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A reference framework for extremely metal-poor OB star studies: calibrations for stellar parameters and intrinsic colours

T0 review · 3 major / 6 minor · reviewed 2026-08-10 · deepseek-v4-flash

Pith's one-line read Extremely metal-poor O and B stars are hotter and more ionizing than their Milky Way counterparts, with a HeII-ionizing output that depends on wind strength as much as on spectral type.

desk verdict A genuinely useful first calibration for 0.1 Zsun OB stars, with a real reproducibility gap: the classification criteria are deferred to an unpublished companion paper, and every number in the tables inherits that uncertainty. read the letter →

arxiv 2501.07569 v1 pith:R5A2CMKZ submitted 2025-01-13 astro-ph.SR astro-ph.GA

classification astro-ph.SRastro-ph.GA
keywords extremelymetal-poorOBstarsFASTWINDmodelsspectralclassificationeffectivetemperaturescaleionizingphotonfluxesHeII-ionizingfluxintrinsiccoloursSextansAextinction
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

Stars are classified by the lines in their spectra, but the mapping from spectral type to physical properties has only been calibrated for metal-rich galaxies. This paper builds the first such calibration for extremely metal-poor (XMP) O and early-B stars, at one tenth of the Sun's metallicity, by classifying a grid of 13,700 synthetic stellar atmospheres and averaging the parameters of all models that reproduce each spectral subtype. It concludes that XMP OB stars of a given type are 1-6 kK hotter than their Galactic analogues, emit more hydrogen- and helium-ionizing radiation, and have a HeII-ionizing output that depends on wind strength so strongly that single-value calibrations can miss individual late-O stars by up to four orders of magnitude. A sympathetic reader would care because these stars are the local proxies for the first massive stars in the Universe, and the same numbers feed population synthesis and photoionization codes used for high-redshift galaxies.

What carries the argument

The central object is the classified model grid: 13,700 FASTWIND synthetic spectra at 0.10 $Z_\odot$, degraded to $R=2500$ with $v \sin i = 70$ km/s, assigned spectral subtypes and luminosity classes using criteria adapted from Lennon (1997) and Sota et al. (2011), and filtered to 5,150 realistic models by the wind-momentum-luminosity relation (scaled from the SMC) and an Eddington-factor cut. The load-bearing step is averaging stellar parameters over all models compatible with each (spectral type, luminosity class) pair, which is what turns a grid into a calibration that carries a range of values instead of a single sequence. The colour tables are corrected for hydrogen-series line dissolution using CMFGEN models, and the $Q_{\mathrm{phot}}$ pseudo-colour relations translate the calibration into reddening-free selection and extinction estimators.

What would settle it

Take a sample of ~20 XMP O dwarfs with high-S/N spectra, classify them with the paper's criteria, and measure $T_{\mathrm{eff}}$ independently from Balmer line profiles and the SED; if O9 V stars consistently come out near 30 kK instead of the calibrated ~34.5 kK, the $T_{\mathrm{eff}}$ scale is wrong. Alternatively, resolve an XMP HII region whose ionizing late-O dwarf has a wind measured from UV P Cygni profiles: the model predicts $\log q_{\mathrm{HeII}}$ jumps by up to 4 dex across similar subtypes as wind strength changes, so a single-valued high $q_{\mathrm{HeII}}$ for all O8-9 V stars would refute the bimodality claim.

Watch

Extended reading notes

Core claim

The central claim is that a grid of 13,700 FASTWIND model atmospheres at $Z = 0.10\,Z_\odot$, classified with spectral criteria adapted to that metallicity and filtered to physically realistic winds, yields the first reference calibration of stellar parameters and intrinsic colours for XMP OB stars. On this scale, O dwarfs of a given subtype are up to ~6 kK hotter than the Milky Way scale of Martins et al. (2005a), giants and supergiants are 1-2 kK hotter, and the whole class emits more H i and He i ionizing photons. The He ii-ionizing flux is not a single-valued function of spectral type: within one late-O subtype it splits into a high and a low branch depending on the wind-strength parameter, with differences of up to 4 dex, so the paper reports only upper limits for $\log q_{\mathrm{HeII}}$. Applying the calibrated intrinsic colours to the Sextans A OB-star sample yields a patchy extinction map with $E(B-V)$ reaching 0.5-0.6 mag, showing that internal reddening in this 0.10 $Z_\odot$ dwarf galaxy is non-negligible and uneven.

Load-bearing premise

The calibration stands on the assignment of spectral types to synthetic spectra using classification criteria adapted to 0.10 $Z_\odot$, but those adapted criteria are not presented in this paper (deferred to a companion work), and the paper notes that B-type classification is severely hampered by weak Si and Mg lines at this metallicity and low signal-to-noise.

Editorial extensions

If this is right

  • Any use of Milky Way effective-temperature scales on 0.10 $Z_\odot$ O and B stars will under-estimate their temperatures, and the under-estimate grows toward dwarfs, reaching ~6 kK.
  • Population synthesis codes that adopt a single wind-strength per spectral type will mis-estimate the HeII-ionizing photon output of late-O dwarfs by up to four orders of magnitude, which directly affects predictions of HeII emission in low-metallicity galaxies.
  • At fixed $Q_{\mathrm{phot}}$, the calibrated $(B-V)_0$ is redder by 0.07 mag than Massey et al. (2000)'s relation, so extinction estimates and candidate cuts shift toward redder intrinsic colours.
  • Sextans A's internal reddening, with colour excesses up to ~0.6 mag in some sightlines, means that assuming negligible extinction in XMP dwarf galaxies biases derived luminosities, masses, and star-formation rates.
  • Four orders-of-magnitude in HeII-ionizing output also changes the interpretation of nebular HeII emission: strong HeII lines do not automatically require very hot or evolved stars if a late-O dwarf with a weak wind is present.

Reading between the lines

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

  • If the bimodal HeII-ionizing behaviour is real, nebular HeII 4686 and HeII 1640 emission in XMP galaxies may serve as a wind diagnostic for late-O dwarfs, complementing UV and near-IR wind tracers.
  • The same grid-and-classify pipeline could be run at 0.05 and 0.2 $Z_\odot$ to build a continuous metallicity ladder, which would let population synthesis codes interpolate ionizing fluxes with wind-strength aware libraries rather than scaling the Milky Way scale.
  • A direct test of the calibration would be to compare the paper's assigned spectral types against an independent XMP spectral atlas: a systematic one-subtype shift would move every $T_{\mathrm{eff}}$ entry by roughly 3 kK in the opposite direction, because spectral type and temperature are tied through the He line ratios.
  • The Sextans A extinction map suggests that some apparently blue 'outlier' stars in dwarf-galaxy CMDs may be reddened rather than young, which would matter for star-formation histories inferred from resolved stellar populations.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 6 minor

Summary. This paper constructs a model-based reference framework for extremely metal-poor (0.10 Zsun) OB-type stars from a grid of 13,700 FASTWIND synthetic spectra. The models are assigned spectral types and luminosity classes using optical classification criteria adapted to low metallicity (the adaptation itself is deferred to a companion paper), then filtered for plausibility using the wind-momentum-luminosity relation and the Eddington factor, leaving 5,150 models. Averaging over models with compatible spectral morphology yields calibrations of Teff (Eq. 3), log qHI and log qHeI (Eqs. 5 and 6), upper limits on log qHeII, and photometric colours and bolometric corrections in several filter systems (Tables 2, B1-B3), supplemented by CMFGEN-based corrections for hydrogen level dissolution (Sect. 4.1). The headline results are that 0.10 Zsun OB stars are 1-6 kK hotter than Galactic analogues, produce higher H I and He I ionizing fluxes, that log qHeII is bimodal in mid- and late-O types with the high-flux branch not captured by some population-synthesis calibrations, and that the Sextans A extinction is non-negligible and uneven (Sect. 5).

Significance. If the calibration holds up, it fills a genuine gap: there is no existing SpT-based scale for stellar parameters and intrinsic colours of XMP massive stars, and the paper's openly stated methodology (classify, filter, average over degenerate models) is well suited to quantifying the intrinsic scatter of each subtype. The authors deserve credit for several concrete strengths: the pipeline is described in detail with a flowchart (Fig. 1); the averaging over the model grid explicitly addresses the degeneracy between Teff, log g and wind strength; the ionizing-flux scale agrees with independent observational estimates from Ramachandran et al. (2021) and Telford et al. (2023) for the H I and He I fluxes (Fig. 12); cross-code checks against CMFGEN and TLUSTY bound the model-dependence of the ionizing fluxes (Sect. 3.2); the photometric corrections for hydrogen level dissolution are a careful, non-obvious refinement; and the paper makes falsifiable predictions (hotter Teff scale, bluer (U-B), bimodal qHeII, non-uniform reddening in Sextans A) that can be tested with future observations.

major comments (3)
  1. [Section 2.2] The adapted spectral classification criteria are the load-bearing step of the entire calibration, but they are deferred to 'Lorenzo et al. in prep' rather than specified. The paper states that the classification follows Sota et al. (2011) and Negueruela et al. (2024) 'adapted to 0.10 Zsun metallicity following Lennon (1997)'s strategy', with only the detectability threshold (I_lambda = 1/(S/N)) and the adopted microturbulence documented. A one-subtype error in the assigned SpT propagates into every downstream result: the slopes in Eq. (3) are ~2.6-3.9 kK per subtype, the qHI and qHeI fits in Eqs. (5)-(6) shift by amounts comparable to the quoted uncertainties, colors change by up to ~0.02-0.04 mag, and the qHeII upper limits in Table 1 can move by several dex because of the steep bimodal branches (Sect. 3.2.1, Fig. 9). The paper itself acknowledges that B-type classification is 'severely hampered' by weak Si and Mg lines even at S/N = 100, forcing reliance on He lines. Since none of the adapted criteria are given and the classified grid is not released, no external check of the classification is currently possible; this is a correctness and reproducibility risk, not a presentation issue. I request that the adapted criteria be specified in an appendix or that the companion paper and the full classified grid be made available before acceptance.
  2. [Section 2.3] The physical filtering that selects which models enter the calibration depends on radii that are themselves adopted from other calibrations. For O stars, radii are taken from Martins et al. (2005a) and scaled to 0.10 Zsun assuming constant luminosity at fixed spectral type, iterated to convergence; for B supergiants, radii come from a linear regression over literature analyses. The WLR and Gamma_e filters then determine which 5,150 models survive, and all averages in Table 1, Eqs. (3), (5)-(6), and the qHeII maxima are computed over the surviving set. A systematic error in the assumed radii (for example, if the constant-luminosity scaling is not accurate at fixed spectral type) would change which models pass the filters and therefore shift the calibrated means and the stated min-max ranges, even though the per-model radii are varied by 20%. The 20% scatter probes random uncertainty but not the systematic offset. I ask for a sensitivity test in which the adopted radii are globally varied by plus and minus 10% and the calibration outputs are recomputed, and for a test of the chosen weak-wind luminosity threshold (log L/Lsun <= 5.6).
  3. [Figure 8; Section 3.1] The empirical support for the headline '1-6 kK hotter' claim is weaker for O dwarfs than the text suggests. In Fig. 8, the two Leo A dwarfs (K1, O9.5 V and K7, O9.7 V from Gull et al. 2022) lie about 4 kK below the new XMP scale and are compatible with the Galactic scale for class V, and the IC 1613 O8.5 I star (Garcia & Herrero 2013) also deviates substantially. The paper explains these discrepancies as possible misclassification of the observed stars, but the same classification logic is being applied to the synthetic spectra without external calibration, so the attribution of the discrepancy to the observations is not fully convincing. The agreement with observation is strong for the ionizing fluxes (Fig. 12) and for early-B supergiants, but for O dwarfs the XMP-vs-Galactic offset is currently a model-prediction resting on the unvalidated classification. Please either add a quantitative test (e.g., spectral fitting of one benchmark star with the new grid) or discuss explicitly what remains of the dwarf temperature offset if the Leo A dwarfs are taken at face value.
minor comments (6)
  1. [Section 6] The summary uses the abbreviation 'S11' for Sota et al. (2011) while the main text cites the full name; please make the citation style consistent.
  2. [Appendix B, Table B3] The table and appendix heading refer to 'WFPC3' filters; the instrument is WFC3 (as in Sect. 4). Please correct this typo.
  3. [Figure 23] The E(B-V) annotations (0.0, 0.5, 1.0, etc.) overlap heavily with the HI contours and the galaxy image, making the map difficult to read. Consider providing the per-star E(B-V) values in a machine-readable table and enlarging the color scale.
  4. [Equations (8) and (9)] Please state explicitly the units of the filter zero points ZP_T used in Eq. (8) and specify the adopted value of the solar bolometric magnitude in Eq. (9), since the BC_V values in Tables 2 and B1 are quoted to 0.01 mag and are used with M_V.
  5. [Section 4.1] The CMFGEN grid used for the level-dissolution corrections (Fig. 18) is described as having one mass-loss value per Teff-logg pair; stating the adopted values of log Qwind in that grid would make the quoted 0.001 mag insensitivity to this parameter more transparent.
  6. [Data Availability] The data availability statement says 'All data are incorporated into the article and its online supplementary material', but the full classified grid (SpT, LC, Teff, log g, log Qwind per model) is not part of the article and the classification criteria are in a companion paper. Please clarify or amend this statement, and consider releasing the classified grid to enable reproduction of Eqs. (3), (5), and (6).

Circularity Check

0 steps flagged · score 2.0 of 10

No circular reduction found; the only self-referential element is the deferred classification adaptation in Sect. 2.2, which is a reproducibility gap rather than a circular argument.

full rationale

The calibration chain is model-based rather than fitted: FASTWIND synthetic spectra are assigned spectral subtypes from He i/He ii line-ratio morphology, and the calibrated Teff scale (Eq. 3) and ionizing-flux fits (Eqs. 5-6) are averages over models binned by those subtypes. The spectral subtype is not defined in terms of the calibrated Teff or ionizing fluxes, so the central calibrations are not self-definitional. The q_HeII bimodality is a computed consequence of the deliberately wide wind-parameter range (log Qwind from -15 to -11.7) and known wind/physics mechanisms, not a fitted prediction. External consistency checks against observations of XMP OB stars (Fig. 8), ionizing-flux measurements (Fig. 12), and an independent cmfgen comparison (Figs. 13, 17-19) provide support outside the fitted values. The one load-bearing self-citation is the adaptation of spectral classification criteria to 0.10 Zsun, deferred to 'Lorenzo et al. in prep' (Sect. 2.2). This is a genuine missing-reference and reproducibility limitation, because all downstream results inherit any error in the unpublished criteria. It does not, however, constitute circularity in the technical sense: the paper does not define spectral types in terms of the quantities it claims to predict, and no equation reduces to another by construction. The score reflects the minor self-citation/reproducibility concern, not a circular derivation.

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

The work introduces no new physical entities. The central results rest on a large FASTWIND model grid, a classification scheme whose details are partly unpublished, and several externally adopted empirical relations (WLR, Gamma_e limit, radii scaling) that are not independently verified at 0.1 Z_sun.

free parameters (7)
  • wind strength parameter range = -15 to -11.7 dex (log Qwind)
    Chosen by hand to cover weak to moderate winds at 0.1 Z_sun; central to the qHeII bimodality.
  • weak-wind luminosity threshold = log L/Lsun = 5.6 dex
    Adopted boundary below which all models are accepted regardless of WLR, adapted from MW/SMC weak-wind detections.
  • Eddington factor upper limit = Gamma_e = 0.55
    From Gräfener et al. (2011) and Holgado et al. (2018) for solar metallicity; applied to O and B stars.
  • microturbulence = 5 km/s (O stars), 10 km/s (B supergiants)
    Adopted per model by hand; classification changes by less than 0.5 subtypes if 15 km/s is used (Appendix A).
  • helium abundance = Y_He = 0.10
    Fixed to a typical metal-poor value; no variation considered.
  • O-star radius scaling = Dwarfs 20% smaller, giants and supergiants 10% smaller than Galactic from Martins et al. (2005a)
    Iteratively derived from Teff differences at constant luminosity; affects L, M, and Qx.
  • B-supergiant radii = linear regression between spectral subtype and literature radii (Table 1)
    Assigned from spectroscopic analyses; no dedicated XMP B-supergiant radii exist.
assumptions (7)
  • domain assumption FASTWIND line-blanketed NLTE unified atmosphere models are reliable for hot stars at 0.1 Z_sun
    The entire calibration is built on FASTWIND (v10.6) SEDs and spectra; accuracy is not independently benchmarked at this metallicity.
  • ad hoc to paper Spectral classification criteria from Sota et al. (2011) and Negueruela et al. (2024), adapted to 0.1 Z_sun via Lennon (1997), apply to synthetic spectra
    The adaptation is central but described only as 'see Lorenzo et al. in prep', not in this paper (Section 2.2).
  • domain assumption The modified wind momentum-luminosity relation (WLR) at 0.1 Z_sun has the same slope as SMC with a metallicity-scaled intercept and +/- 1 dex scatter
    Used to select 'realistic' models in Section 2.3; no direct 0.1 Z_sun WLR exists.
  • domain assumption Gamma_e upper limit of 0.55 applies to O and B stars at low metallicity
    Transferred from solar-neighborhood and Local Group analyses; affects model selection.
  • standard math O-star radii scale with T_eff to the power minus two at constant luminosity (from Martins et al. 2005a)
    Used to scale radii to 0.1 Z_sun via iterative Teff differences (Section 2.3).
  • standard math The line detectability limit follows I_lambda = 1/(S/N)
    Simplified from a fit to simulations (slope 0.884, intercept 0.004) in Fig. 4.
  • domain assumption CMFGEN models with lines and level dissolution de-activated reproduce FASTWIND SEDs; interpolation and extrapolation of the magnitude corrections is valid
    Used to correct synthetic photometry for missing hydrogen series lines (Section 4.1).

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Cite this review

Pith. "Pith review of A reference framework for extremely metal-poor OB star studies: calibrations for stellar parameters and intrinsic colours." pith.science (2026). https://pith.science/paper/R5A2CMKZ

@misc{pith2026250107569,
  author       = {Pith},
  title        = {Pith review of: A reference framework for extremely metal-poor OB star studies: calibrations for stellar parameters and intrinsic colours},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/R5A2CMKZ}},
  note         = {Machine review of arXiv:2501.07569}
}
abstract

We provide the first reference framework for extremely metal-poor (XMP) OB-type stars. We parsed a grid of 0.10 $Z_{\odot}$ FASTWIND models, covering the parameter space of O stars and early-B supergiants, through contemporary spectral classification criteria to deliver a calibration of key stellar properties as a function of spectral type, and tabulated colours for the most common photometric systems. By using an extensive grid of models, we account for the different combinations of stellar parameters that result in the same spectral morphology and provide a range of parameters and colours compatible with each spectral subtype and luminosity class. We supply updated photometric criteria to optimize candidate selection of OB stars in XMP environments. We find 0.10 $Z_{\odot}$ OB stars are 1-6 kK hotter and produce higher ionizing fluxes than their Galactic analogues. In addition, we find a bimodal distribution of the HeII-ionizing flux with spectral type; because of its known dependence on effective temperature and the wind, $\log~q_{HeII}$ for individual XMP late-O type stars could be underestimated by up to 4 orders of magnitude by other calibrations, some of them used by population synthesis codes. Finally, we used our calibrated colours to map the extinction of the 0.10 $Z_{\odot}$ galaxy Sextans A finding that reddening is non-negligible and uneven.

Figures

Figures reproduced from arXiv: 2501.07569 by the authors.

Figure 1
Figure 1. Flowchart illustrating the strategy followed to assign spectral types to our grid of fastwind synthetic spectra and distil the subsample of models that hold realistic physical properties. 2001) were treated as background elements (i.e., allowing them to contribute to line-blocking/blanketing but not calculating their spec￾tral line profiles). The models have 0.10 𝑍⊙ metallicity (scaled using the solar abundances fro… view at source ↗
Figure 4
Figure 4. Minimum intensity at which spectral lines are detected for different levels of noise. We used various random seeds to simulate the noise. The points fit a linear function of slope 0.884 and intercept 0.004, shown in yellow in the Figure. We approximate this function to a 1:1 relation 𝐼𝜆 = 1/(S/N) throughout the text. To this end, we plotted the He ii 4541 transition with different line￾intensities, as shown in [PIT… view at source ↗
Figure 3
Figure 3. He ii 4541 line with different line-intensities, as indicated above each panel. The profile was convolved to 𝑅 = 2500 and 𝑣 sin 𝑖 = 70 km s−1 (in red), including Gaussian noise with 𝜎 = 1/50 sp. pix.−1 (in orange) and after applying a five-point smooth (in black). The line is no longer detected at intensities lower than 0.02. embedded shocks. The exponent of the wind-velocity law (𝛽) and the helium abundance (𝑌He) w… view at source ↗
Figures from the paper (16 more)
Figure 5
Figure 5. Figure 5: Complete grid of fastwind models (grey) and the selection of realistic models (orange) according to the observed properties of low-𝑍 OB￾type stars (see Sect. 2.3). In the top panel, we present the modified wind￾momentum – luminosity relation (WLR). As a reference, we i…
Figure 6
Figure 6. Figure 6: Effective temperature of all the models as a function of their spectral subtype for different luminosity classes. The black solid lines are the linear fits for O stars excluding the O9.7 subtype. The dashed black line is the linear fit for the early-B supergiants. We p…
Figure 8
Figure 8. Figure 8: Effective temperature as a function of spectral type, comparing this work’s calibration with observations of OB-type stars in environments with sub-SMC oxygen and iron content (filled symbols): Telford et al. (2021) in Leo P (0.03 𝑍⊙), Gull et al. (2022) in Leo A (0.05…
Figure 9
Figure 9. Figure 9: H i-, He i- and He ii-ionizing photon flux (in logarithm) of the grid models as a function of spectral type for different luminosity classes. The black solid lines are the least squared fits to O star models, excluding the O9.7 subtype. The black dashed lines are the f…
Figure 12
Figure 12. Figure 12: The log 𝑞HI (green) and log 𝑞HeI (blue) scales obtained in this work are compared against measurements of the ionizing flux of XMP O stars: MB01 and MB02 in the Magellanic Bridge (Ramachandran et al. 2021) and LP26 in Leo P (Telford et al. 2023). We note that Ramachan…
Figure 13
Figure 13. Figure 13: Spectral energy distributions of 𝑇eff = 38 kK, log 𝑔 = 4.0 dex and log 𝑄wind = -14 dex models calculated with fastwind (purple) and cmfgen (black). The right panels zoom into the ionization edges of H, He i and He ii. The ionization wavelengths of these atomic species…
Figure 11
Figure 11. Figure 11: Same as [PITH_FULL_IMAGE:figures/full_fig_p011_11.png]
Figure 14
Figure 14. Figure 14: He ii-ionizing flux of all the models classified as O stars, regardless their luminosity class, as a function of 𝑇eff for different values of the wind strength parameter. The coloured sidebar indicates the assigned spectral subtypes. The Figure illustrates how the pro…
Figure 15
Figure 15. Figure 15: Impact of log 𝑔 on 𝑞HeII. All models classified as O stars with log 𝑄wind = -14 dex and -13.5 dex are shown, independently of their spectral type and luminosity class. The sidebar illustrates the colour code according to log 𝑔. We mark the transition 𝑇eff for models w…
Figure 16
Figure 16. Figure 16: The He ii-ionizing flux estimated in this work for O dwarfs and supergiants (points) compared against Smith et al. (2002)’s scales for metallicities 0.20 𝑍⊙ (solid lines) and 0.05 𝑍⊙ (dashed lines). where 𝑇 (𝜆) is the transmission curve of filter T1 . Then, we compute…
Figure 17
Figure 17. Figure 17: SEDs delivered by different atmosphere codes: fastwind (yellow solid line), cmfgen (black solid line) and cmfgen with lines and level disso￾lution de-activated in the formal solution (red dashed line). All models have 𝑇eff = 33 kK and log 𝑔 = 3.4 dex. As a reference, …
Figure 19
Figure 19. Figure 19: Left panels: Differences between the KPNO-MOSAIC 𝑈𝐵𝑉 magnitudes calculated from the SED of cmfgen models with and without including spectral lines and the continuum dissolution by the higher levels of the Balmer series (Δ𝑀T,LDcorr). These effects have the largest impa…
Figure 20
Figure 20. Figure 20: Martins & Plez (2006)’s calibration for the Bessell filters is compared against this work. We show the difference between the two systems in the upper panels. Colours are indicated in the legend. 1.0 0.8 0.6 1.2 1.1 1.0 0.9 0.8 0.7 V 1.0 0.8 0.6 III 1.0 0.8 0.6 I O4 O…
Figure 21
Figure 21. Figure 21: 𝑄phot vs. (𝑈 − 𝐵)0 calculated for our grid models, separated by luminosity class and colour-coded according to spectral type. The solid lines are the linear fits to the points for each luminosity class. The black dashed line represents the fit to all models regardless…
Figure 22
Figure 22. Figure 22: 𝑄phot vs. (𝐵 − 𝑉)0 calculated for our grid models, separated by luminosity class and colour-coded according to spectral type. The solid lines are the linear fits to the points for each luminosity class. The black dashed line represents the fit to all models regardless…
Figure 23
Figure 23. Figure 23: Extinction map of Sextans A. The background image is an RGB composite of Sextans A, built with H𝛼– (red) and 𝑉–bands (green) from Massey et al. (2007), and GALEX FUV (blue) data. We overlay a little things H i map (Hunter et al. 2012) with contour lines marking region…

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Works this paper leans on

103 extracted references · 19 canonical work pages

  1. [1]

    C., Hummer D

    Abbott D. C., Hummer D. G., 1985, @doi [ ] 10.1086/163297 , https://ui.adsabs.harvard.edu/abs/1985ApJ...294..286A 294, 286

  2. [2]

    J., Scott P., 2009, @doi [ ] 10.1146/annurev.astro.46.060407.145222 , https://ui.adsabs.harvard.edu/abs/2009ARA&A..47..481A 47, 481

    Asplund M., Grevesse N., Sauval A. J., Scott P., 2009, @doi [ ] 10.1146/annurev.astro.46.060407.145222 , https://ui.adsabs.harvard.edu/abs/2009ARA&A..47..481A 47, 481

  3. [3]

    arXiv:2308.08540

    Atek H., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2308.08540 , https://ui.adsabs.harvard.edu/abs/2023arXiv230808540A p. arXiv:2308.08540

  4. [4]

    O., Puls J., Najarro F., 2021, @doi [ ] 10.1051/0004-6361/202038384 , https://ui.adsabs.harvard.edu/abs/2021A&A...648A..36B 648, A36

    Bj \"o rklund R., Sundqvist J. O., Puls J., Najarro F., 2021, @doi [ ] 10.1051/0004-6361/202038384 , https://ui.adsabs.harvard.edu/abs/2021A&A...648A..36B 648, A36

  5. [5]

    C., Savage B

    Bohlin R. C., Savage B. D., Drake J. F., 1978, @doi [ ] 10.1086/156357 , https://ui.adsabs.harvard.edu/abs/1978ApJ...224..132B 224, 132

  6. [6]

    D., Wolfire M., Leroy A

    Bolatto A. D., Wolfire M., Leroy A. K., 2013, @doi [ ] 10.1146/annurev-astro-082812-140944 , https://ui.adsabs.harvard.edu/abs/2013ARA&A..51..207B 51, 207

  7. [7]

    C., Lanz T., Hillier D

    Bouret J. C., Lanz T., Hillier D. J., Heap S. R., Hubeny I., Lennon D. J., Smith L. J., Evans C. J., 2003, @doi [ ] 10.1086/377368 , https://ui.adsabs.harvard.edu/abs/2003ApJ...595.1182B 595, 1182

  8. [8]

    C., Lanz T., Hillier D

    Bouret J. C., Lanz T., Hillier D. J., Martins F., Marcolino W. L. F., Depagne E., 2015, @doi [ ] 10.1093/mnras/stv379 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.449.1545B 449, 1545

Show all 103 references
  1. [9]

    A., Gieren W., Pietrzy \'n ski G., Kudritzki R.-P., 2007, @doi [ ] 10.1086/522571 , https://ui.adsabs.harvard.edu/abs/2007ApJ...671.2028B 671, 2028

    Bresolin F., Urbaneja M. A., Gieren W., Pietrzy \'n ski G., Kudritzki R.-P., 2007, @doi [ ] 10.1086/522571 , https://ui.adsabs.harvard.edu/abs/2007ApJ...671.2028B 671, 2028

  2. [10]

    J., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2302.07256 , https://ui.adsabs.harvard.edu/abs/2023arXiv230207256B p

    Bunker A. J., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2302.07256 , https://ui.adsabs.harvard.edu/abs/2023arXiv230207256B p. arXiv:2302.07256

  3. [11]

    Camacho I., Garcia M., Herrero A., Sim \'o n-D \' az S., 2016, @doi [ ] 10.1051/0004-6361/201425533 , https://ui.adsabs.harvard.edu/abs/2016A&A...585A..82C 585, A82

  4. [12]

    P., Cohen D

    Cassinelli J. P., Cohen D. H., Macfarlane J. J., Sanders W. T., Welsh B. Y., 1994, @doi [ ] 10.1086/173683 , https://ui.adsabs.harvard.edu/abs/1994ApJ...421..705C 421, 705

  5. [13]

    A., Hillier D

    Crowther P. A., Hillier D. J., Evans C. J., Fullerton A. W., De Marco O., Willis A. J., 2002, @doi [ ] 10.1086/342877 , https://ui.adsabs.harvard.edu/abs/2002ApJ...579..774C 579, 774

  6. [14]

    A., Lennon D

    Crowther P. A., Lennon D. J., Walborn N. R., 2006, @doi [ ] 10.1051/0004-6361:20053685 , https://ui.adsabs.harvard.edu/abs/2006A&A...446..279C 446, 279

  7. [15]

    Ekstr \"o m S., Meynet G., Chiappini C., Hirschi R., Maeder A., 2008, @doi [ ] 10.1051/0004-6361:200809633 , https://ui.adsabs.harvard.edu/abs/2008A&A...489..685E 489, 685

  8. [16]

    P., Whitler L., Topping M

    Endsley R., Stark D. P., Whitler L., Topping M. W., Chen Z., Plat A., Chisholm J., Charlot S., 2022, @doi [arXiv e-prints] 10.48550/arXiv.2208.14999 , https://ui.adsabs.harvard.edu/abs/2022arXiv220814999E p. arXiv:2208.14999

  9. [17]

    J., Lennon D

    Evans C. J., Lennon D. J., Trundle C., Heap S. R., Lindler D. J., 2004, @doi [ ] 10.1086/383306 , https://ui.adsabs.harvard.edu/abs/2004ApJ...607..451E 607, 451

  10. [18]

    J., Bresolin F., Urbaneja M

    Evans C. J., Bresolin F., Urbaneja M. A., Pietrzy \'n ski G., Gieren W., Kudritzki R. P., 2007, @doi [ ] 10.1086/511382 , https://ui.adsabs.harvard.edu/abs/2007ApJ...659.1198E 659, 1198

  11. [19]

    J., et al., 2019, @doi [ ] 10.1051/0004-6361/201834145 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.129E 622, A129

    Evans C. J., et al., 2019, @doi [ ] 10.1051/0004-6361/201834145 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.129E 622, A129

  12. [20]

    P., Puls J., Pauldrach A., 1989, , https://ui.adsabs.harvard.edu/abs/1989A&A...226..162G 226, 162

    Gabler R., Gabler A., Kudritzki R. P., Puls J., Pauldrach A., 1989, , https://ui.adsabs.harvard.edu/abs/1989A&A...226..162G 226, 162

  13. [21]

    Garcia M., Herrero A., 2013, @doi [ ] 10.1051/0004-6361/201219977 , https://ui.adsabs.harvard.edu/abs/2013A&A...551A..74G 551, A74

  14. [22]

    J., Rosenberg A., Monelli M., 2009, @doi [ ] 10.1051/0004-6361/200911791 , https://ui.adsabs.harvard.edu/abs/2009A&A...502.1015G 502, 1015

    Garcia M., Herrero A., Vicente B., Castro N., Corral L. J., Rosenberg A., Monelli M., 2009, @doi [ ] 10.1051/0004-6361/200911791 , https://ui.adsabs.harvard.edu/abs/2009A&A...502.1015G 502, 1015

  15. [23]

    Garcia M., Herrero A., Castro N., Corral L., Rosenberg A., 2014, VizieR Online Data Catalog, https://ui.adsabs.harvard.edu/abs/2014yCat..35230023G pp J/A+A/523/A23

  16. [24]

    Garcia M., Herrero A., Najarro F., Camacho I., Lorenzo M., 2019, @doi [ ] 10.1093/mnras/sty3503 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484..422G 484, 422

  17. [25]

    S., de Koter A., Langer N., 2011, @doi [ ] 10.1051/0004-6361/201116701 , https://ui.adsabs.harvard.edu/abs/2011A&A...535A..56G 535, A56

    Gr \"a fener G., Vink J. S., de Koter A., Langer N., 2011, @doi [ ] 10.1051/0004-6361/201116701 , https://ui.adsabs.harvard.edu/abs/2011A&A...535A..56G 535, A56

  18. [26]

    Gull M., et al., 2022, @doi [ ] 10.3847/1538-4357/aca295 , https://ui.adsabs.harvard.edu/abs/2022ApJ...941..206G 941, 206

  19. [27]

    Hawcroft C., et al., 2024, @doi [ ] 10.1051/0004-6361/202245588 , https://ui.adsabs.harvard.edu/abs/2024A&A...688A.105H 688, A105

  20. [28]

    J., 1990, , https://ui.adsabs.harvard.edu/abs/1990A&A...231..116H 231, 116

    Hillier D. J., 1990, , https://ui.adsabs.harvard.edu/abs/1990A&A...231..116H 231, 116

  21. [29]

    J., Miller D

    Hillier D. J., Miller D. L., 1998, @doi [ ] 10.1086/305350 , https://ui.adsabs.harvard.edu/abs/1998ApJ...496..407H 496, 407

  22. [30]

    G., Drew J

    Hoare M. G., Drew J. E., Denby M., 1993, @doi [ ] 10.1093/mnras/262.1.L19 , https://ui.adsabs.harvard.edu/abs/1993MNRAS.262L..19H 262, L19

  23. [31]

    Holgado G., et al., 2018, @doi [ ] 10.1051/0004-6361/201731543 , https://ui.adsabs.harvard.edu/abs/2018A&A...613A..65H 613, A65

  24. [32]

    A., et al., 2012, @doi [ ] 10.1088/0004-6256/144/5/134 , https://ui.adsabs.harvard.edu/abs/2012AJ....144..134H 144, 134

    Hunter D. A., et al., 2012, @doi [ ] 10.1088/0004-6256/144/5/134 , https://ui.adsabs.harvard.edu/abs/2012AJ....144..134H 144, 134

  25. [33]

    L., Morgan W

    Johnson H. L., Morgan W. W., 1953, @doi [ ] 10.1086/145697 , https://ui.adsabs.harvard.edu/abs/1953ApJ...117..313J 117, 313

  26. [34]

    M., P \'e rez-Montero E., Iglesias-P \'a ramo J., Brinchmann J., Kunth D., Durret F., Bayo F

    Kehrig C., V \' lchez J. M., P \'e rez-Montero E., Iglesias-P \'a ramo J., Brinchmann J., Kunth D., Durret F., Bayo F. M., 2015, @doi [ ] 10.1088/2041-8205/801/2/L28 , https://ui.adsabs.harvard.edu/abs/2015ApJ...801L..28K 801, L28

  27. [35]

    Kudritzki R.-P., Puls J., 2000, @doi [ ] 10.1146/annurev.astro.38.1.613 , https://ui.adsabs.harvard.edu/abs/2000ARA&A..38..613K 38, 613

  28. [36]

    P., Pauldrach A., Puls J., 1987, , https://ui.adsabs.harvard.edu/abs/1987A&A...173..293K 173, 293

    Kudritzki R. P., Pauldrach A., Puls J., 1987, , https://ui.adsabs.harvard.edu/abs/1987A&A...173..293K 173, 293

  29. [37]

    P., Lennon D

    Kudritzki R. P., Lennon D. J., Puls J., 1995, in Walsh J. R., Danziger I. J., eds, Science with the VLT. p. 246

  30. [38]

    P., Puls J., Lennon D

    Kudritzki R. P., Puls J., Lennon D. J., Venn K. A., Reetz J., Najarro F., McCarthy J. K., Herrero A., 1999, , https://ui.adsabs.harvard.edu/abs/1999A&A...350..970K 350, 970

  31. [39]

    Kunth D., \"O stlin G., 2000, @doi [ ] 10.1007/s001590000005 , https://ui.adsabs.harvard.edu/abs/2000A&ARv..10....1K 10, 1

  32. [40]

    Lanz T., Hubeny I., 2003, @doi [ ] 10.1086/374373 , https://ui.adsabs.harvard.edu/abs/2003ApJS..146..417L 146, 417

  33. [41]

    Leitherer C., Robert C., Drissen L., 1992, @doi [ ] 10.1086/172089 , https://ui.adsabs.harvard.edu/abs/1992ApJ...401..596L 401, 596

  34. [42]

    Leitherer C., et al., 1999, @doi [ ] 10.1086/313233 , https://ui.adsabs.harvard.edu/abs/1999ApJS..123....3L 123, 3

  35. [43]

    J., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...317..871L 317, 871

    Lennon D. J., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...317..871L 317, 871

  36. [44]

    Lorenzo M., Garcia M., Najarro F., Herrero A., Cervi \ n o M., Castro N., 2022, @doi [ ] 10.1093/mnras/stac2050 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.4164L 516, 4164

  37. [45]

    Madau P., Dickinson M., 2014, @doi [ ] 10.1146/annurev-astro-081811-125615 , https://ui.adsabs.harvard.edu/abs/2014ARA&A..52..415M 52, 415

  38. [46]

    C., et al., 2020, @doi [ ] 10.1051/0004-6361/202038860 , https://ui.adsabs.harvard.edu/abs/2020A&A...643A.141M 643, A141

    Madden S. C., et al., 2020, @doi [ ] 10.1051/0004-6361/202038860 , https://ui.adsabs.harvard.edu/abs/2020A&A...643A.141M 643, A141

  39. [47]

    Marcolino W. L. F., Bouret J. C., Martins F., Hillier D. J., Lanz T., Escolano C., 2009, @doi [ ] 10.1051/0004-6361/200811289 , https://ui.adsabs.harvard.edu/abs/2009A&A...498..837M 498, 837

  40. [48]

    Markova N., Puls J., Langer N., 2018, @doi [ ] 10.1051/0004-6361/201731361 , https://ui.adsabs.harvard.edu/abs/2018A&A...613A..12M 613, A12

  41. [49]

    Martins F., Palacios A., 2021, @doi [ ] 10.1051/0004-6361/202039337 , https://ui.adsabs.harvard.edu/abs/2021A&A...645A..67M 645, A67

  42. [50]

    Martins F., Plez B., 2006, @doi [ ] 10.1051/0004-6361:20065753 , https://ui.adsabs.harvard.edu/abs/2006A&A...457..637M 457, 637

  43. [51]

    J., 2005a, @doi [ ] 10.1051/0004-6361:20042386 , https://ui.adsabs.harvard.edu/abs/2005A&A...436.1049M 436, 1049

    Martins F., Schaerer D., Hillier D. J., 2005a, @doi [ ] 10.1051/0004-6361:20042386 , https://ui.adsabs.harvard.edu/abs/2005A&A...436.1049M 436, 1049

  44. [52]

    J., Meynadier F., Heydari-Malayeri M., Walborn N

    Martins F., Schaerer D., Hillier D. J., Meynadier F., Heydari-Malayeri M., Walborn N. R., 2005b, @doi [ ] 10.1051/0004-6361:20052927 , https://ui.adsabs.harvard.edu/abs/2005A&A...441..735M 441, 735

  45. [53]

    Massey P., Waterhouse E., DeGioia-Eastwood K., 2000, @doi [ ] 10.1086/301345 , https://ui.adsabs.harvard.edu/abs/2000AJ....119.2214M 119, 2214

  46. [54]

    P., Puls J., Pauldrach A

    Massey P., Bresolin F., Kudritzki R. P., Puls J., Pauldrach A. W. A., 2004, @doi [ ] 10.1086/420766 , https://ui.adsabs.harvard.edu/abs/2004ApJ...608.1001M 608, 1001

  47. [55]

    Massey P., Puls J., Pauldrach A. W. A., Bresolin F., Kudritzki R. P., Simon T., 2005, @doi [ ] 10.1086/430417 , https://ui.adsabs.harvard.edu/abs/2005ApJ...627..477M 627, 477

  48. [56]

    Massey P., Olsen K. A. G., Hodge P. W., Jacoby G. H., McNeill R. T., Smith R. C., Strong S. B., 2007, @doi [ ] 10.1086/513319 , https://ui.adsabs.harvard.edu/abs/2007AJ....133.2393M 133, 2393

  49. [57]

    M., Morrell N

    Massey P., Zangari A. M., Morrell N. I., Puls J., DeGioia-Eastwood K., Bresolin F., Kudritzki R.-P., 2009, @doi [ ] 10.1088/0004-637X/692/1/618 , https://ui.adsabs.harvard.edu/abs/2009ApJ...692..618M 692, 618

  50. [58]

    M., et al., 2015, @doi [ ] 10.1051/0004-6361/201425202 , https://ui.adsabs.harvard.edu/abs/2015A&A...575A..70M 575, A70

    McEvoy C. M., et al., 2015, @doi [ ] 10.1051/0004-6361/201425202 , https://ui.adsabs.harvard.edu/abs/2015A&A...575A..70M 575, A70

  51. [59]

    R., et al., 2006, @doi [ ] 10.1051/0004-6361:20064995 , https://ui.adsabs.harvard.edu/abs/2006A&A...456.1131M 456, 1131

    Mokiem M. R., et al., 2006, @doi [ ] 10.1051/0004-6361:20064995 , https://ui.adsabs.harvard.edu/abs/2006A&A...456.1131M 456, 1131

  52. [60]

    R., et al., 2007a, @doi [ ] 10.1051/0004-6361:20066489 , https://ui.adsabs.harvard.edu/abs/2007A&A...465.1003M 465, 1003

    Mokiem M. R., et al., 2007a, @doi [ ] 10.1051/0004-6361:20066489 , https://ui.adsabs.harvard.edu/abs/2007A&A...465.1003M 465, 1003

  53. [61]

    R., et al., 2007b, @doi [ ] 10.1051/0004-6361:20077545 , https://ui.adsabs.harvard.edu/abs/2007A&A...473..603M 473, 603

    Mokiem M. R., et al., 2007b, @doi [ ] 10.1051/0004-6361:20077545 , https://ui.adsabs.harvard.edu/abs/2007A&A...473..603M 473, 603

  54. [62]

    P., Cassinelli J

    Najarro F., Kudritzki R. P., Cassinelli J. P., Stahl O., Hillier D. J., 1996, , https://ui.adsabs.harvard.edu/abs/1996A&A...306..892N 306, 892

  55. [63]

    M., Puls J., 2011, @doi [ ] 10.1051/0004-6361/201016003 , https://ui.adsabs.harvard.edu/abs/2011A&A...535A..32N 535, A32

    Najarro F., Hanson M. M., Puls J., 2011, @doi [ ] 10.1051/0004-6361/201016003 , https://ui.adsabs.harvard.edu/abs/2011A&A...535A..32N 535, A32

  56. [64]

    G., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.04163 , https://ui.adsabs.harvard.edu/abs/2024arXiv240704163N p

    Negueruela I., Sim \'o n-D \' az S., de Burgos A., Casasbuenas A., Beck P. G., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.04163 , https://ui.adsabs.harvard.edu/abs/2024arXiv240704163N p. arXiv:2407.04163

  57. [65]

    Pauldrach A. W. A., Lennon M., Hoffmann T. L., Sellmaier F., Kudritzki R. P., Puls J., 1998, in Howarth I., ed., Astronomical Society of the Pacific Conference Series Vol. 131, Properties of Hot Luminous Stars. p. 258

  58. [66]

    Pauldrach A. W. A., Hoffmann T. L., Lennon M., 2001, @doi [ ] 10.1051/0004-6361:20010805 , https://ui.adsabs.harvard.edu/abs/2001A&A...375..161P 375, 161

  59. [67]

    Puls J., et al., 1996, , https://ui.adsabs.harvard.edu/abs/1996A&A...305..171P 305, 171

  60. [68]

    Puls J., Springmann U., Lennon M., 2000, @doi [ ] 10.1051/aas:2000312 , https://ui.adsabs.harvard.edu/abs/2000A&AS..141...23P 141, 23

  61. [69]

    A., Venero R., Repolust T., Springmann U., Jokuthy A., Mokiem M

    Puls J., Urbaneja M. A., Venero R., Repolust T., Springmann U., Jokuthy A., Mokiem M. R., 2005, @doi [ ] 10.1051/0004-6361:20042365 , https://ui.adsabs.harvard.edu/abs/2005A&A...435..669P 435, 669

  62. [70]

    Ramachandran V., et al., 2019, @doi [ ] 10.1051/0004-6361/201935365 , https://ui.adsabs.harvard.edu/abs/2019A&A...625A.104R 625, A104

  63. [71]

    M., Hamann W

    Ramachandran V., Oskinova L. M., Hamann W. R., 2021, @doi [ ] 10.1051/0004-6361/202039486 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A..16R 646, A16

  64. [72]

    Ramambason L., et al., 2022, @doi [ ] 10.1051/0004-6361/202243866 , https://ui.adsabs.harvard.edu/abs/2022A&A...667A..35R 667, A35

  65. [73]

    H., et al., 2017, @doi [ ] 10.1051/0004-6361/201628914 , https://ui.adsabs.harvard.edu/abs/2017A&A...600A..81R 600, A81

    Ram \' rez-Agudelo O. H., et al., 2017, @doi [ ] 10.1051/0004-6361/201628914 , https://ui.adsabs.harvard.edu/abs/2017A&A...600A..81R 600, A81

  66. [74]

    G., Puls J., Massey P., Najarro F., 2012, @doi [ ] 10.1051/0004-6361/201218955 , https://ui.adsabs.harvard.edu/abs/2012A&A...543A..95R 543, A95

    Rivero Gonz \'a lez J. G., Puls J., Massey P., Najarro F., 2012, @doi [ ] 10.1051/0004-6361/201218955 , https://ui.adsabs.harvard.edu/abs/2012A&A...543A..95R 543, A95

  67. [75]

    Rodrigo C., Solano E., 2020, in XIV.0 Scientific Meeting (virtual) of the Spanish Astronomical Society. p. 182

  68. [76]

    Rodrigo C., Solano E., Bayo A., 2012, SVO Filter Profile Service Version 1.0 , IVOA Working Draft 15 October 2012, @doi 10.5479/ADS/bib/2012ivoa.rept.1015R

  69. [77]

    arXiv:2406.03310

    Rodrigo C., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.03310 , https://ui.adsabs.harvard.edu/abs/2024arXiv240603310R p. arXiv:2406.03310

  70. [78]

    Sab \' n-Sanjuli \'a n C., et al., 2017, @doi [ ] 10.1051/0004-6361/201629210 , https://ui.adsabs.harvard.edu/abs/2017A&A...601A..79S 601, A79

  71. [79]

    E., Puls J., Herrero A., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...323..488S 323, 488

    Santolaya-Rey A. E., Puls J., Herrero A., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...323..488S 323, 488

  72. [80]

    Schaerer D., de Koter A., 1997, @doi [ ] 10.48550/arXiv.astro-ph/9611068 , https://ui.adsabs.harvard.edu/abs/1997A&A...322..598S 322, 598

  73. [81]

    R., 1986, , https://ui.adsabs.harvard.edu/abs/1986A&A...166L..11S 166, L11

    Schmutz W., Hamann W. R., 1986, , https://ui.adsabs.harvard.edu/abs/1986A&A...166L..11S 166, L11

  74. [82]

    P., Charlot S., Chevallard J., Bruzual G., Vidal-Garc \' a A., 2021, @doi [ ] 10.1093/mnras/stab884 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.6112S 503, 6112

    Senchyna P., Stark D. P., Charlot S., Chevallard J., Bruzual G., Vidal-Garc \' a A., 2021, @doi [ ] 10.1093/mnras/stab884 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.6112S 503, 6112

  75. [83]

    Shi Y., Wang J., Zhang Z.-Y., Gao Y., Armus L., Helou G., Gu Q., Stierwalt S., 2015, @doi [ ] 10.1088/2041-8205/804/1/L11 , https://ui.adsabs.harvard.edu/abs/2015ApJ...804L..11S 804, L11

  76. [84]

    Sim \'o n-D \' az S., Stasi \'n ska G., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13444.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.389.1009S 389, 1009

  77. [85]

    J., 2014, @doi [ ] 10.1051/0004-6361/201424742 , https://ui.adsabs.harvard.edu/abs/2014A&A...570L...6S 570, L6

    Sim \'o n-D \' az S., Herrero A., Sab \' n-Sanjuli \'a n C., Najarro F., Garcia M., Puls J., Castro N., Evans C. J., 2014, @doi [ ] 10.1051/0004-6361/201424742 , https://ui.adsabs.harvard.edu/abs/2014A&A...570L...6S 570, L6

  78. [86]

    J., Norris R

    Smith L. J., Norris R. P. F., Crowther P. A., 2002, @doi [ ] 10.1046/j.1365-8711.2002.06042.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.337.1309S 337, 1309

  79. [87]

    R., Alfaro E

    Sota A., Ma \' z Apell \'a niz J., Walborn N. R., Alfaro E. J., Barb \'a R. H., Morrell N. I., Gamen R. C., Arias J. I., 2011, @doi [ ] 10.1088/0067-0049/193/2/24 , https://ui.adsabs.harvard.edu/abs/2011ApJS..193...24S 193, 24

  80. [88]

    Sz \'e csi D., Agrawal P., W \"u nsch R., Langer N., 2022, @doi [ ] 10.1051/0004-6361/202141536 , https://ui.adsabs.harvard.edu/abs/2022A&A...658A.125S 658, A125

  81. [89]

    A., Reindl B., Sandage A., 2011, @doi [ ] 10.1051/0004-6361/201016382 , https://ui.adsabs.harvard.edu/abs/2011A&A...531A.134T 531, A134

    Tammann G. A., Reindl B., Sandage A., 2011, @doi [ ] 10.1051/0004-6361/201016382 , https://ui.adsabs.harvard.edu/abs/2011A&A...531A.134T 531, A134

  82. [90]

    G., Chisholm J., McQuinn K

    Telford O. G., Chisholm J., McQuinn K. B. W., Berg D. A., 2021, @doi [ ] 10.3847/1538-4357/ac1ce2 , https://ui.adsabs.harvard.edu/abs/2021ApJ...922..191T 922, 191

  83. [91]

    G., McQuinn K

    Telford O. G., McQuinn K. B. W., Chisholm J., Berg D. A., 2023, @doi [ ] 10.3847/1538-4357/aca896 , https://ui.adsabs.harvard.edu/abs/2023ApJ...943...65T 943, 65

  84. [92]

    W., Stark D

    Topping M. W., Stark D. P., Endsley R., Plat A., Whitler L., Chen Z., Charlot S., 2022, @doi [ ] 10.3847/1538-4357/aca522 , https://ui.adsabs.harvard.edu/abs/2022ApJ...941..153T 941, 153

  85. [93]

    H., 2014, @doi [ ] 10.1051/0004-6361/201424312 , https://ui.adsabs.harvard.edu/abs/2014A&A...572A..36T 572, A36

    Tramper F., Sana H., de Koter A., Kaper L., Ram \' rez-Agudelo O. H., 2014, @doi [ ] 10.1051/0004-6361/201424312 , https://ui.adsabs.harvard.edu/abs/2014A&A...572A..36T 572, A36

  86. [94]

    L., Hunter I., Evans C

    Trundle C., Dufton P. L., Hunter I., Evans C. J., Lennon D. J., Smartt S. J., Ryans R. S. I., 2007, The VLT-FLAMES survey of massive stars: evolution of surface N abundances and effective temperature scales in the Galaxy and Magellanic Clouds , Astronomy and Astrophysics, Volu...

  87. [95]

    A., Herrero A., Kudritzki R

    Urbaneja M. A., Herrero A., Kudritzki R. P., Bresolin F., Corral L. J., Puls J., 2002, @doi [ ] 10.1051/0004-6361:20020349 , https://ui.adsabs.harvard.edu/abs/2002A&A...386.1019U 386, 1019

  88. [96]

    A., Kudritzki R.-P., Bresolin F., Przybilla N., Gieren W., Pietrzy \'n ski G., 2008, @doi [ ] 10.1086/590334 , https://ui.adsabs.harvard.edu/abs/2008ApJ...684..118U 684, 118

    Urbaneja M. A., Kudritzki R.-P., Bresolin F., Przybilla N., Gieren W., Pietrzy \'n ski G., 2008, @doi [ ] 10.1086/590334 , https://ui.adsabs.harvard.edu/abs/2008ApJ...684..118U 684, 118

  89. [97]

    S., de Koter A., Lamers H

    Vink J. S., de Koter A., Lamers H. J. G. L. M., 2000, , https://ui.adsabs.harvard.edu/abs/2000A&A...362..295V 362, 295

  90. [98]

    S., de Koter A., Lamers H

    Vink J. S., de Koter A., Lamers H. J. G. L. M., 2001, @doi [ ] 10.1051/0004-6361:20010127 , https://ui.adsabs.harvard.edu/abs/2001A&A...369..574V 369, 574

  91. [99]

    R., et al., 2015, @doi [ ] 10.1088/0004-637X/814/1/30 , https://ui.adsabs.harvard.edu/abs/2015ApJ...814...30W 814, 30

    Warren S. R., et al., 2015, @doi [ ] 10.1088/0004-637X/814/1/30 , https://ui.adsabs.harvard.edu/abs/2015ApJ...814...30W 814, 30

  92. [100]

    P., Herenz E

    Wofford A., Vidal-Garc \' a A., Feltre A., Chevallard J., Charlot S., Stark D. P., Herenz E. C., Hayes M., 2021, @doi [ ] 10.1093/mnras/staa3365 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.500.2908W 500, 2908

  93. [101]

    C., Langer N., Norman C., 2006, @doi [ ] 10.1051/0004-6361:20065912 , https://ui.adsabs.harvard.edu/abs/2006A&A...460..199Y 460, 199

    Yoon S. C., Langer N., Norman C., 2006, @doi [ ] 10.1051/0004-6361:20065912 , https://ui.adsabs.harvard.edu/abs/2006A&A...460..199Y 460, 199

  94. [102]

    write newline

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

  95. [103]

    write newline

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

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.