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REVIEW 4 major objections 5 minor 96 references

Galactic HII regions in LAMOST Medium-Resolution Spectroscopic Survey of Nebulae

T0 review · 4 major / 5 minor · reviewed 2026-08-01 · deepseek-v4-flash

Pith's one-line read This paper claims that a spectroscopically confirmed sample of 255 HII regions in the outer Milky Way shows a steep inner-disk and a shallow outer-disk oxygen abundance gradient, with a global slope of -0.014 ± 0.005 dex/kpc.

desk verdict The catalog is a genuine contribution; the broken oxygen-abundance gradient is likely a calibration artifact that the paper itself contains the evidence for. read the letter →

arxiv 2607.27662 v1 pith:PRVRKT6C submitted 2026-07-30 astro-ph.GA

classification astro-ph.GA
keywords HIIregionsMilkyWaydiskoxygenabundancegradientelectrontemperaturedensitydiffuseionizedgasspectroscopicsurveygalacticchemicalevolution
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 builds a spectroscopic sample of 280 HII regions and candidates in the outer Galaxy, confirms 255 of them as genuine HII regions using optical line ratios, and measures their electron temperatures, electron densities, and oxygen abundances. It claims that oxygen abundance falls steeply in the inner disk (-0.044 ± 0.010 dex/kpc) but only shallowly in the outer disk (-0.016 ± 0.005 dex/kpc), with a global slope of -0.014 ± 0.005 dex/kpc. The paper also reports a rising electron temperature gradient and a falling electron density gradient with galactocentric radius, and finds that the radial gradients vary with azimuth. It further claims that spiral-arm and interarm HII regions show no systematic differences, and that HII regions and diffuse ionized gas occupy heavily overlapping line-ratio space. If correct, this homogeneous sample provides a new statistical constraint on how the outer Milky Way is enriched and ionized, and on chemical evolution models.

What carries the argument

The central object is the sample of 255 spectroscopically confirmed HII regions, built by cross-matching an infrared HII region catalog with medium-resolution optical spectra, stacking spectra in 3-arcmin bins, and subtracting representative diffuse-ionized-gas spectra. The key measurement tools are the line-width-based electron temperature formula, the [SII] line-ratio electron density diagnostic, and the N2Hα strong-line oxygen abundance calibration; these convert the observed line ratios into physical properties, while the line-ratio diagnostic diagram separates HII regions from planetary nebulae and supernova remnants.

What would settle it

Re-derive [NII]/Hα and [SII]/Hα for a handful of HII regions using diffuse-ionized-gas templates built from fibers at several different angular separations; if the recovered line ratios change by more than the quoted uncertainties, the DIG subtraction assumption fails. Alternatively, compare N2Hα-based oxygen abundances with direct Te-based abundances in any region where auroral lines happen to be detectable; a systematic offset larger than about 0.1 dex would indicate calibration bias.

Watch

Extended reading notes

Core claim

The core discovery is a large, homogeneously measured optical sample of 255 spectroscopically confirmed Galactic HII regions spanning 8.16 to 15.36 kpc from the Galactic center, which reveals a two-slope oxygen abundance gradient: a steep inner-disk slope of -0.044 ± 0.010 dex/kpc and a shallow outer-disk slope of -0.016 ± 0.005 dex/kpc, with a global slope of -0.014 ± 0.005 dex/kpc. The paper additionally derives a positive electron temperature gradient (344.6 ± 78.1 K/kpc), a negative electron density gradient (-0.143 ± 0.041 cm^-3/kpc), and finds that these gradients vary with azimuth while no systematic spiral-arm versus interarm differences appear. The authors argue that the different l

Load-bearing premise

The results assume that a representative diffuse-ionized-gas spectrum built from the lowest-[NII] fibers outside each HII region can be subtracted from the observed spectra without bias; if the diffuse emission varies significantly across the region, all line ratios, classifications, abundances, and gradients shift.

Editorial extensions

If this is right

  • A catalog of 255 confirmed outer-Galaxy HII regions, 165 newly classified, is now available with measured electron temperature, electron density, oxygen abundance, and distances, enabling statistical studies of feedback and nebular physics.
  • The oxygen abundance gradient flattens beyond roughly 9.65 kpc, supporting a two-slope or flattened outer-disk enrichment scenario rather than a single linear gradient.
  • The radial trends of [NII]/Hα and [SII]/Hα in HII regions differ from those in diffuse ionized gas, implying that diffuse ionized gas is not simply the sum of leaked HII-region photons and may require additional ionization sources.
  • Spiral-arm versus interarm location does not change the measured HII region physical properties, but the radial gradients vary with azimuth by up to a factor of two, suggesting local or environmental drivers.
  • HII regions and diffuse ionized gas cannot be cleanly separated using the [NII]/Hα–[SII]/Hα diagram alone, so future classifications will need to include radial or other information.

Reading between the lines

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

  • If the faint outer-disk gradient is confirmed with more objects, it would strengthen the case for radial mixing or a flattened star-formation efficiency in the outer disk; this is testable with high-resolution chemodynamical simulations.
  • Because distances mix OB-star parallax distances and kinematic distances, azimuthal gradient variations could be partly contaminated by distance errors; expanding maser parallax measurements would yield a cleaner two-dimensional map.
  • The success of the line-ratio classification suggests that many infrared-selected 'candidate' and 'radio-quiet' sources are genuine HII regions; applying the same method across the full survey footprint could roughly triple the current sample size.
  • The heavy overlap between HII regions and diffuse ionized gas in line-ratio space implies that electron temperature or ionization-parameter diagnostics, rather than line ratios alone, will be needed to separate these phases in future wide-field surveys.
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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

4 major / 5 minor

Summary. The paper constructs a sample of 280 WISE-selected HII regions and candidates in the outer Galaxy (80 < l < 220 deg) and spectroscopically classifies 255 as HII regions using LAMOST MRS-N medium-resolution spectra. For each source it stacks spectra, measures Halpha, [NII]6584, and [SII]6717,6731, and derives electron temperature from line widths, electron density from the [SII] ratio, and oxygen abundance from the Pettini & Pagel (2004) N2Halpha calibration. Distances are obtained from OB-star parallaxes, kinematic methods, and archival values. The main quantitative claims are a Te gradient of 344.5±78 K/kpc, a log-ne gradient of -0.143±0.041 /kpc, and a broken oxygen-abundance gradient with a steep inner slope (-0.044±0.010 dex/kpc) and a shallow outer slope (-0.016±0.005 dex/kpc). The paper also examines azimuthal variations and finds no clear arm/interarm difference. The central sample and line-ratio catalog are potentially valuable, but the oxygen-abundance gradient claim is weakened by a factor-of-three discrepancy between the N2Halpha calibration and the paper's own Te-based abundance gradient, and by the untested DIG subtraction procedure.

Significance. If the sample is reliable, this is one of the largest uniform optical spectroscopic samples of outer-Galaxy HII regions, with 165 newly confirmed sources. The distance-matched, line-ratio-measured catalog would be a useful community resource for studies of star formation, DIG, and Galactic structure. The Te gradient measured from line widths is independent of the abundance calibration and is consistent with prior work, which is a strength. However, the abstract's broken oxygen-abundance gradient is not robust to the choice of metallicity indicator: the same data transformed through the Shaver et al. relation give a single steep slope of -0.051±0.012 dex/kpc, whereas the N2Halpha calibration gives -0.014±0.005 globally. Because the broken gradient is a central claim, the current evidence is not yet sufficient.

major comments (4)
  1. [§2.3, Fig. 2] The DIG subtraction is the foundational assumption of the line-ratio measurements. The paper selects fibers outside each HII region with the lowest [NII] flux to construct a representative DIG spectrum and subtracts it, but provides no test that this template accurately represents diffuse emission within the HII region's angular extent. If DIG emission varies on scales smaller than the region, the resulting [NII]/Halpha and [SII]/Halpha will be biased, which propagates directly into the SMB classification (Fig. 4), the N2Halpha abundance (Eq. 5), and all gradients in Figs. 9-10. I request a validation: e.g., repeat the analysis using alternate DIG templates (different percentile, different radial annuli) and show the distribution of residual line ratios for sources with and without nearby DIG-only fibers. A quantitative statement on how much the gradients shift under this choice is essen
  2. [§5.3, Eqs. (8)-(11)] The reported oxygen-abundance gradient is internally inconsistent with the paper's own Te-based gradient. The N2Halpha global slope is -0.014±0.005 (Eq. 8), while transforming the Te gradient (Eq. 6) through the Shaver et al. (1983) relation (Eq. 10) gives -0.051±0.012 (Eq. 11). The difference is ~3.6 sigma and is a slope difference, not a zero-point offset. The paper's discussion in §5.3 attributes the difference to 'methodology' and an 'overall offset', but does not address the factor-of-three slope discrepancy. Given that the sample spans 12+log(O/H) ~ 8.43-8.73, close to the upper validity limit of the N2Halpha calibration, saturation of the [NII]/Halpha diagnostic is a plausible cause. This directly affects the central abstract claim of a broken gradient: the broken fit (Eqs. 9.1-9.2) may be an artifact of fitting a piecewise model to a saturated calibration. Please quantify the eff
  3. [§4.1, Eq. (2)] The Te measurement rests on the assumption that the Halpha-[NII] line-width difference is entirely thermal and that any non-thermal/instrumental contributions cancel exactly. The text is also inconsistent: §3.2 states that W_Halpha and W_[NII] have been corrected for instrumental broadening, while §4.1 says the observed FWHMs are used without subtracting instrumental broadening. Since the Te gradient (Eq. 6) is subsequently used to derive the alternative oxygen gradient (Eq. 11), the systematic uncertainty in Te from any residual non-thermal broadening, beam smearing, or an imperfect cancellation of the instrumental term needs to be estimated. Please address this explicitly and, if possible, compare a few sources with auroral-line Te estimates to validate the line-width method on this sample.
  4. [§5.4, Fig. 12] The azimuthal sector analysis uses only three sectors (345-360, 0-15, 15-60 deg) with boundaries that appear arbitrary and unnamed. The paper correctly warns that some reversed gradients are due to small numbers, but the 'gradients vary with azimuth' claim is based on these sectors. Please state why these boundaries were chosen, and whether the result survives alternative sector definitions. This is not a load-bearing point for the main catalog, but it is a headline conclusion in the abstract.
minor comments (5)
  1. [§3.1, Eq. (1)] Please clarify whether the skyline OHλ6554 subtraction and flux alignment are performed before or after the DIG subtraction; the current order is not explicit.
  2. [§4.2, Eq. (4)] The density diagnostic is only valid for R < 1.42, but the paper does not state the minimum ratio or the resulting upper density limit. Also, only 94/255 sources have n_e; the gradient in Eq. (7) should be described as applying to this subset, and potential selection effects should be discussed.
  3. [Table 1] Column labels 'N2Ha', 'S2Ha', 'S2N2' are ambiguous; please define in the table notes. Also, 'Mod.' and 'Cls.' should be spelled out at least once.
  4. [§5.3, Eq. (5)] The valid range quoted for the N2Halpha diagnostic is -2.5 < log([NII]/Halpha) < -0.3. The inferred values approach this upper limit; please report the distribution of log([NII]/Halpha) or explicitly state how many sources lie near the boundary.
  5. [§4.4.4] Distances are given for 243 of 255 sources; please specify how the remaining 12 sources are treated in the Rgal analysis and in Figs. 9-10.

Circularity Check

0 steps flagged · score 1.0 of 10

No material circularity: the central abundances, temperatures, densities, and distances come from external calibrations and are not equivalent to the paper's own inputs.

full rationale

I walked the derivation chain from sample selection to the reported gradients. HII-region classification uses the Kniazev et al. (2008) SMB boundaries on the measured [NII]/Halpha and [SII]/Halpha ratios (Section 3.3, Figure 4); these ratios are also used to compute oxygen abundance via the externally calibrated N2Halpha relation (Pettini & Pagel 2004; Eq. 5), but that calibration is an independent external mapping, not a self-defined output. T_e is obtained from Halpha vs [NII] line-width differences (Eq. 2, Reynolds et al. 1977), n_e from the [SII] doublet ratio (Eqs. 3-4, Proxauf et al. 2014), and distances from external astrometric and kinematic catalogues (Bailer-Jones et al. 2021; Wenger et al. 2018; Reid et al. 2019). None of these steps uses the paper's own radial-gradient claims as input. The same-author-group citations (Wen et al. 2025; Zhang et al. 2025; Ma et al. 2026) provide data-reduction recipes and a DIG comparison sample; the relevant recipe is spelled out explicitly (Eq. 1 and Section 2.3), so the reliance is procedural rather than an import of an unverified uniqueness theorem or ansatz. The internal inconsistency between the N2Halpha-based O/H slope (-0.014+-0.005, Eq. 8) and the Shaver-transformed T_e-based slope (-0.051+-0.012, Eq. 11) is a real diagnostic-dependence concern for the scientific interpretation, but it is not circularity: the two slopes are independent estimates, and the paper does not derive one from the other by construction. Verdict: no significant circularity; score 1 only to acknowledge non-structural same-group method citations.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

No new physical entities are proposed. The free parameters are analysis choices (segmented-break radius, azimuthal sector boundaries). The load-bearing axioms are external calibration/assumptions: the N2Halpha abundance calibration, the line-width Te method, the DIG subtraction procedure, the rotation-curve-based kinematic distances, and the SMB classification boundaries. The O/H gradient is therefore only as secure as the PP04 calibration, and the radial gradients are only as secure as the adopted distances and Rgal.

free parameters (2)
  • Inner/outer oxygen-abundance break radius = Rgal = 9.65 kpc
    The segmented linear fit of oxygen abundance changes slope at Rgal=9.65 kpc (Section 5.3, Eqs. 9.1-9.2). This break is chosen without independent justification or uncertainty, and it directly controls the reported steep inner (-0.044) and shallow outer (-0.016) slopes.
  • Azimuthal sector boundaries = 345-360, 0-15, 15-60 degrees
    The azimuthal gradient analysis (Figure 12) divides the sample into three hand-defined sectors. The factor-of-~2 variation in gradient slope depends on this arbitrary partition and on sparse data, as the authors themselves note when a reversed slope is attributed to small sample size.
assumptions (5)
  • domain assumption The Pettini & Pagel (2004) N2Halpha calibration, 12+log(O/H)=8.90+0.57 log([NII]/Halpha), is valid and unsaturated across the metallicity range of the sample.
    Invoked in Eq. (5) to convert every measured [NII]/Halpha ratio into an oxygen abundance. This diagnostic is known to flatten at high metallicity, which would bias the outer-disk gradient; the paper does not test or discuss saturation.
  • domain assumption The Reynolds et al. line-width formula Te=23.5 W_Halpha^2 (1 - W_NII^2/W_Halpha^2) gives unbiased electron temperatures under the assumption that non-thermal broadening is identical for Halpha and [NII].
    Used in Eq. (2) with observed FWHMs and no instrumental-broadening subtraction. Differential turbulence, double-Gaussian structure, and the fact that 28 sources are rejected because W_Halpha < W_NII all indicate the assumption is fragile, yet no systematic error is assigned.
  • ad hoc to paper Subtracting a representative DIG spectrum built from the lowest-[NII] fibers outside each source removes diffuse emission without altering the intrinsic HII region line ratios.
    Described in Section 2.3. The paper provides no test of DIG spatial variability across HII region angular scales; all line ratios, classifications, and derived abundances inherit this subtraction.
  • domain assumption The kinematic distances computed with the Wenger et al. (2018) tool and the Reid et al. (2019) rotation curve are reliable for the adopted sources.
    Kinematic distances are used for 92 of 243 assigned distances (Section 4.4.2). The paper acknowledges that non-circular motions in the Perseus Arm can distort distances and thus the Rgal values on which all gradients are computed.
  • domain assumption The SMB/Kniazev emission-line diagnostic boundaries correctly separate HII regions from PNe and SNRs in these LAMOST spectra.
    The classification of 255 HII regions and the rejection of 11 PNe and 14 SNR candidates rests on the empirical SMB diagram and the Kniazev et al. (2008) criteria (Section 3.3).

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Cite this review

Pith. "Pith review of Galactic HII regions in LAMOST Medium-Resolution Spectroscopic Survey of Nebulae." pith.science (2026). https://pith.science/paper/PRVRKT6C

@misc{pith2026260727662,
  author       = {Pith},
  title        = {Pith review of: Galactic HII regions in LAMOST Medium-Resolution Spectroscopic Survey of Nebulae},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PRVRKT6C}},
  note         = {Machine review of arXiv:2607.27662}
}
abstract

Based on LAMOST Medium-Resolution Spectroscopic Survey of Nebulae (MRS-N) data and WISE Galactic HII region catalog, we construct a sample of 280 Galactic HII regions and candidates in the Outer Galaxy (80$^{\circ}$ $\lesssim$ l $\lesssim$ 220$^{\circ}$). Using MRS-N optical spectra, we measure four emission lines (H$\alpha$, [NII]$\lambda$6584, [SII]$\lambda\lambda$6717,6731) and use line-ratios to spectroscopically confirm 255 HII regions, including 90 previously "Known" HII regions and 165 newly classified ones. We measure their $T_{\rm e}$, $n_{\rm e}$ and oxygen abundance, and determine distances via associated OB stars and the kinematic method. The sample spans $R_{\rm gal}$ from 8.16 to 15.36 kpc, enabling investigation of radial gradients in physical properties. We find [NII]/H$\alpha$ and [SII]/H$\alpha$ decrease with increasing $R_{\rm gal}$, while [SII]/[NII] remains nearly flat; these trends are quite different from diffuse ionized gas (DIG). We derive the $T_{\rm e}$ gradient of 344.530 $\pm$ 78.083 K kpc$^{-1}$, and the $\log n_{\rm e}$ gradient of -0.143 $\pm$ 0.041 cm$^{-3}$ kpc$^{-1}$. Oxygen abundance shows a steep slope of -0.044 $\pm$ 0.010 dex kpc$^{-1}$ in the inner disk and a shallow slope of -0.016 $\pm$ 0.005 dex kpc$^{-1}$ in the outer disk, with a global slope of -0.014 $\pm$ 0.005 dex kpc$^{-1}$. We also examine the two-dimensional distributions of $T_{\rm e}$, $n_{\rm e}$, and oxygen abundance, and find the gradients vary with azimuth. There is no obvious difference between spiral arm and interarm regions, and no trend appears along individual arms. From [NII]/H$\alpha$-[SII]$\lambda$6717/H$\alpha$ diagram, HII regions have a S$^+$/S ratio (0.32), lower than DIG (0.43); however, heavy overlap prevents clear separation from this diagram alone.

Figures

Figures reproduced from arXiv: 2607.27662 by the authors.

Figure 1
Figure 1. Spatial distribution of MRS-N observations and our sample constructed in Section 2.3. Gray dots denote all MRS-N fibers without S/N cuts. Circles of different colors represent sources of different catalogs: red, green, blue, and yellow indicate Known (‘K’), Group (‘G’), Candidate (‘C’), and radio-Quiet (‘Q’), respectively. uniform density is necessary. The spatial resolution (de￾fined by the median fiber-to-fiber di… view at source ↗
Figure 2
Figure 2. Example of the sky/DIG subtraction procedure. The observed spectrum before sky/DIG subtraction is shown in the upper panel, while the sky/DIG-subtracted spectrum is shown in the lower panel. The main emission lines are marked with red dashed vertical lines. The flux is given in units of ADU. spectra in recent years (Wang et al. 2018; Zhang et al. 2020; Lu et al. 2022). Here, we employ the classification criteria pro… view at source ↗
Figure 3
Figure 3. Fiber distributions and spectral processes for two example H II regions. Example 1: Panels (a1) ∼ (d1) show the spatial distributions of fibers in the radius range, overlaid with 3′ × 3 ′ grids. The colorbars indicate the flux values of Hα, [N II]λ6584, [S II]λ6717, and [S II]λ6731, respectively. Panels (a2) ∼ (d2) show the processes of stacking and Gaussian fitting. Each gray line represents one individual spectrum… view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: SMB diagnostic diagram. The black dashed line is the criterion to separate H II regions and PNe, whose mathematical expression is shown in the lower right corner. The gray shaded area belongs to SNRs. H II regions, PNe, and SNRs are denoted by black crosses, red dots, …
Figure 5
Figure 5. Figure 5: Histograms of parameters. The valid counts are shown in the upper right corner. The red dashed vertical lines indicate the median values, with their corresponding uncertainties also provided [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Comparison of dOB, dkin,lamost with dwise. The two panels share the same x-axis (dwise), with the y-axes corresponding to dOB and dkin,lamost, respectively. Magenta dots denote maser parallax distances (dmaser,wise), and black dots denote kinematic distances (dkin,wise…
Figure 7
Figure 7. Figure 7: Comparison of VLSR,lamost with VLSR,wise. VLSR,lamost values are obtained from our LAMOST spectra in Section 3.2. VLSR,wise values are provided by HIIcat V2.3. Error bars are shown in purple. Open circles represent the outliers from panel (b) of [PITH_FULL_IMAGE:figur…
Figure 8
Figure 8. Figure 8: Face-on view of H II regions in the Galactic plane. Galactic coordinates and the locations of the spiral arms are overlaid. Magenta squares, yellow dots, and cyan triangles indicate “maser/WISE”, “OBstar”, and “kin/lamost”, respectively. The background is an artistic i…
Figure 9
Figure 9. Figure 9: Radial gradients of line ratios as functions of Rgal. From top to bottom, the panels show [N II]/Hα, [S II]/Hα, and [S II]/[N II], respectively. Gray crosses denote H II regions, and black squares represent the median values of binned H II regions with scatter shown as…
Figure 10
Figure 10. Figure 10: Radial gradients of physical properties as functions of Rgal. The panels from top to bottom are Te, ne and oxygen abundance (in units of 12+log(O/H)), respectively. Gray crosses denote H II regions, and black squares represent the median values of binned H II regions …
Figure 11
Figure 11. Figure 11: 2D distributions from face-on view of the Milky Way. The colors of points indicate the values of Te, ne, and 12 + log(O/H). The color bars on the right show the range of each parameter. In three panels, the number of H II regions is 227, 94, and 246, respectively [PI…
Figure 12
Figure 12. Figure 12: Radial gradients of Te, ne, and 12+log(O/H) at different azimuths. The panels from top to bottom are 345◦ < Az < 360◦ , 0◦ < Az < 15◦ , and 15◦ < Az < 60◦ . Gray crosses denote H II regions, and black squares represent the median values of binned H II regions with err…
Figure 13
Figure 13. Figure 13: Distribution of HII regions and DIG on the [N II]/Hα vs. [S II]λ6717/Hα diagram. H II regions are shown in gray contours. Blue contours represent DIG from Wen et al. (2025). The brown dash-dotted lines are the line emissivity models from Madsen et al. (2006), correspo…

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Works this paper leans on

96 extracted references · 26 canonical work pages

  1. [1]

    1979, A&A, 78, 200

    Alloin, D., Collin-Souffrin, S., Joly, M., & Vigroux, L. 1979, A&A, 78, 200

  2. [2]

    D., Bania, T

    Anderson, L. D., Bania, T. M., Balser, D. S., et al. 2014, ApJS, 212, 1, doi: 10.1088/0067-0049/212/1/1 Arellano-C´ ordova, K. Z., Esteban, C., Garc ´ ıa-Rojas, J., & M´ endez-Delgado, J. E. 2020, MNRAS, 496, 1051, doi: 10.1093/mnras/staa1523 —. 2021, MNRAS, 502, 225, doi: 10.1093/mnras/staa3903

  3. [3]

    2021, AJ, 161, 147, doi: 10.3847/1538-3881/abd806

    Demleitner, M., & Andrae, R. 2021, AJ, 161, 147, doi: 10.3847/1538-3881/abd806

  4. [4]

    A., Phillips, M

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

  5. [5]

    S., Rood, R

    Balser, D. S., Rood, R. T., Bania, T. M., & Anderson, L. D. 2011, ApJ, 738, 27, doi: 10.1088/0004-637X/738/1/27

  6. [6]

    S., Wenger, T

    Balser, D. S., Wenger, T. V., Anderson, L. D., & Bania, T. M. 2015, ApJ, 806, 199, doi: 10.1088/0004-637X/806/2/199 19

  7. [7]

    T., Longmore, S

    Barnes, A. T., Longmore, S. N., Dale, J. E., et al. 2020, MNRAS, 498, 4906, doi: 10.1093/mnras/staa2719

  8. [8]

    2016, MNRAS, 461, 3111, doi: 10.1093/mnras/stw1234

    Belfiore, F., Maiolino, R., Maraston, C., et al. 2016, MNRAS, 461, 3111, doi: 10.1093/mnras/stw1234

Show all 96 references
  1. [10]

    2025, A&A, 695, A144, doi: 10.1051/0004-6361/202450356

    Bordiu, C., Riggi, S., Bufano, F., et al. 2025, A&A, 695, A144, doi: 10.1051/0004-6361/202450356

  2. [11]

    C., & Ryan-Weber, E

    Bresolin, F., Kennicutt, R. C., & Ryan-Weber, E. 2012, ApJ, 750, 122, doi: 10.1088/0004-637X/750/2/122

  3. [12]

    Burton, W. B. 1971, A&A, 10, 76

  4. [13]

    L., & Haynes, R

    Caswell, J. L., & Haynes, R. F. 1987, A&A, 171, 261 Cedr´ es, B., & Cepa, J. 2002, A&A, 391, 809, doi: 10.1051/0004-6361:20020588

  5. [14]

    A., & Rand, R

    Collins, J. A., & Rand, R. J. 2001, ApJ, 551, 57, doi: 10.1086/320072

  6. [15]

    A., Mieda, E., et al

    Cosens, M., Wright, S. A., Mieda, E., et al. 2018, ApJ, 869, 11, doi: 10.3847/1538-4357/aaeb8f

  7. [16]

    A., Murray, N., et al

    Cosens, M., Wright, S. A., Murray, N., et al. 2022, ApJ, 929, 74, doi: 10.3847/1538-4357/ac52f3

  8. [17]

    2012, Research in Astronomy and Astrophysics, 12, 1197, doi: 10.1088/1674-4527/12/9/003

    Cui, X.-Q., Zhao, Y.-H., Chu, Y.-Q., et al. 2012, Research in Astronomy and Astrophysics, 12, 1197, doi: 10.1088/1674-4527/12/9/003

  9. [18]

    2000, MNRAS, 311, 329, doi: 10.1046/j.1365-8711.2000.03030.x Di Matteo, P., Haywood, M., Combes, F., Semelin, B., &

    Deharveng, L., Pe˜ na, M., Caplan, J., & Costero, R. 2000, MNRAS, 311, 329, doi: 10.1046/j.1365-8711.2000.03030.x Di Matteo, P., Haywood, M., Combes, F., Semelin, B., &

  10. [19]

    Snaith, O. N. 2013, A&A, 553, A102, doi: 10.1051/0004-6361/201220539

  11. [20]

    A., Kewley, L

    Dopita, M. A., Kewley, L. J., Sutherland, R. S., & Nicholls, D. C. 2016, Ap&SS, 361, 61, doi: 10.1007/s10509-016-2657-8

  12. [21]

    Esteban, C., Carigi, L., Copetti, M. V. F., et al. 2013, MNRAS, 433, 382, doi: 10.1093/mnras/stt730

  13. [22]

    2017, MNRAS, 471, 987, doi: 10.1093/mnras/stx1624 Fern´ andez-Mart ´ ın, A., P´ erez-Montero, E., V ´ ılchez, J

    Cipriano, L. 2017, MNRAS, 471, 987, doi: 10.1093/mnras/stx1624 Fern´ andez-Mart ´ ın, A., P´ erez-Montero, E., V ´ ılchez, J. M., &

  14. [23]

    2017, A&A, 597, A84, doi: 10.1051/0004-6361/201628423

    Mampaso, A. 2017, A&A, 597, A84, doi: 10.1051/0004-6361/201628423

  15. [24]

    1991, ApJ, 366, 107, doi: 10.1086/169544

    Fich, M., & Silkey, M. 1991, ApJ, 366, 107, doi: 10.1086/169544

  16. [26]

    Foster, T., & Brunt, C. M. 2015, AJ, 150, 147, doi: 10.1088/0004-6256/150/5/147

  17. [27]

    M., & Georgelin, Y

    Georgelin, Y. M., & Georgelin, Y. P. 1976, A&A, 49, 57 G´ omez, G. C. 2006, AJ, 132, 2376, doi: 10.1086/508412

  18. [28]

    M., Reynolds, R

    Haffner, L. M., Reynolds, R. J., Tufte, S. L., et al. 2003, ApJS, 149, 405, doi: 10.1086/378850

  19. [29]

    M., Dettmar, R.-J., Beckman, J

    Haffner, L. M., Dettmar, R.-J., Beckman, J. E., et al. 2009, Reviews of Modern Physics, 81, 969, doi: 10.1103/RevModPhys.81.969

  20. [30]

    E., et al

    Ho, I.-T., Seibert, M., Meidt, S. E., et al. 2017, ApJ, 846, 39, doi: 10.3847/1538-4357/aa8460

  21. [31]

    E., Kudritzki, R.-P., et al

    Ho, I.-T., Meidt, S. E., Kudritzki, R.-P., et al. 2018, A&A, 618, A64, doi: 10.1051/0004-6361/201833262

  22. [32]

    G., Han, J

    Hou, L. G., Han, J. L., & Shi, W. B. 2009, A&A, 499, 473, doi: 10.1051/0004-6361/200809692

  23. [33]

    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

  24. [34]

    C., & Chu, Y.-H

    Kennicutt, Jr., R. C., & Chu, Y.-H. 1988, AJ, 95, 720, doi: 10.1086/114669

  25. [35]

    J., & Dopita, M

    Kewley, L. J., & Dopita, M. A. 2002, ApJS, 142, 35, doi: 10.1086/341326

  26. [36]

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

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

  27. [37]

    J., Nicholls, D

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

  28. [38]

    R., Brunthaler, A., et al

    Khan, S., Rugel, M. R., Brunthaler, A., et al. 2024, A&A, 689, A81, doi: 10.1051/0004-6361/202449390

  29. [39]

    Y., Pustilnik, S

    Kniazev, A. Y., Pustilnik, S. A., & Zucker, D. B. 2008, MNRAS, 384, 1045, doi: 10.1111/j.1365-2966.2007.12540.x

  30. [40]

    A., & Kewley, L

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

  31. [41]

    A., Schinnerer, E., et al

    Kreckel, K., Blanc, G. A., Schinnerer, E., et al. 2016, ApJ, 827, 103, doi: 10.3847/0004-637X/827/2/103

  32. [42]

    2019, MNRAS, 485, 367, doi: 10.1093/mnras/stz366

    Kumari, N., Maiolino, R., Belfiore, F., & Curti, M. 2019, MNRAS, 485, 367, doi: 10.1093/mnras/stz366

  33. [43]

    2012, MNRAS, 420, 2280, doi: 10.1111/j.1365-2966.2011.20227.x

    Lagrois, D., Joncas, G., & Drissen, L. 2012, MNRAS, 420, 2280, doi: 10.1111/j.1365-2966.2011.20227.x

  34. [44]

    Larson, R. B. 1981, MNRAS, 194, 809, doi: 10.1093/mnras/194.4.809

  35. [45]

    2005, The Interstellar Medium, doi: 10.1007/b137959

    Lequeux, J. 2005, The Interstellar Medium, doi: 10.1007/b137959

  36. [46]

    2021, ApJ, 917, 72, doi: 10.3847/1538-4357/ac0973

    Li, N., Li, C., Mo, H., et al. 2021, ApJ, 917, 72, doi: 10.3847/1538-4357/ac0973

  37. [47]

    2020, arXiv e-prints, arXiv:2005.07210, doi: 10.48550/arXiv.2005.07210

    Liu, C., Fu, J., Shi, J., et al. 2020, arXiv e-prints, arXiv:2005.07210, doi: 10.48550/arXiv.2005.07210

  38. [48]

    2019, ApJS, 241, 32, doi: 10.3847/1538-4365/ab0a0d

    Liu, Z., Cui, W., Liu, C., et al. 2019, ApJS, 241, 32, doi: 10.3847/1538-4365/ab0a0d

  39. [49]

    A., Krumholz, M

    Lopez, L. A., Krumholz, M. R., Bolatto, A. D., Prochaska, J. X., & Ramirez-Ruiz, E. 2011, ApJ, 731, 91, doi: 10.1088/0004-637X/731/2/91

  40. [50]

    A., Krumholz, M

    Lopez, L. A., Krumholz, M. R., Bolatto, A. D., et al. 2014, ApJ, 795, 121, doi: 10.1088/0004-637X/795/2/121 20

  41. [51]

    2022, Research in Astronomy and Astrophysics, 22, 065015, doi: 10.1088/1674-4527/ac693b

    Lu, Y., Luo, A.-L., Wang, L.-L., et al. 2022, Research in Astronomy and Astrophysics, 22, 065015, doi: 10.1088/1674-4527/ac693b

  42. [52]

    2015, Research in Astronomy and Astrophysics, 15, 1095, doi: 10.1088/1674-4527/15/8/002

    Luo, A.-L., Zhao, Y.-H., Zhao, G., et al. 2015, Research in Astronomy and Astrophysics, 15, 1095, doi: 10.1088/1674-4527/15/8/002

  43. [53]

    2026, Research in Astronomy and Astrophysics, 26, 055010, doi: 10.1088/1674-4527/ae45fb

    Ma, L., Zhao, Y., Zhang, W., et al. 2026, Research in Astronomy and Astrophysics, 26, 055010, doi: 10.1088/1674-4527/ae45fb

  44. [54]

    J., Reynolds, R

    Madsen, G. J., Reynolds, R. J., & Haffner, L. M. 2006, ApJ, 652, 401, doi: 10.1086/508441

  45. [55]

    Magrini, L., Perinotto, M., Corradi, R. L. M., & Mampaso, A. 2003, A&A, 400, 511, doi: 10.1051/0004-6361:20030031

  46. [56]

    A., Rosales-Ortega, F

    Marino, R. A., Rosales-Ortega, F. F., S´ anchez, S. F., et al. 2013, A&A, 559, A114, doi: 10.1051/0004-6361/201321956 M´ endez-Delgado, J. E., Amayo, A., Arellano-C´ ordova, K. Z., et al. 2022, MNRAS, 510, 4436, doi: 10.1093/mnras/stab3782 Mois´ es, A. P., Damineli, A., Figuer...

  47. [57]

    A., Williams, G

    Mutale, M., Thompson, M. A., Williams, G. M., et al. 2026, MNRAS, 546, staf1849, doi: 10.1093/mnras/staf1849

  48. [58]

    Pagel, B. E. J., Edmunds, M. G., Blackwell, D. E., Chun, M. S., & Smith, G. 1979, MNRAS, 189, 95, doi: 10.1093/mnras/189.1.95

  49. [59]

    Parker, Q. A. 2022, Frontiers in Astronomy and Space Sciences, 9, 895287, doi: 10.3389/fspas.2022.895287

  50. [60]

    L., Urquhart, J

    Patel, A. L., Urquhart, J. S., Yang, A. Y., et al. 2024, MNRAS, 533, 2005, doi: 10.1093/mnras/stae1910 —. 2023, MNRAS, 524, 4384, doi: 10.1093/mnras/stad2143 —. 2025, MNRAS, 538, 2267, doi: 10.1093/mnras/staf450

  51. [61]

    K., Thompson, T

    Pathak, D., Leroy, A. K., Thompson, T. A., et al. 2025, ApJ, 982, 140, doi: 10.3847/1538-4357/adb484 P´ erez-Montero, E. 2017, PASP, 129, 043001, doi: 10.1088/1538-3873/aa5abb

  52. [62]

    Pettini, M., & Pagel, B. E. J. 2004, MNRAS, 348, L59, doi: 10.1111/j.1365-2966.2004.07591.x

  53. [63]

    2014, A&A, 561, A10, doi: 10.1051/0004-6361/201322581

    Proxauf, B., ¨Ottl, S., & Kimeswenger, S. 2014, A&A, 561, A10, doi: 10.1051/0004-6361/201322581

  54. [64]

    Maciel, W. J. 2006, ApJ, 653, 1226, doi: 10.1086/508803

  55. [65]

    J., Menten, K

    Reid, M. J., Menten, K. M., Zheng, X. W., et al. 2009, ApJ, 700, 137, doi: 10.1088/0004-637X/700/1/137

  56. [66]

    J., Menten, K

    Reid, M. J., Menten, K. M., Brunthaler, A., et al. 2014, ApJ, 783, 130, doi: 10.1088/0004-637X/783/2/130 —. 2019, ApJ, 885, 131, doi: 10.3847/1538-4357/ab4a11

  57. [67]

    2021, Research in Astronomy and Astrophysics, 21, 051, doi: 10.1088/1674-4527/21/3/51

    Ren, J.-J., Wu, H., Wu, C.-J., et al. 2021, Research in Astronomy and Astrophysics, 21, 051, doi: 10.1088/1674-4527/21/3/51

  58. [68]

    Reynolds, R. J. 1991, in IAU Symposium, Vol. 144, The Interstellar Disk-Halo Connection in Galaxies, ed. H. Bloemen, 67

  59. [69]

    J., Roesler, F

    Reynolds, R. J., Roesler, F. L., & Scherb, F. 1977, ApJ, 211, 115, doi: 10.1086/154908

  60. [70]

    Riesgo-Tirado, H., & L´ opez, J. A. 2002, in Revista Mexicana de Astronomia y Astrofisica Conference Series, Vol. 12, Revista Mexicana de Astronomia y Astrofisica Conference Series, ed. W. J. Henney, J. Franco, & M. Martos, 174–174

  61. [71]

    L., Fich, M., Bell, G

    Rudolph, A. L., Fich, M., Bell, G. R., et al. 2006, ApJS, 162, 346, doi: 10.1086/498869

  62. [72]

    2003a, A&A, 397, 133, doi: 10.1051/0004-6361:20021504 —

    Russeil, D. 2003a, A&A, 397, 133, doi: 10.1051/0004-6361:20021504 —. 2003b, A&A, 397, 133, doi: 10.1051/0004-6361:20021504

  63. [73]

    1977, A&A, 60, 147 S´ anchez-Menguiano, L., S´ anchez, S

    Sabbadin, F., Minello, S., & Bianchini, A. 1977, A&A, 60, 147 S´ anchez-Menguiano, L., S´ anchez, S. F., P´ erez, I., et al. 2020, MNRAS, 492, 4149, doi: 10.1093/mnras/staa088 S´ anchez-Menguiano, L., S´ anchez, S. F., Kawata, D., et al. 2016, ApJL, 830, L40, doi: 10.3847/2041...

  64. [74]

    A., McGee, R

    Shaver, P. A., McGee, R. X., Newton, L. M., Danks, A. C., & Pottasch, S. R. 1983, MNRAS, 204, 53, doi: 10.1093/mnras/204.1.53

  65. [75]

    J., Hou, L

    Shen, X. J., Hou, L. G., Liu, H. L., & Gao, X. Y. 2025, A&A, 696, A67, doi: 10.1051/0004-6361/202452712

  66. [76]

    Shi, F., Kong, X., Li, C., & Cheng, F. Z. 2005, A&A, 437, 849, doi: 10.1051/0004-6361:20041945

  67. [77]

    2019, A&A, 623, A60, doi: 10.1051/0004-6361/201834188

    Grisoni, V. 2019, A&A, 623, A60, doi: 10.1051/0004-6361/201834188

  68. [78]

    2004, ChJA&A, 4, 1, doi: 10.1088/1009-9271/4/1/1 van Zee, L., Salzer, J

    Su, D.-Q., & Cui, X.-Q. 2004, ChJA&A, 4, 1, doi: 10.1088/1009-9271/4/1/1 van Zee, L., Salzer, J. J., Haynes, M. P., O’Donoghue, A. A., & Balonek, T. J. 1998, AJ, 116, 2805, doi: 10.1086/300647

  69. [79]

    M., & Esteban, C

    Vilchez, J. M., & Esteban, C. 1996, MNRAS, 280, 720, doi: 10.1093/mnras/280.3.720

  70. [80]

    2018, PASP, 130, 114301, doi: 10.1088/1538-3873/aadf22

    Wang, L.-L., Luo, A.-L., Hou, W., et al. 2018, PASP, 130, 114301, doi: 10.1088/1538-3873/aadf22

  71. [81]

    2023, ApJS, 267, 39, doi: 10.3847/1538-4365/acd6f9

    Wang, M., Wu, J., Jiang, B., & Zhang, Y. 2023, ApJS, 267, 39, doi: 10.3847/1538-4365/acd6f9

  72. [82]

    1996, ApOpt, 35, 5155, doi: 10.1364/AO.35.005155 21

    Wang, S.-G., Su, D.-Q., Chu, Y.-Q., Cui, X., & Wang, Y.-N. 1996, ApOpt, 35, 5155, doi: 10.1364/AO.35.005155 21

  73. [83]

    2025, AJ, 169, 95, doi: 10.3847/1538-3881/ad9b8e

    Wen, S., Zhang, W., Ma, L., et al. 2025, AJ, 169, 95, doi: 10.3847/1538-3881/ad9b8e

  74. [84]

    V., Balser, D

    Wenger, T. V., Balser, D. S., Anderson, L. D., & Bania, T. M. 2018, ApJ, 856, 52, doi: 10.3847/1538-4357/aaaec8 —. 2019, ApJ, 887, 114, doi: 10.3847/1538-4357/ab53d3

  75. [85]

    V., Dawson, J

    Wenger, T. V., Dawson, J. R., Dickey, J. M., et al. 2021, ApJS, 254, 36, doi: 10.3847/1538-4365/abf4d4

  76. [86]

    2012, MNRAS, 422, 3339, doi: 10.1111/j.1365-2966.2012.20850.x

    Wisnioski, E., Glazebrook, K., Blake, C., et al. 2012, MNRAS, 422, 3339, doi: 10.1111/j.1365-2966.2012.20850.x

  77. [87]

    2021, Research in Astronomy and Astrophysics, 21, 096, doi: 10.1088/1674-4527/21/4/96 —

    Wu, C.-J., Wu, H., Zhang, W., et al. 2021, Research in Astronomy and Astrophysics, 21, 096, doi: 10.1088/1674-4527/21/4/96 —. 2022, Research in Astronomy and Astrophysics, 22, 075015, doi: 10.1088/1674-4527/ac7387

  78. [88]

    G., Bian, S

    Xu, Y., Hou, L. G., Bian, S. B., et al. 2021, A&A, 645, L8, doi: 10.1051/0004-6361/202040103

  79. [89]

    Y., Thompson, M

    Yang, A. Y., Thompson, M. A., Tian, W. W., et al. 2019, MNRAS, 482, 2681, doi: 10.1093/mnras/sty2811

  80. [90]

    Y., Urquhart, J

    Yang, A. Y., Urquhart, J. S., Thompson, M. A., et al. 2021, A&A, 645, A110, doi: 10.1051/0004-6361/202038608

  81. [91]

    Y., Dzib, S

    Yang, A. Y., Dzib, S. A., Urquhart, J. S., et al. 2023, A&A, 680, A92, doi: 10.1051/0004-6361/202347563

  82. [92]

    Y., Thompson, M

    Yang, A. Y., Thompson, M. A., Urquhart, J. S., et al. 2025, A&A, 694, A26, doi: 10.1051/0004-6361/202452078

  83. [93]

    2021, PASP, 133, 124501, doi: 10.1088/1538-3873/ac193a

    Yang, Y., & Jiang, B. 2021, PASP, 133, 124501, doi: 10.1088/1538-3873/ac193a

  84. [94]

    2017, MNRAS, 466, 3217, doi: 10.1093/mnras/stw3308

    Zhang, K., Yan, R., Bundy, K., et al. 2017, MNRAS, 466, 3217, doi: 10.1093/mnras/stw3308

  85. [95]

    2020, Research in Astronomy and Astrophysics, 20, 097, doi: 10.1088/1674-4527/20/6/97

    Zhang, M., Chen, B.-Q., Huo, Z.-Y., et al. 2020, Research in Astronomy and Astrophysics, 20, 097, doi: 10.1088/1674-4527/20/6/97

  86. [96]

    2021, Research in Astronomy and Astrophysics, 21, 280, doi: 10.1088/1674-4527/21/11/280

    Zhang, W., Wu, H., Wu, C.-J., et al. 2021, Research in Astronomy and Astrophysics, 21, 280, doi: 10.1088/1674-4527/21/11/280

  87. [97]

    2025, AJ, 169, 257, doi: 10.3847/1538-3881/adbf8f

    Zhang, W., Zhao, Y., Ma, L., et al. 2025, AJ, 169, 257, doi: 10.3847/1538-3881/adbf8f

  88. [98]

    2012, Research in Astronomy and Astrophysics, 12, 723, doi: 10.1088/1674-4527/12/7/002

    Zhao, G., Zhao, Y.-H., Chu, Y.-Q., Jing, Y.-P., & Deng, L.-C. 2012, Research in Astronomy and Astrophysics, 12, 723, doi: 10.1088/1674-4527/12/7/002

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