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Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) II: Photoionization Model View of Ionized to Neutral Gas Emission

T0 review · 2 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read A five-parameter power law captures the ratios of far-infrared fine-structure lines, leaving three independent ISM quantities.

desk verdict A genuinely useful FIR-line diagnostic paper whose power-law scalings are solid but conditional on the dust-radiation-pressure-free grid; deserves peer review with requested revisions. read the letter →

arxiv 2507.11829 v1 pith:UEO6IDAN submitted 2025-07-16 astro-ph.GA

Bo Peng , Amit Vishwas , Cody Lamarche , Gordon Stacey , Catie Ball , Christopher Rooney , Thomas Nikola , Carl Ferkinhoff This is my paper · ORCID
classification astro-ph.GA
keywords fine-structurelinesphotoionizationmodelsinterstellarmediumHIIregionsphotodissociationchemicalabundancesionizationparameterradiationfieldhardness
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 claims that the familiar far-infrared fine-structure line ratios of galaxies can be captured by a five-parameter power-law fit over a large photoionization grid, and that the fitted exponents show which physical quantity each ratio actually traces. It runs 20,446 converged plane-parallel models that vary ionization parameter $U$, electron density $n_e$, N/O, O/H, and radiation hardness $Q_1/Q_0$, then fits every diagnostic ratio to a product of power laws in those five quantities. The resulting exponent table identifies [N iii]/[O iii]88 as an almost linear N/O tracer, [O iii]88/[C ii] as a tracer of $U_1=U\times(Q_1/Q_0)$, and [Ne iii]/[Ne ii] as a steep function of $Q_1/Q_0$. If this is right, it explains the tight empirical correlations observed in galaxies as parameter marginalization, and it sets an information limit: FIR fine-structure lines determine three physical parameters ($U_1$, $n_e$, N/O), with MIR and optical lines needed for the rest.

What carries the argument

The load-bearing object is the five-parameter power-law fit of Eq. 1, applied to every diagnosed line ratio over the photoionization grid; the fitted exponent of each parameter is the claim about what that ratio traces. The grid itself is the supporting mechanism, computed with the Cloudy photoionization code as a plane-parallel, constant-gas-pressure slab including dust, PAHs, CMB, X-rays, and cosmic rays, with radiation hardness defined as $Q_1/Q_0$ (helium-ionizing to total ionizing photon luminosity ratio). Segmented fits above and below a break in ratios such as [O iii]88/[C ii] handle the shift of the dominant oxygen and nitrogen ionization stage, and the residual scatter quoted for each fit measures how completely the power law closes over the grid.

What would settle it

Measure [N iii]/[O iii]88 and [O iii]88/[C ii] in galaxies with independently known N/O, $n_e$, and ionizing spectral hardness; the model predicts an almost exactly linear slope for the N/O diagnostic (index 1.0) and $U_1$ scaling near index 1.2 for [O iii]88/[C ii], so a slope outside the reported scatter would falsify the mapping. A rerun of the grid with dust radiation pressure included is the second check: if the Table 1 exponents shift by more than their residual scatter, the diagnostics inherit the neglected-pressure structure.

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Extended reading notes

Core claim

The central discovery is a quantitative mapping from observable line ratios to physical conditions. Using a grid of 20,446 photoionization models computed in a single plane-parallel, constant-pressure structure that contains both the H ii region and the PDR, the authors fit each ratio as a product of power laws (Eq. 1) in $U$, $n_e$, N/O, O/H, and $Q_1/Q_0$. The fits show that high-to-low ionization ratios such as [O iii]88/[C ii] and [N iii]/[N ii] are governed by the composite helium-ionization parameter $U_1=U(Q_1/Q_0)$, that [Ne iii]/[Ne ii] scales about as $U(Q_1/Q_0)^3$ and therefore breaks the $U$--$Q_1/Q_0$ degeneracy, and that [N iii]/[O iii]88 and [N ii]/[C ii] track N/O nearly linearly. The observed tightness of galaxy relations is attributed to marginalization: real galaxies sit near $n_e\approx 50$ cm$^{-3}$ and follow an O/H--$U$--$Q_1/Q_0$ correlation, so the apparent one-parameter drivers are not single physical variables. The authors conclude that the eight standard FIR lines contain about three independent pieces of information, fixing only $U_1$, $n_e$, and N/O.

Load-bearing premise

Everything rests on treating a single plane-parallel, constant-gas-pressure slab, run to $A_V=100$ mag or $T_e=10$ K with dust radiation pressure turned off, as an adequate stand-in for the luminosity-averaged, galaxy-integrated line emission; the paper itself shows that including dust radiation pressure cuts the slab depth by more than half, lowers $U$ by 0.5 dex, and caps $\log U$ near $-2$.

Editorial extensions

If this is right

  • A galaxy's FIR fine-structure spectrum carries at most three independent ISM numbers: $U_1$, $n_e$, and N/O, fixed respectively by [O iii]88/[C ii] (or [N iii]/[N ii]122), by [N ii]122/205 or [O i]145/[C ii], and by [N iii]/[O iii]88 or [N ii]/[C ii].
  • The steep $Q_1/Q_0$ dependence of [Ne iii]/[Ne ii] provides the practical lever for separating ionization parameter from radiation hardness, which oxygen ratios alone cannot do.
  • Tight observed correlations among FIR ratios reflect small real variation in $n_e$ (near 50 cm$^{-3}$) plus an intrinsic O/H--$U$--$Q_1/Q_0$ correlation, rather than a single dominant physical parameter.
  • MIR and optical lines remain necessary for recovering $Q_1/Q_0$, O/H, and electron temperature separately, so FIR-only studies of the ISM hit a fundamental information barrier.

Reading between the lines

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

  • If the three-parameter saturation is correct, adding more FIR lines beyond the standard set will not break the $U_1$--$n_e$--N/O degeneracy; the next gains come from joint FIR/optical/MIR fitting or from resolved maps that separate H ii regions from PDRs.
  • The dust-radiation-pressure cap, $U$ below roughly $0.005(D/G)^{-1/2}(Q_1/Q_0)^{1/3}$, suggests a testable explanation for why compact dusty H ii regions and some high-redshift systems appear to sit at lower effective $U$ than local dwarf galaxies.
  • The model's persistent over-prediction of [O i]63/[O i]145 relative to the observed value near 10 points to missing neutral-gas physics or unresolved [O i]63 self-absorption; resolved observations of individual star-forming regions could locate the discrepancy.
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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

2 major / 5 minor

Summary. This paper presents the second installment of the FLAMES series, using a large grid of Cloudy photoionization models (20,446 converged models) to interpret far- and mid-infrared fine-structure line ratios from both ionized and neutral gas phases in a unified plane-parallel, constant-gas-pressure framework. The authors fit multi-dimensional power laws (Eq. 1) to line ratios as functions of ionization parameter U, electron density ne, abundance ratios N/O and O/H, and radiation hardness Q1/Q0. They report fitted indices (Table 1), identify segmented (broken) power-law behavior in high-to-low ionization ratios, compare model predictions to the empirical relations from Paper I, and argue that FIR FSLs effectively constrain only three independent physical parameters: U1 = U × (Q1/Q0), ne, and N/O. The paper also discusses parameter marginalization, the degeneracy between U and Q1/Q0, and the role of dust radiation pressure, explicitly acknowledging that the default grid neglects radiation pressure.

Significance. If the fitted power laws are robust, this paper provides a valuable quantitative framework for interpreting FIR FSL observations and for understanding why galaxy-integrated line ratios often form tight empirical sequences. The public model catalog (Appendix A, Table 2) and the explicit, candid discussion of model failures (e.g., the [O i]63/145 ratio, residual scatter above 0.5 dex, and the radiation-pressure issue) are strengths. The paper is also careful to distinguish parameter degeneracies and marginalization effects, which is a useful contribution to the field. The main uncertainty is whether the quantitative indices in Table 1 survive a more complete treatment of dust radiation pressure; the authors themselves show in Sec. 4.3.1 that this modeling choice alters the gas structure substantially.

major comments (2)
  1. [Sec. 4.3.1 and Table 1] The central quantitative claim—that FIR FSL ratios are captured by the Eq. (1) power law with the indices in Table 1, and that they constrain only U1, ne, and N/O—is derived from the default grid, which assumes constant gas pressure and neglects dust radiation pressure (Sec. 2.1). In Sec. 4.3.1, the authors show that including radiation pressure at constant total pressure reduces model depth by more than half, lowers output log U by ~0.5 dex, raises the neutral gas column by ~0.5 dex, and caps output log U below about -2 at high D/G (Fig. 15 and 16). This is a structural change large enough to affect the least-squares exponents in Table 1, yet the paper does not report how those exponents would change under the radiation-pressure-inclusive grid, even for the parameter range where that grid is not deemed unphysical. The quoted indices (e.g., [N iii]/[O iii] with N/O index 1.00, and [Ne iii]/[Ne ii] scaling as U × (Q1/Q0)^3) are therefore presented without a robustness check. I ask the authors to either (a) fit Eq. (1) on a radiation-pressure-inclusive grid (or on a sub-grid restricted to parameter combinations where the unphysical density jumps are mild) and show that the Table 1 indices remain consistent within some tolerance, or (b) explicitly qualify, in the abstract and summary, that all fitted indices and the three-parameter constraint are conditional on the gas-pressure-only assumption. As written, the headline 'tracer' interpretation has not been shown to survive this modeling choice.
  2. [Table 1] No uncertainties are reported for the fitted power-law indices x1–x5 (only the residual scatter Δ is given). Since the paper's interpretation relies on distinguishing e.g. an index of 1.00 for [N iii]/[O iii] vs N/O from an index of 0.97 or 1.05, standard errors or bootstrap confidence intervals are needed to assess whether differences between indices are significant. Please add uncertainties to each fitted index and describe the least-squares weighting (equal weights per model? any outlier rejection?).
minor comments (5)
  1. [Table 1] In the [O iii]88/[C ii] row, the residual scatter column reads '0.38.0.16,0.24', which appears to be a typo for '0.38,0.16,0.24'. Please correct.
  2. [Sec. 2.1] The sentence 'Dust is included in both neutral and ionized gas, as its presence ... is importance in the heating' contains a grammatical error; 'is importance' should be 'is important'.
  3. [Sec. 3.1 and Table 1] The segmented-fit thresholds (e.g., [O iii]88/[C ii] >1/<1, [N iii]/[N ii]122 >5/<5, [N iii]/[N ii]205 >10/<10) appear arbitrary. The paper should state how these thresholds were chosen and whether the break points were fit as free parameters or fixed a priori; otherwise, the reported residual scatter for the segmented fits may be optimistically biased.
  4. [Fig. 10 caption] The caption contains typos: 'bsfc- e (middel)' should likely be '(b)–(e) (middle)'.
  5. [Sec. 4.3.1] The paper uses the scaling from the radiation-pressure-inclusive models (Fig. 16, U < 0.005 (D/G)^-1/2 (Q1/Q0)^1/3) to argue for the O/H–U–Q1/Q0 correlation, while simultaneously stating that such models produce unphysical structures and 'should not be used for normalization'. Please clarify the logical status of this scaling relation: if the models are unphysical, why are their scaling relations considered informative?

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the Table 1 exponents are least-squares fits to an independently computed Cloudy grid, and Paper I is used as an external observational comparison rather than as a premise of the model.

full rationale

The paper's central quantitative claim is the five-parameter power-law fit in Eq. (1). Each exponent in Table 1 is a least-squares slope fitted to line ratios that are outputs of Cloudy C23.01 calculations; the independent variables (log U, log ne, log(N/O), log(O/H), log(Q1/Q0)) are either explicit grid inputs (N/O, O/H), stellar-SED-derived quantities (Q1/Q0), or model-output average quantities (U, ne). The fitted quantity is not the same variable as any predictor: for instance, [N III]/[O III]88 is an integrated intensity ratio, whereas N/O is an input abundance, so the claimed exponent 1.00 is extracted from the model, not imposed by construction. The U1 = U × (Q1/Q0) combination is a post-fit composite justified by comparable indices, and the steep Q1/Q0 dependence of [Ne III]/[Ne II] is likewise a fitted result from the grid, not an input. Paper I is an empirically assembled catalog from separate observations; the model grid is compared against it as external validation, and the paper explicitly warns (Sec. 4.4) that photoionization models are not the endpoint of line diagnostics. The dust-radiation-pressure discussion (Sec. 4.3.1) is an acknowledged modeling limitation: the default grid neglects radiation pressure, and including it changes the structure, so the Table 1 exponents are model-dependent—a robustness caveat, not a circular reduction. No step in the derivation chain equates the claimed prediction with its input by definition, and no load-bearing argument rests on a self-citation chain.

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

The paper introduces no new physical entities, forces, or dimensions; it is a modeling grid over standard ISM parameters. The key free parameters are the fitted power-law exponents themselves, the segmented-break thresholds, and the 0.05 index cut. The main axioms are standard Cloudy assumptions plus the domain-specific choices of SED library, plane-parallel geometry, constant gas pressure without dust radiation pressure, fixed C/O, and D/G scaling with O/H. The single-slab assumption is explicitly acknowledged in Section 4.4. These axioms are the appropriate targets for scrutiny: they determine whether the derived scalings hold for real galaxies.

free parameters (3)
  • Power-law exponents x1...x5 = Table 1 values, e.g., [N iii]/[O iii]88: x3=1.00, x5=-0.52
    Each of the 21 diagnostics in Table 1 has up to five free exponents and a zero-point x0 fitted by least squares to model output. These are the central quantitative results; they carry no quoted uncertainties.
  • Segmented fit break points = Break at [O iii]88/[C ii] ~ 1; breaks at [N iii]/[N ii] ~ 5 and ~10 for 122 and 205 um variants; similar for optical…
    For fits involving high-ionization lines, the authors split the data above and below an apparent break point and fit two power laws. The break location is chosen from the data, adding a fitted threshold not part of Eq. 1.
  • Index cutoff at 0.05 = Indices with |x| < 0.05 are set to zero in Table 1
    A reporting threshold applied to the fitted exponents; it does not change fits but affects the reported table.
assumptions (7)
  • standard math Cloudy C23.01 atomic data and physical processes are correct for FIR FSL emissivities
    All line intensities come from Cloudy. The paper relies on Cloudy's collisional and radiative data being sufficiently accurate for the ratios studied (Section 2.1).
  • domain assumption POPSTAR 2009 stellar population SEDs with Chabrier IMF accurately represent the ionizing radiation in star-forming galaxies
    The incident radiation field is taken from these SEDs with ages limited to <=6 Myr for analysis (Section 2.1). The hardness-age-metallicity relation in Fig. 1 is assumed representative.
  • domain assumption Plane-parallel, constant gas pressure equilibrium with dust radiation pressure neglected is a valid representation of galaxy-integrated ISM emission
    Stated in Section 2.1 and revisited in Section 4.3.1, where the authors show the alternative (constant total pressure including dust radiation pressure) produces density structures they consider unphysical and an output U cap near log U = -2.
  • domain assumption Dust-to-gas ratio scales linearly with O/H from a solar value of 0.01
    Section 2.1 states D/G = 0.01 at solar metallicity and 'simply scale D/G directly with O/H'. This drives the O/H dependence of dust absorption and heating.
  • domain assumption Fixed solar abundance ratios for elements other than N and O, with independent N/O variation
    Section 2.1 varies O/H and N/O independently; He/H, C/O, Ne/O etc. are fixed at solar. The C/O ratio, which directly affects [C ii] and therefore many ratios, is not varied.
  • domain assumption Line width of 3 km/s and stopping at AV=100 mag or Te=10 K does not materially affect integrated line ratios
    Section 2.1 sets these values; the stopping criterion prevents deep molecular integration and could truncate [C i] or CO emitting layers, though the analysis focuses on atomic lines.
  • domain assumption Galaxy-integrated FIR FSL emission can be modeled by a single uniform slab
    Section 4.4 openly states: 'the explicit assumption that all emission arises from a single, uniform ionized structure is unrealistic for most galaxies.' This is a stated limitation, not hidden.

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Cite this review

Pith. "Pith review of Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) II: Photoionization Model View of Ionized to Neutral Gas Emission." pith.science (2026). https://pith.science/paper/UEO6IDAN

@misc{pith2026250711829,
  author       = {Pith},
  title        = {Pith review of: Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) II: Photoionization Model View of Ionized to Neutral Gas Emission},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/UEO6IDAN}},
  note         = {Machine review of arXiv:2507.11829}
}
abstract

Far-infrared (FIR) and mid-infrared (MIR) fine-structure lines (FSLs) provide key diagnostics of physical conditions in the interstellar medium (ISM). Building on empirical relations established in our previous work, we use photoionization models to systematically investigate the emission from both ionized and neutral gas phases in a coherent structure. By applying power-law fits to model parameters, we quantitatively capture how key FIR FSL ratios scale with physical properties such as density, radiation field strength and hardness, and elemental abundances. Our analysis confirms the primary dependencies behind most observed empirical trends and establishes certain FIR FSL ratios as tracers of physical parameters, while revealing that parameter marginalization-particularly in density and the O/H-$U$-$Q_1/Q_0$ relation-plays a crucial role in shaping tight correlations seen in galaxies. We also identify persistent challenges, including degeneracies between ionization parameter and radiation field hardness, uncertainties in neutral gas density, and difficulties in modeling dusty H II regions. We outline the fundamental observational and theoretical limitations of current FIR FSL diagnostics, and highlight prospects for advancing the field through comprehensive, multi-wavelength studies of diverse galaxy populations.

Figures

Figures reproduced from arXiv: 2507.11829 by the authors.

Figure 1
Figure 1. Stellar population age–radiation hardness dia￾gram. The stellar population models of different metallicities are plotted in different colors. Cloudy. Gas structure is modeled under constant pres￾sure, a choice justified in this section and discussed fur￾ther in Sec. 4.3. Each model is computed to a depth corresponding to either AV = 100 mag or Te = 10 K, whichever is reached first. This prevents the model from exten… view at source ↗
Figure 2
Figure 2. Example photoionization model structure of hydrogen (upper left), carbon (upper right), nitrogen (lower left), oxygen (lower right), as a function of depth. The y-axis on the right side shows the density (both total nH0 and electron ne), ionization parameter (log U), electron temperature (Te), and extinction (AV), corresponding to the dash-dotted lines. Only the layer near the boundary of the H ii region is shown. 1… view at source ↗
Figure 3
Figure 3. Model output spectral line intensities near the H ii region boundary, for hydrogen & neon (upper left), carbon (upper right), nitrogen (lower left), oxygen (lower right) spectral lines. The model output unit with arbitrary normalization is used [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (12 more)
Figure 5
Figure 5. Figure 5: Comparison of model [N ii]122/205 to a, [O iii]52/88; or b, [S ii]λ6731/6716. Data points are col￾or-coded according to the color bars displayed. The solid, dashed, and dotted thin lines are the theoretical emissivity ratio calculated using Te = 1E4, 2E4, 5E3 K, the sa…
Figure 4
Figure 4. Figure 4: Examples of power-law fit to the model output of a, [C ii]/Hα; b, all models of [O iii]88/[C ii]; c, [O iii]88/[C ii] with the line ratio <1; d, [O iii]88/[C ii] with the line ratio >1. In each panel, the model output quantity is plotted on x-axis, and the fitted relat…
Figure 6
Figure 6. Figure 6: [N ii]122/205 to [O i]63/145 of a, observations; and b, models. The color classification by galaxy type in the left panel is the same as that in fig. 1 in Paper I. For the model points, both the intrinsic flux by integrating intensity and emergent flux by considering r…
Figure 7
Figure 7. Figure 7: Model interpretation of [N ii]122/205 vs. [O i]145/[C ii] comparison. a, shows the model output line ratios color-coded by log U, and the 2-d grid manifests the effect of ne increasing along the thick solid lines, and U in￾creasing along the dashed lines, across the wh…
Figure 8
Figure 8. Figure 8: Model interpretation of [Ne iii]15/[Ne ii]12–[O iii]88/[C ii] diagnostics. a, the model data points comparing the two line ratios are plotted and color-coded by Q1/Q0. The 2-d grid shows the effect of increasing Q1/Q0 (log (Q1/Q0) = –1.4, –1.0, to –0.6) along the solid…
Figure 9
Figure 9. Figure 9: Model view of the comparison of [O iii]88/[C ii]–[N iii]/[N ii]. Both [N ii]205 (top row) and [N ii]122 (bottom row) are shown. The right column shows the [N iii]/[N ii] dependence on log U. In left column, the grid of ne (solid lines) and U (dotted lines) is shown. Th…
Figure 10
Figure 10. Figure 10: Radiation field diagnostics comparison between optical and FIR line ratios. a-b (left), [O iii]λ5007/[S ii]λ6717,6731 vs. [O iii]88/[C ii]; bsfc-e (middel), [O iii]λ5007/[O i]λ6300 vs. [O iii]88/[O i]145; bsff-h (right), [O iii]λ5007/[N ii]λ6584 vs. [O iii]88/[N ii]20…
Figure 11
Figure 11. Figure 11: N/O diagnostics using a, [N iii]/[O iii]88; and b, [N iii]/[O iii]52,88. The gray and thick dashed lines and the shade represent the fit on the observational data in Paper I fig. 19. A grid of Q1/Q0 (solid lines, –0.6, –1.0, –1.4)–N/O is also plotted. 3.5. Electron Te…
Figure 13
Figure 13. Figure 13: [O iii]λ5007/[O iii]88–log (O/H), with the grid ne (solid lines)–O/H (dashed lines) overplotted on model points in a. 10 0 10 1 [N II] 6584/[N II]122 10 1 10 0 10 1 [O III] 5007/[O III]88 10 1 10 2 10 3 10 4 ne [cm 3 ] 10 0 10 1 10 2 [N II] 6584/[N II]205 ne = 10 cm 3…
Figure 14
Figure 14. Figure 14: Comparison of Te,[O III],FIR by [O iii]λ5007/[O iii]88 to Te,[N II],FIR by a, [N ii]λ6584/[N ii]122; and b [N ii]λ6584/[N ii]205. The different colored lines with black edge are emissivity ratios assuming different ne but temperature equilibrium, while the gray dashed…
Figure 15
Figure 15. Figure 15: Comparison of the structure of a model that uses a constant gas pressure (solid lines) with that of a model with the same setup except for adopting a constant total pressure that includes dust radiation pressure (dashed lines). In the figure, ne and the total density …
Figure 16
Figure 16. Figure 16: The output ionization parameter U as a function of power-law scaling of (D/G) and Q1/Q0, color-coded by different model input U. The dashed line highlights the cap on output U set by the scaling in the x axis. concentrate in a thin shell near the ionization front. Dra…

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Works this paper leans on

53 extracted references · 8 canonical work pages · cited by 1 Pith paper

  1. [1]

    P., Ferland, G

    Abel, N. P., Ferland, G. J., Shaw, G., & van Hoof, P. A. M. 2005, ApJS, 161, 65, doi: 10.1086/432913

    doi:10.1086/432913 2005

  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 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f

    arXiv 2009

  3. [3]

    R., Dale, D

    Brauher, J. R., Dale, D. A., & Helou, G. 2008, ApJS, 178, 280, doi: 10.1086/590249

    doi:10.1086/590249 2008

  4. [4]

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

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

    doi:10.1086/376392 2003

  5. [5]

    2023, RMxAA, 59, 327, doi: 10.22201/ia.01851101p.2023.59.02.12

    Chatzikos, M., Bianchi, S., Camilloni, F., et al. 2023, RMxAA, 59, 327, doi: 10.22201/ia.01851101p.2023.59.02.12

    doi:10.22201/ia.01851101p.2023.59.02.12 2023

  6. [6]

    C., Lebouteiller, V., et al

    Cormier, D., Madden, S. C., Lebouteiller, V., et al. 2015, A&A, 578, A53, doi: 10.1051/0004-6361/201425207

    doi:10.1051/0004-6361/201425207 2015

  7. [7]

    P., Hony, S., et al

    Cormier, D., Abel, N. P., Hony, S., et al. 2019, A&A, 626, A23, doi: 10.1051/0004-6361/201834457

    doi:10.1051/0004-6361/201834457 2019

  8. [8]

    Cunningham, D. J. M., Chapman, S. C., Aravena, M., et al. 2020, MNRAS, 494, 4090, doi: 10.1093/mnras/staa820

    doi:10.1093/mnras/staa820 2020

Show all 53 references
  1. [9]

    D., et al

    Deharveng, L., Schuller, F., Anderson, L. D., et al. 2010, A&A, 523, A6, doi: 10.1051/0004-6361/201014422 D’Hendecourt, L. B., & Leger, A. 1987, A&A, 180, L9 D ´ ıaz-Santos, T., Armus, L., Charmandaris, V., et al. 2017, ApJ, 846, 32, doi: 10.3847/1538-4357/aa81d7

    2010 doi

  2. [10]

    Dimaratos, A., Cormier, D., Bigiel, F., & Madden, S. C. 2015, A&A, 580, A135, doi: 10.1051/0004-6361/201526447

    2015 doi

  3. [11]

    A., Fischera, J., Sutherland, R

    Dopita, M. A., Fischera, J., Sutherland, R. S., et al. 2006, ApJ, 647, 244, doi: 10.1086/505418

    2006 doi

  4. [12]

    Draine, B. T. 2011, ApJ, 732, 100, doi: 10.1088/0004-637X/732/2/100

    2011 doi

  5. [13]

    T., Dale, D

    Draine, B. T., Dale, D. A., Bendo, G., et al. 2007, ApJ, 663, 866, doi: 10.1086/518306

    2007 doi

  6. [14]

    G., & Pagel, B

    Edmunds, M. G., & Pagel, B. E. J. 1978, MNRAS, 185, 77P, doi: 10.1093/mnras/185.1.77P

    1978 doi

  7. [15]

    Farrah, D., Lebouteiller, V., Spoon, H. W. W., et al. 2013, ApJ, 776, 38, doi: 10.1088/0004-637X/776/1/38 Fern´ andez Aranda, R., D ´ ıaz Santos, T., Hatziminaoglou, E., et al. 2024, A&A, 682, A166, doi: 10.1051/0004-6361/202347869 Fern´ andez-Ontiveros, J. A., Spinoglio, L., ...

    2013 doi

  8. [16]

    P., Gonz´ alez-Alfonso, E., et al

    Fischer, J., Abel, N. P., Gonz´ alez-Alfonso, E., et al. 2014, ApJ, 795, 117, doi: 10.1088/0004-637X/795/2/117

    2014 doi

  9. [17]

    M., & Graham, J

    Gilbert, A. M., & Graham, J. R. 2007, ApJ, 668, 168, doi: 10.1086/520910

    2007 doi

  10. [18]

    Grevesse, N., & Sauval, A. J. 1998, SSRv, 85, 161, doi: 10.1023/A:1005161325181

    1998 doi

  11. [19]

    Ferland, G. J. 2023, Research Notes of the American Astronomical Society, 7, 246, doi: 10.3847/2515-5172/ad0e75

    2023 doi

  12. [20]

    Henry, R. B. C., Edmunds, M. G., & K¨ oppen, J. 2000, ApJ, 541, 660, doi: 10.1086/309471

    2000 doi

  13. [21]

    2018, ApJ, 861, 94, doi: 10.3847/1538-4357/aac0f6

    Herrera-Camus, R., Sturm, E., Graci´ a-Carpio, J., et al. 2018, ApJ, 861, 94, doi: 10.3847/1538-4357/aac0f6

    2018 doi

  14. [22]

    K., & Hirashita, H

    Hunt, L. K., & Hirashita, H. 2009, A&A, 507, 1327, doi: 10.1051/0004-6361/200912020

    2009 doi

  15. [23]

    R., Oka, T., & McCall, B

    Indriolo, N., Geballe, T. R., Oka, T., & McCall, B. J. 2007, ApJ, 671, 1736, doi: 10.1086/523036

    2007 doi

  16. [24]

    Inoue, A. K. 2002, ApJ, 570, 688, doi: 10.1086/339788

    2002 doi

  17. [25]

    R., & Conley, A

    Kamenetzky, J., Rangwala, N., Glenn, J., Maloney, P. R., & Conley, A. 2016, ApJ, 829, 93, doi: 10.3847/0004-637X/829/2/93

    2016 doi

  18. [26]

    2014, A&A, 562, A45, doi: 10.1051/0004-6361/201321954

    Karska, A., Herpin, F., Bruderer, S., et al. 2014, A&A, 562, A45, doi: 10.1051/0004-6361/201321954

    2014 doi

  19. [27]

    J., Wolfire, M

    Kaufman, M. J., Wolfire, M. G., & Hollenbach, D. J. 2006, ApJ, 644, 283, doi: 10.1086/503596

    2006 doi

  20. [28]

    Kennicutt, R. C., J. 1984, ApJ, 287, 116, doi: 10.1086/162669

    1984 doi

  21. [29]

    K., & Hodge, P

    Kennicutt, Robert C., J., Edgar, B. K., & Hodge, P. W. 1989, ApJ, 337, 761, doi: 10.1086/167147

    1989 doi

  22. [30]

    2021, MNRAS, 508, 1084, doi: 10.1093/mnras/stab2495

    Maiolino, R. 2021, MNRAS, 508, 1084, doi: 10.1093/mnras/stab2495

    2021 doi

  23. [31]

    C., Young, L

    Lapham, R. C., Young, L. M., & Crocker, A. 2017, ApJ, 840, 51, doi: 10.3847/1538-4357/aa6d83

    2017 doi

  24. [32]

    K., Sandstrom, K., Rosolowsky, E., et al

    Leroy, A. K., Sandstrom, K., Rosolowsky, E., et al. 2023, ApJL, 944, L9, doi: 10.3847/2041-8213/acaf85

    2023 doi

  25. [33]

    C., Marrone, D

    Litke, K. C., Marrone, D. P., Aravena, M., et al. 2022, ApJ, 928, 179, doi: 10.3847/1538-4357/ac58f9

    2022 doi

  26. [34]

    2017, ApJS, 230, 1, doi: 10.3847/1538-4365/aa6476

    Lu, N., Zhao, Y., D ´ ıaz-Santos, T., et al. 2017, ApJS, 230, 1, doi: 10.3847/1538-4365/aa6476

    2017 doi

  27. [35]

    C., Galliano, F., Jones, A

    Madden, S. C., Galliano, F., Jones, A. P., & Sauvage, M. 2006, A&A, 446, 877, doi: 10.1051/0004-6361:20053890

    2006 doi

  28. [36]

    C., R´ emy-Ruyer, A., Galametz, M., et al

    Madden, S. C., R´ emy-Ruyer, A., Galametz, M., et al. 2013, PASP, 125, 600, doi: 10.1086/671138 Mart ´ ın-Hern´ andez, N. L., Vermeij, R., & van der Hulst, J. M. 2005, A&A, 433, 205, doi: 10.1051/0004-6361:20042143 Moll´ a, M., Garc ´ ıa-Vargas, M. L., & Bressan, A. 2009, MNRA...

    2013

  29. [37]

    2025, Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) I: Comprehensive Low and High Redshift Catalogs and Empirical Relations for Probing Gas Conditions

    Peng, B., Lamarche, C., Ball, C., et al. 2025, Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) I: Comprehensive Low and High Redshift Catalogs and Empirical Relations for Probing Gas Conditions. https://arxiv.org/abs/2507.10702

    2025 arXiv

  30. [38]

    J., et al

    Peng, B., Lamarche, C., Stacey, G. J., et al. 2021, ApJ, 908, 166, doi: 10.3847/1538-4357/abd4e2

    2021 doi

  31. [39]

    S., Thuan, T

    Pilyugin, L. S., Thuan, T. X., & V ´ ılchez, J. M. 2003, A&A, 397, 487, doi: 10.1051/0004-6361:20021458

    2003 doi

  32. [40]

    D., Spilker, J

    Reuter, C., Vieira, J. D., Spilker, J. S., et al. 2020, ApJ, 902, 78, doi: 10.3847/1538-4357/abb599

    2020 doi

  33. [41]

    Rosenberg, M. J. F., van der Werf, P. P., Aalto, S., et al. 2015, ApJ, 801, 72, doi: 10.1088/0004-637X/801/2/72

    2015 doi

  34. [42]

    A., Vegetti, S., et al

    Rybak, M., Hodge, J. A., Vegetti, S., et al. 2020, MNRAS, 494, 5542, doi: 10.1093/mnras/staa879

    2020 doi

  35. [43]

    2022, A&A, 658, A188, doi: 10.1051/0004-6361/202141907

    Santoro, F., Kreckel, K., Belfiore, F., et al. 2022, A&A, 658, A188, doi: 10.1051/0004-6361/202141907

    2022 doi

  36. [44]

    2002, A&A, 382, 28, doi: 10.1051/0004-6361:20011619

    Schaerer, D. 2002, A&A, 382, 28, doi: 10.1051/0004-6361:20011619

    2002 doi

  37. [45]

    S., Harnden, F

    Sciortino, S., Vaiana, G. S., Harnden, F. R., J., et al. 1990, ApJ, 361, 621, doi: 10.1086/169225

    1990 doi

  38. [46]

    M., et al

    Spinoglio, L., Pereira-Santaella, M., Dasyra, K. M., et al. 2015, ApJ, 799, 21, doi: 10.1088/0004-637X/799/1/21

    2015 doi

  39. [47]

    A., Malkan, M

    Spinoglio, L., Fern´ andez-Ontiveros, J. A., Malkan, M. A., et al. 2022, ApJ, 926, 55, doi: 10.3847/1538-4357/ac37b7 Stasi´ nska, G., Cid Fernandes, R., Mateus, A., Sodr´ e, L., &

    2022 doi

  40. [48]

    Asari, N. V. 2006, MNRAS, 371, 972, doi: 10.1111/j.1365-2966.2006.10732.x

    2006

  41. [49]

    A., Croxall, K

    Sutter, J., Dale, D. A., Croxall, K. V., et al. 2019, ApJ, 886, 60, doi: 10.3847/1538-4357/ab4da5

    2019 doi

  42. [50]

    Tielens, A. G. G. M. 2008, ARA&A, 46, 289, doi: 10.1146/annurev.astro.46.060407.145211

    2008

  43. [51]

    Tielens, A. G. G. M., & Hollenbach, D. 1985, ApJ, 291, 722, doi: 10.1086/163111 Vale Asari, N., Stasi´ nska, G., Morisset, C., & Cid

    1985 doi

  44. [52]

    2016, MNRAS, 460, 1739, doi: 10.1093/mnras/stw971

    Fernandes, R. 2016, MNRAS, 460, 1739, doi: 10.1093/mnras/stw971

    2016 doi

  45. [53]

    K., et al

    Zhao, Y., Lu, N., Xu, C. K., et al. 2016, ApJ, 819, 69, doi: 10.3847/0004-637X/819/1/69

    2016 doi

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