

    Ozaki, S., Fukushima, M., Iwashita, H., et al. 2020, PASJ, 72, 97, doi: 10.1093/pasj/psaa092

    2020 doi

  62. [71]

    A., Kniazev, A

    Pustilnik, S. A., Kniazev, A. Y., & Pramskij, A. G. 2005, A&A, 443, 91, doi: 10.1051/0004-6361:20053102 Rickards Vaught, R. J., Sandstrom, K. M., & Hunt, L. K. 2021, ApJL, 911, L17, doi: 10.3847/2041-8213/abf09b S´ anchez, S. F., Rosales-Ortega, F. F., Jungwiert, B., et al. 20...

    2005 doi

  63. [72]

    G., & M´ endez-Abreu, J

    Elmegreen, B. G., & M´ endez-Abreu, J. 2013, ApJ, 767, 74, doi: 10.1088/0004-637X/767/1/74 S´ anchez Almeida, J., P´ erez-Montero, E., Morales-Luis, A. B., et al. 2016, ApJ, 819, 110, doi: 10.3847/0004-637X/819/2/110 S´ anchez Almeida, J., Elmegreen, B. G., Mu˜ noz-Tu˜ n´ on, ...

    2013 doi

  64. [73]

    L., Shapley, A

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

    2021 doi

  65. [74]

    Schaerer, D., Fragos, T., & Izotov, Y. I. 2019, A&A, 622, L10, doi: 10.1051/0004-6361/201935005

    2019 doi

  66. [75]

    M., et al

    Schaye, J., Dalla Vecchia, C., Booth, C. M., et al. 2010, MNRAS, 402, 1536, doi: 10.1111/j.1365-2966.2009.16029.x

    2010

  67. [76]

    1959, ApJ, 129, 243, doi: 10.1086/146614

    Schmidt, M. 1959, ApJ, 129, 243, doi: 10.1086/146614

    1959 doi

  68. [77]

    P., Mirocha, J., et al

    Senchyna, P., Stark, D. P., Mirocha, J., et al. 2020, MNRAS, 494, 941, doi: 10.1093/mnras/staa586

    2020 doi

  69. [78]

    D., Salzer, J

    Skillman, E. D., Salzer, J. J., Berg, D. A., et al. 2013, AJ, 146, 3, doi: 10.1088/0004-6256/146/1/3

    2013 doi

  70. [79]

    S., & Dav´ e, R

    Somerville, R. S., & Dav´ e, R. 2015, ARA&A, 53, 51, doi: 10.1146/annurev-astro-082812-140951

    2015 doi

  71. [80]

    T., Lilly, S

    Soto, K. T., Lilly, S. J., Bacon, R., Richard, J., & Conseil, S. 2016, MNRAS, 458, 3210, doi: 10.1093/mnras/stw474

    2016 doi

  72. [81]

    2024, arXiv e-prints, arXiv:2409.09290, doi: 10.48550/arXiv.2409.09290

    Sun, X., Wang, X., Ma, X., et al. 2024, arXiv e-prints, arXiv:2409.09290, doi: 10.48550/arXiv.2409.09290

    2024 doi arXiv

  73. [83]

    X., Guseva, N

    Thuan, T. X., Guseva, N. G., & Izotov, Y. I. 2022, MNRAS, 516, L81, doi: 10.1093/mnrasl/slac095

    2022 doi

  74. [84]

    X., & Izotov, Y

    Thuan, T. X., & Izotov, Y. I. 2005, ApJS, 161, 240, doi: 10.1086/491657

    2005 doi

  75. [85]

    A., Heckman, T

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

    2004 doi

  76. [86]

    2024, arXiv e-prints, arXiv:2403.08431, doi: 10.48550/arXiv.2403.08431

    Tripodi, R., D’Eugenio, F., Maiolino, R., et al. 2024, arXiv e-prints, arXiv:2403.08431, doi: 10.48550/arXiv.2403.08431

    2024 doi arXiv

  77. [87]

    2014, A&A, 563, A58, doi: 10.1051/0004-6361/201322099

    Troncoso, P., Maiolino, R., Sommariva, V., et al. 2014, A&A, 563, A58, doi: 10.1051/0004-6361/201322099

    2014 doi

  78. [88]

    2022, ApJ, 930, 37, doi: 10.3847/1538-4357/ac602d van de Voort, F., & Schaye, J

    Umeda, H., Ouchi, M., Nakajima, K., et al. 2022, ApJ, 930, 37, doi: 10.3847/1538-4357/ac602d van de Voort, F., & Schaye, J. 2012, MNRAS, 423, 2991, doi: 10.1111/j.1365-2966.2012.20949.x

    2022

  79. [89]

    2023, A&A, 678, A173, doi: 10.1051/0004-6361/202346981

    Vanzella, E., Loiacono, F., Bergamini, P., et al. 2023, A&A, 678, A173, doi: 10.1051/0004-6361/202346981

    2023 doi

  80. [90]

    2024, A&A, 691, A19, doi: 10.1051/0004-6361/202449855 Resolved mass-metallicity relation in EMPGs 29

    Venturi, G., Carniani, S., Parlanti, E., et al. 2024, A&A, 691, A19, doi: 10.1051/0004-6361/202449855 Resolved mass-metallicity relation in EMPGs 29

    2024 doi

  81. [91]

    2024, ApJ, 962, 50, doi: 10.3847/1538-4357/ad13ff

    Watanabe, K., Ouchi, M., Nakajima, K., et al. 2024, ApJ, 962, 50, doi: 10.3847/1538-4357/ad13ff

    2024 doi

  82. [92]

    H., Turk, M

    Wise, J. H., Turk, M. J., Norman, M. L., & Abel, T. 2012, ApJ, 745, 50, doi: 10.1088/0004-637X/745/1/50

    2012 doi

  83. [93]

    2016, ApJ, 827, 74, doi: 10.3847/0004-637X/827/1/74

    Wuyts, E., Wisnioski, E., Fossati, M., et al. 2016, ApJ, 827, 74, doi: 10.3847/0004-637X/827/1/74

    2016 doi

  84. [94]

    2022, ApJ, 929, 134, doi: 10.3847/1538-4357/ac5e32

    Xu, Y., Ouchi, M., Rauch, M., et al. 2022, ApJ, 929, 134, doi: 10.3847/1538-4357/ac5e32

    2022 doi

  85. [95]

    2024, ApJ, 961, 49, doi: 10.3847/1538-4357/ad06ab

    Xu, Y., Ouchi, M., Isobe, Y., et al. 2024, ApJ, 961, 49, doi: 10.3847/1538-4357/ad06ab

    2024 doi

  86. [96]

    2023, MNRAS, 525, 4832, doi: 10.1093/mnras/stad2497

    Yajima, H., Abe, M., Fukushima, H., et al. 2023, MNRAS, 525, 4832, doi: 10.1093/mnras/stad2497

    2023 doi

  87. [97]

    2022, ApJ, 926, 57, doi: 10.3847/1538-4357/ac3b55

    Yao, Y., Liu, H., Kong, X., et al. 2022, ApJ, 926, 57, doi: 10.3847/1538-4357/ac3b55

    2022 doi

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.