Pith. sign in

REVIEW 3 major objections 4 minor 4 cited by

pySTARBURST99: The Next Generation of STARBURST99

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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

Pith's one-line read The updated population-synthesis code pySTARBURST99 reproduces STARBURST99 and predicts that allowing stars up to 300 solar masses raises early hydrogen-ionising flux by 0.3 dex (about a factor of two).

desk verdict A useful, honest update to a standard population synthesis code, with a headline VMS ionising-flux boost that is plausible but rests on model physics and grid coverage the paper does not fully document. read the letter →

arxiv 2505.24841 v1 pith:NFNCMJBA submitted 2025-05-30 astro-ph.GA astro-ph.SR

Calum Hawcroft , Claus Leitherer , Oskar Arangure , John Chisholm , Sylvia Ekstrom , Sebastien Martinet , Lucimara Martins , Georges Meynet
show 3 more authors
Christophe Morisset Andreas Sander Aida Wofford
This is my paper · ORCID
classification astro-ph.GAastro-ph.SR
keywords populationsynthesisstarburstgalaxiesverymassivestarsionisingfluxstellarevolutionmodelatmospheresUVspectralslopePythoncode
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

pySTARBURST99 claims to be a faithful, more capable successor to STARBURST99: it reproduces the old code's spectral outputs when given the same stellar inputs, and it extends the models to lower metallicities, rotating stars, and very massive stars (initial masses above roughly 100 solar masses) up to $300$–$500\,M_\odot$. The paper combines new GENEC evolutionary tracks with a new grid of FASTWIND model-atmosphere spectra, then uses the updated code to predict the properties of young starburst galaxies: ionising fluxes, spectral energy distributions (SEDs), bolometric luminosity, wind power, hydrogen-line equivalent widths, and UV $\beta$ slopes. Its headline result is that raising the upper mass limit from $120$ to $300\,M_\odot$ raises the hydrogen-ionising flux by 0.3 dex during the first 2 Myr, an effect that matters for interpreting the earliest, most luminous phases of star-forming galaxies and for reionisation-era predictions. The paper also finds that metallicity barely changes early ionising flux but strongly boosts late-time flux at low metallicity, and that rotation keeps ionising fluxes higher for longer.

What carries the argument

The engine is isochrone synthesis: GENEC evolutionary tracks are interpolated track-to-track to arbitrary mass resolution and turned into isochrones, and each stellar position is assigned a spectrum from a new FASTWIND model-atmosphere grid built to cover the extended parameter space, including very massive stars. This grid replaces the WMBASIC low-resolution SED library and is matched in metallicity to the evolutionary tracks ($Z=0.0$, $0.0004$, $0.002$, $0.006$, $0.014$, $0.02$). The Python port uses SciPy and NumPy interpolation so that runtimes stay comparable to the FORTRAN version; the new very-massive-star tracks extend to $300\,M_\odot$ at low metallicity and $500\,M_\odot$ at solar metallicity, and their early hot phase is what produces the 0.3 dex ionising flux boost.

What would settle it

Re-run the same synthesis with a very-massive-star grid that includes enhanced main-sequence mass loss, or measure the ionising flux of a young star-forming region whose upper mass limit is independently known; if the predicted difference between 120 and 300 solar-mass upper limits vanishes, or observations rule out the boost, the headline claim is wrong.

Watch

Extended reading notes

Core claim

The central claim is that a modernised population synthesis code can both reproduce a well-tested legacy tool and extend it into new physical territory. Concretely, pySTARBURST99 produces SEDs that agree with STARBURST99 to within a few percent once small time-step and interpolation differences are accounted for, giving the authors confidence to adopt new GENEC tracks (including rotation and stars up to $300$–$500\,M_\odot$) and a new FASTWIND spectral library. Using these inputs, the code predicts that extending the initial-mass upper limit from $120$ to $300\,M_\odot$ increases the H I ionising flux by 0.3 dex in the first 2 Myr, that this boost disappears once the very massive stars die out within about 3 Myr, that metallicity has little effect on early H I ionising flux (0.015 dex across $Z=0.02$ to $0.0$) but lower metallicity raises later H I flux by about 1 dex, and that rotating models maintain higher ionising fluxes after 2 Myr. Similar behaviour holds for He I and He II ionising fluxes, bolometric luminosity, and wind momentum, while the H-$\alpha$ equivalent width and UV $\beta$ slope show more complex dependence on very massive stars.

Load-bearing premise

The load-bearing premise is that the evolutionary tracks for stars above 120 solar masses describe those stars correctly, even though the models do not include a general increase in mass loss for such stars while they steadily burn hydrogen in their cores; if these stars shed mass much faster than assumed, their temperatures, lifetimes, and luminosities would change, and the paper's headline 0.3 dex boost in ionising flux would change with them.

Editorial extensions

If this is right

  • Raising the upper mass limit from $120$ to $300\,M_\odot$ raises H I ionising flux by 0.3 dex in the first 2 Myr, after which the flux returns to ordinary levels once very massive stars disappear within about 3 Myr.
  • Metallicity has almost no effect on H I ionising flux before 2 Myr (0.015 dex from $Z=0.02$ to $0.0$), but after about 3 Myr lower metallicity raises the flux by roughly 1 dex, with zero-metallicity populations highest.
  • Rotating populations keep H I, He I, and He II ionising fluxes, bolometric luminosity, and wind momentum higher for longer than non-rotating populations, roughly from 3 to 10 Myr.
  • Including very massive stars boosts early wind momentum by about 0.43 to 0.47 dex, while overall wind momentum decreases toward low metallicity.
  • The H-alpha equivalent width rises with very massive stars at first but dips between about 1.6 and 2.2 Myr because those stars cool sharply, then recovers when Wolf-Rayet stars appear.

Reading between the lines

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

  • Beyond the paper's stated results, the missing general increase in main-sequence mass loss for very massive stars is the main open lever: if such mass loss is strong, the temperatures and lifetimes of $180$–$300\,M_\odot$ stars change, and the 0.3 dex early ionising flux boost could move substantially; a direct test would be to rerun the isochrones with an enhanced mass-loss prescription.
  • The paper matched FASTWIND metallicities to the evolutionary tracks, so users comparing older WMBASIC-based models (computed at $Z=0.02$ for solar) with the new ones should attribute part of any flux difference to the change in atmosphere metallicity rather than to stellar evolution alone.
  • Because binary interactions are excluded, late-time ionising flux predictions are likely lower bounds for real young populations; the paper itself notes that binary and stripped-star channels can raise ionising flux at ages beyond 10 Myr by about an order of magnitude, so combining pySTARBURST99 with binary population synthesis is a natural next test.
  • For users, a practical consequence is that the current Python release covers low-resolution SEDs and derived quantities but not high-resolution UV line profiles, so line-profile work should wait for the planned high-resolution spectral library.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper presents pySTARBURST99, a Python port of the STARBURST99 population synthesis code, and combines it with new GENEC evolutionary tracks (rotating and non-rotating, metallicities from Z=0.02 down to Z=0.0, and initial masses up to 300-500 Msol) and a new grid of FASTWIND synthetic spectra. The authors verify pySTARBURST99 against the FORTRAN version for the older GENEC/WMBASIC inputs, then use the new inputs to predict SEDs, HI/HeI/HeII ionising fluxes, bolometric luminosities, wind powers, H-alpha equivalent widths, and UV beta-slopes. The headline result is an increase in HI ionising flux of about 0.3 dex in the first 2 Myr when the upper IMF mass limit is raised from 120 to 300 Msol. The code and model grids are publicly available, with tabulated predictions in the appendix.

Significance. If the VMS-related predictions are robust, this paper provides a valuable community resource: a modern, open Python implementation of a widely used code, newly consistent low-metallicity evolution+atmosphere grids, and a clear set of falsifiable predictions for extreme star-forming populations. The explicit cross-checks against STARBURST99 in Section 3.1 and Appendix C, the tabulated output values, and the public code release are concrete strengths. The main significance risk is that the headline 0.3 dex ionising-flux boost depends on VMS evolutionary tracks that lack Eddington-enhanced mass loss and on a FASTWIND grid whose VMS coverage is not quantitatively documented; both issues are fixable with additional analysis and should be addressed before the predictions are used for quantitative inference.

major comments (3)
  1. [§2.1, §3.2, Table 2] The paper states in §2.1 that the VMS models of Martinet et al. (2023) 'do not contain a general increase in mass-loss rate for VMS on the main sequence', despite the physical expectation of Eddington-enhanced mass loss. The headline result of a ~0.3 dex increase in HI ionising flux when the upper mass limit is raised from 120 to 300 Msol (Abstract; §3.2; Table 2) depends on the temperatures, luminosities, and lifetimes of 180-300 Msol stars. If VMS mass loss is underestimated, these stars would be cooler or have shorter lifetimes, and the predicted ionising flux boost would change. Please quantify the sensitivity, for example by recomputing the isochrones with an enhanced mass-loss prescription or by applying a bracketing multiplicative factor to the VMS mass-loss rates and rerunning the synthesis. Without this, the 0.3 dex result rests on a known missing physical ingredient.
  2. [§2.2, Fig. 2] The extension of the FASTWIND grid for VMS is described only as a '33% increase in the size of the model grid' and is illustrated in Fig. 2. The paper does not provide the maximum effective temperature, luminosity, or surface gravity of the added grid points, nor does it state whether the 180-300 Msol GENEC tracks lie inside the grid or require extrapolation. Since the M300 columns of Table 2 and Fig. 7 rely on these spectra, the 0.3 dex HI ionising flux increase could be an artifact of extrapolation rather than a physical prediction. Please add a table of the grid parameter ranges (Teff, log g, mass-loss rate) for each metallicity, and show that the VMS tracks are covered by the grid or explain how interpolation/extrapolation is performed.
  3. [§3.1, Appendix C] The verification against STARBURST99 shows flux differences up to 300% at wavelengths <1000 A when both codes are evaluated at 1.01 Myr, and the agreement is recovered only by comparing the pySTARBURST99 output at 1.04 Myr. The text attributes this to the precision of the time increment, but the native time-step and its effect on the Appendix C comparisons are not quantified. Please state the time resolution of the isochrone outputs and confirm that the same 0.03 Myr offset (or similar) accounts for the residuals in all the Appendix C comparisons; otherwise the claim that pySTARBURST99 'faithfully reproduces' STARBURST99 is not fully established.
minor comments (4)
  1. [Fig. 23] The caption reads 'WMBASICspectra at Z=0.2', which appears to be a typo for Z=0.02.
  2. [§2.1] The sentence 'Available GENECevolutionary models for initial masses from from 1 to 120M⊙' contains a duplicated 'from'.
  3. [§3.3, Table 7] Please justify the choice of Z=10^-5 for the zero-metallicity terminal wind speed and state how the wind-power predictions depend on this assumed value; currently the Z0 wind-power entries in Table 7 are mostly empty, so the reader cannot assess the impact.
  4. [§2.2, §3.2] The footnote that Z0 FASTWIND models are computed with Z=10^-6 should be referenced explicitly when discussing the Z0 columns of Table 2, since the abstract and §3.2 describe these as zero-metallicity predictions; the paper's argument that Q(H) is insensitive to input metallicity for fixed stellar parameters mitigates this, but the statement should be made at the point of the Z0 predictions.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the headline predictions are forward-model outputs from external evolutionary tracks and newly computed atmosphere grids, with no fitted target quantity.

full rationale

The central derivation chain in pySTARBURST99 is a forward population-synthesis calculation: GENEC evolutionary tracks (including the VMS tracks of Martinet et al. 2023) supply stellar parameters as a function of time and initial mass, FASTWIND model atmospheres supply SEDs as functions of those parameters, and the code integrates these over a Kroupa IMF. The claimed 0.3 dex increase in H I ionising flux when the upper mass limit is raised from 120 to 300 Msol is obtained by re-running this same forward chain with a different IMF upper cutoff; no parameter is fitted to that flux value and no output quantity is used in the definition of an input. The code cross-check against the original FORTRAN STARBURST99 (Sect. 3.1, Figs. 1 and 3) is a genuine independent reproduction test using the old inputs and does not enter the new predictions. The many GENEC-affiliated authors are a normal overlap, not load-bearing circularity: the cited tracks are published, parameter-free model grids with stated physics assumptions (Sect. 2.1), and the paper explicitly flags the missing Eddington-enhanced mass-loss for VMS as a limitation rather than silently importing it. Similarly, the use of Z=1e-6 in FASTWIND for the 'zero' metallicity models (Sect. 2.2) and the lack of detailed observational comparison (Sect. 4) are acknowledged modeling compromises and validation gaps, not cases where an output is equivalent to an input by construction.

Assumptions & free parameters 2 free parameters · 3 assumptions · 0 invented entities

No new physical entities are introduced. The free parameters are numerical proxies to handle zero metallicity in codes that require nonzero Z. The predictions depend on externally developed evolution and atmosphere models, plus internally generated FASTWIND spectra.

free parameters (2)
  • Adopted metallicity for zero-metallicity terminal wind speed = Z=10^-5
    Used to estimate v_inf for Z=0 populations in wind power predictions (Sect. 3.3); the paper states there are no v_inf estimates for zero metallicity.
  • FASTWIND proxy metallicity for zero-metallicity spectra = Z=10^-6
    FASTWIND cannot accept Z=0.0, so Z=10^-6 is used for numerical reasons (Sect. 2.2, footnote 2).
assumptions (3)
  • domain assumption The GENEC stellar evolution tracks, including the new VMS tracks, correctly represent the physical properties of massive stars across Z=0.02 to 0.0 and up to 500 Msun.
    All population outputs depend on these tracks; many track authors are co-authors. The paper notes the VMS tracks omit a general Eddington-enhanced mass-loss rate (Sect. 2.1).
  • domain assumption The FASTWIND synthetic atmosphere grid with prescribed beta-velocity law and no tailored mass-loss rates yields SEDs accurate enough for integrated ionising fluxes.
    Invoked in Sect. 2.2; the paper argues wind clumping and X-rays have little impact on integrated SEDs but does not quantify this for ionising flux.
  • domain assumption Single-star evolution without binary interactions is sufficient for the quantities presented here.
    The paper itself flags binaries can increase late-time ionising flux by an order of magnitude (Sect. 4). This limits the generalizability of later-time predictions.

how reviews work

0 comments
Cite this review

Pith. "Pith review of pySTARBURST99: The Next Generation of STARBURST99." pith.science (2026). https://pith.science/paper/NFNCMJBA

@misc{pith2026250524841,
  author       = {Pith},
  title        = {Pith review of: pySTARBURST99: The Next Generation of STARBURST99},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NFNCMJBA}},
  note         = {Machine review of arXiv:2505.24841}
}
read the original abstract

STARBURST99 is a population synthesis code tailored to predict the integrated properties or observational characteristics of star-forming galaxies. Here we present an update to STARBURST99 where we port the code to python, include new evolutionary tracks both rotating and non-rotating at a range of low metallicity environments. We complement these tracks with a corresponding grid of new synthetic SEDs. Additionally we include both evolutionary and spectral models of stars up to 300-500Msol. Synthesis models made with the python version of the code and new input stellar models are labelled pySTARBURST99. We make new predictions for many properties, such as ionising flux, SED, bolometric luminosity, wind power, hydrogen line equivalent widths and the UV beta-slope. These properties are all assessed over wider coverage in metallicity, mass and resolution than in previous versions of STARBURST99. A notable finding from these updates is an increase in H I ionising flux of 0.3 dex in the first 2Myr when increasing the upper mass limit from 120 to 300Msol. Changing metallicity has little impact on H I in the first 2Myr (range of 0.015 dex from Z = 0.02 to 0.0) but lower metallicities have higher H I by 1 dex (comparing Z = 0.02 to 0.0004) at later times, with Z = 0.0 having even higher H I at later times. Rotating models have significantly higher H I than their equivalent non-rotating models at any time after 2Myr. Similar trends are found for He I and He II, bolometric luminosity and wind momentum, with more complex relations found for hydrogen line equivalent widths and UV beta-slopes.

Figures

Figures reproduced from arXiv: 2505.24841 by the authors.

Figure 1
Figure 1. Isochrones computed with Z = 0.014 GENEC tracks without rotation from 1-4 Myr. The tracks in red are produced with STARBURST99 and the tracks in black are produced with pySTARBURST99, showing good agreement between the two code versions. mass-loss rate for VMS on the main sequence, which would be physically motivated by proximity to the Eddington limit (Grafener & Hamann ¨ 2008; Vink et al. 2011; Bestenlehner et al.… view at source ↗
Figure 2
Figure 2. Example of grid coverage for SED predictions with ex￾tension for VMS at Z = 0.014. GENEC evolutionary tracks are overplotted at regular intervals from 9-500M⊙. This coverage is available for all metallicities. A similar level of coverage is avail￾able at zero-metallicity where the tracks are much hotter than any others. 2.3. Python In translating the code to python from FORTRAN, our pri￾mary goal is to increase the … view at source ↗
Figure 3
Figure 3. Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99 in both cases utilising the Ekstrom et al. ¨ (2012) stellar evolutionary models at Z=0.014 and WMBASIC spectra at Z=0.02. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr. minosity is held constant for this comparison, showing the effect of lower metallicity resulting in overall higher temper￾atures for the s… view at source ↗
Figures from the paper (38 more)
Figure 5
Figure 5. Figure 5: Low resolution synthetic SEDs with metallicities rep￾resentative of populations in the Galactic centre to zero metallic￾ity. These are produced at 2Myr using pySTARBURST99 with the GENEC tracks, new FASTWIND model grid, an upper mass limit of 120M⊙ and no rotation. et …
Figure 4
Figure 4. Figure 4: Synthetic FUV SEDs, utilising the Ekstrom et al. ¨ (2012) stellar evolutionary models at Z = 0.014 for both, with WMBASIC spectra at Z = 0.02 compared with FASTWIND spectra at Z = 0.014. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr. there…
Figure 6
Figure 6. Figure 6: Synthetic FUV SEDs from pySTARBURST99, utilising the Ekstrom et al. ¨ (2012) stellar evolutionary models at Z=0.014 and FASTWIND spectra at Z=0.014. This is compared with the ad￾dition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and FASTWIND mode…
Figure 9
Figure 9. Figure 9 [PITH_FULL_IMAGE:figures/full_fig_p010_9.png]
Figure 10
Figure 10. Figure 10: As described in [PITH_FULL_IMAGE:figures/full_fig_p011_10.png]
Figure 12
Figure 12. Figure 12: As described in [PITH_FULL_IMAGE:figures/full_fig_p012_12.png]
Figure 13
Figure 13. Figure 13: As described in [PITH_FULL_IMAGE:figures/full_fig_p012_13.png]
Figure 14
Figure 14. Figure 14: Wind momentum fluxes over time for a typical sin￾gle stellar population with upper mass limit of 120M⊙, no rotation comparing STARBURST99 with pySTARBURST99 and a few other mass loss and terminal wind speed recipes on the main sequence. dust attenuation, making it a p…
Figure 15
Figure 15. Figure 15: UV slopes computed from synthetic FUV SEDs, within the range 1250-1750A, including the contribution from the nebular ˚ continuum. populations. We are now able to offer an updated metal￾licity grid (Z = 0.02, 0.014, 0.006, 0.002, 0.0004 and 0.0) and an extended upper m…
Figure 16
Figure 16. Figure 16: As described in [PITH_FULL_IMAGE:figures/full_fig_p022_16.png]
Figure 17
Figure 17. Figure 17: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Yusof et al. (2022) stellar evolutionary models at Z = 0.02 and WMBASIC spectra at Z = 0.02. The evolution with time is shown from 1 Myr to 10 Myr at interva…
Figure 18
Figure 18. Figure 18: Synthetic FUV SEDs, utilising the Yusof et al. (2022) stellar evolutionary models at Z = 0.02 for both, with WMBASIC spectra at Z = 0.02 compared with FASTWIND spectra at Z = 0.02. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr [PITH_FULL…
Figure 19
Figure 19. Figure 19: Synthetic FUV SEDs from pySTARBURST99, utilising the Yusof et al. (2022) stellar evolutionary models at Z=0.02 and FASTWIND spectra at Z=0.02. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and FASTWIND models tai…
Figure 20
Figure 20. Figure 20: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Yusof et al. (2022) stellar evolutionary models including rotation at Z = 0.02 and WMBASIC spectra at Z = 0.02. The evolution with time is shown from 1 Myr t…
Figure 21
Figure 21. Figure 21: Synthetic FUV SEDs, utilising the Yusof et al. (2022) stellar evolutionary models at Z = 0.02 with rotation for both, with WMBASIC spectra at Z = 0.02 compared with FASTWIND spectra at Z = 0.02. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 M…
Figure 22
Figure 22. Figure 22: Synthetic FUV SEDs from pySTARBURST99, utilising the Yusof et al. (2022) stellar evolutionary models at Z=0.02 with rotation and FASTWIND spectra at Z=0.02. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and FASTW…
Figure 23
Figure 23. Figure 23: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Ekstrom¨ et al. (2012) stellar evolutionary models including rotation at Z=0.014 and WMBASIC spectra at Z=0.2. The evolution with time is shown from 1 Myr to…
Figure 24
Figure 24. Figure 24: Synthetic FUV SEDs, utilising the Ekstrom et al. ¨ (2012) stellar evolutionary models at Z = 0.014 with rotation for both, with WMBASIC spectra at Z = 0.02 compared with FASTWIND spectra at Z = 0.014. The evolution with time is shown from 1 Myr to 10 Myr at intervals …
Figure 25
Figure 25. Figure 25: Synthetic FUV SEDs from pySTARBURST99, utilising the Ekstrom et al. ¨ (2012) stellar evolutionary models at Z=0.014 with rotation and FASTWIND spectra at Z=0.014. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and…
Figure 26
Figure 26. Figure 26: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Eggen￾berger et al. (2021) stellar evolutionary models at Z=0.006 and WMBASIC spectra at Z=0.008. The evolution with time is shown from 1 Myr to 10 Myr at in…
Figure 27
Figure 27. Figure 27: Synthetic FUV SEDs, utilising the Eggenberger et al. (2021) stellar evolutionary models at Z = 0.006 for both, with WMBASIC spectra at Z = 0.008 compared with FASTWIND spectra at Z = 0.006. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr […
Figure 28
Figure 28. Figure 28: Synthetic FUV SEDs from pySTARBURST99, utilising the Eggenberger et al. (2021) stellar evolutionary models at Z = 0.006 and FASTWIND spectra at Z = 0.006. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and FASTWIN…
Figure 29
Figure 29. Figure 29: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Eggen￾berger et al. (2021) stellar evolutionary models including rotation at Z = 0.006 and WMBASIC spectra at Z = 0.008. The evolution with time is shown fro…
Figure 30
Figure 30. Figure 30: Synthetic FUV SEDs, utilising the Eggenberger et al. (2021) stellar evolutionary models at Z = 0.006 with rotation for both, with WMBASIC spectra at Z = 0.008 compared with FASTWIND spectra at Z = 0.006. The evolution with time is shown from 1 Myr to 10 Myr at interva…
Figure 31
Figure 31. Figure 31: Synthetic FUV SEDs from pySTARBURST99, utilising the Eggenberger et al. (2021) stellar evolutionary models at Z = 0.006 with rotation and FASTWIND spectra at Z = 0.006. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (202…
Figure 32
Figure 32. Figure 32: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Georgy et al. (2013) stellar evolutionary models at Z = 0.002 and WMBASIC spectra at Z = 0.004. The evolution with time is shown from 1 Myr to 10 Myr at inte…
Figure 33
Figure 33. Figure 33: Synthetic FUV SEDs, utilising the Georgy et al. (2013) stellar evolutionary models at Z = 0.002 for both, with WMBASIC spectra at Z = 0.004 compared with FASTWIND spectra at Z = 0.002. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr [PITH_…
Figure 34
Figure 34. Figure 34: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Georgy et al. (2013) stellar evolutionary models at Z = 0.002 with rotation and WMBASIC spectra at Z = 0.004. The evolution with time is shown from 1 Myr to …
Figure 35
Figure 35. Figure 35: Synthetic FUV SEDs, utilising the Georgy et al. (2013) stellar evolutionary models at Z = 0.002 with rotation for both, with WMBASIC spectra at Z = 0.004 compared with FASTWIND spectra at Z = 0.002. The evolution with time is shown from 1 Myr to 10 Myr at intervals of…
Figure 36
Figure 36. Figure 36: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Groh et al. (2019) stellar evolutionary models at Z = 0.0004 and WMBASIC spectra at Z = 0.001. The evolution with time is shown from 1 Myr to 10 Myr at inter…
Figure 37
Figure 37. Figure 37: Synthetic FUV SEDs, utilising the Groh et al. (2019) stellar evolutionary models at Z = 0.0004 for both, with WMBASIC spectra at Z = 0.001 compared with FASTWIND spectra at Z = 0.004. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr [PITH_F…
Figure 38
Figure 38. Figure 38: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Groh et al. (2019) stellar evolutionary models at Z = 0.0004 with rotation and WMBASIC spectra at Z = 0.001. The evolution with time is shown from 1 Myr to 1…
Figure 39
Figure 39. Figure 39: Synthetic FUV SEDs, utilising the Groh et al. (2019) stellar evolutionary models at Z = 0.0004 with rotation for both, with WMBASIC spectra at Z = 0.001 compared with FASTWIND spectra at Z = 0.004. The evolution with time is shown from 1 Myr to 10 Myr at intervals of …
Figure 40
Figure 40. Figure 40: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Murphy et al. (2021) stellar evolutionary models at Z = 0.0 and WMBASIC spectra at Z = 0.001. The evolution with time is shown from 1 Myr to 10 Myr at interv…
Figure 41
Figure 41. Figure 41: Synthetic FUV SEDs, utilising the Murphy et al. (2021) stellar evolutionary models at Z = 0.0 for both, with WMBASIC spectra at Z = 0.001 compared with FASTWIND spectra at Z = 1E − 6. The evolution with time is shown from 1 Myr to 10 Myr at intervals of 1 Myr [PITH_F…
Figure 42
Figure 42. Figure 42: Synthetic FUV SEDs from pySTARBURST99, utilising the Murphy et al. (2021) stellar evolutionary models at Z = 0.0 and FASTWIND spectra at Z = 1E − 6. This is compared with the addition of VMS evolutionary tracks up to 300M⊙ from Martinet et al. (2023) and FASTWIND mode…
Figure 43
Figure 43. Figure 43: Synthetic FUV SEDs from STARBURST99 compared to those produced with pySTARBURST99, in both cases utilising the Murphy et al. (2021) stellar evolutionary models with rotation at Z=0.0 and WMBASIC spectra at Z = 0.001. The evolution with time is shown from 1 Myr to 10 M…
Figure 44
Figure 44. Figure 44: Synthetic FUV SEDs, utilising the Murphy et al. (2021) stellar evolutionary models with rotation at Z = 0.0 for both, with WMBASIC spectra at Z = 0.001 compared with FASTWIND spectra at Z = 1E − 6. The evolution with time is shown from 1 Myr to 10 Myr at intervals of …

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 4 Pith papers

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

  1. The COLIBRE-SKIRT pipeline: Calibration-free dust radiative transfer postprocessing for cosmological simulations

    astro-ph.GA 2026-07 conditional novelty 7.0 of 10

    The COLIBRE-SKIRT pipeline reproduces the observed low-redshift cosmic SED without calibrating the post-processing, using live dust from the simulation and a new 'split & scale' grain-size mapping.

  2. Unveiling Metal Mixing in a Grand-Design Spiral: A UV-optical multiphase spatially resolved study of M83

    astro-ph.GA 2026-08 conditional novelty 6.0 of 10

    Multiphase abundance mapping of M83 reveals a persistent roughly 1.5 dex nitrogen excess in ionized gas relative to neutral gas around young clusters, indicating slow metal mixing in a massive spiral.

  3. On the detection of Population III galaxies: Emission Line Diagnostics for Hybrid Stellar Populations

    astro-ph.GA 2026-07 conditional novelty 5.0 of 10

    Existing HeII emission-line diagnostics identify pure Pop III galaxies but fail for hybrid Pop III/Pop II systems, introducing spectral degeneracies that hide residual first stars.

  4. The Mysterious Case of Iron in XMPs: Anomalous High log(Fe/O) Observed in Extremely Metal-Poor Galaxies HSCJ1631+4426 and SDSSJ0811+4730

    astro-ph.GA 2026-07 conditional novelty 4.0 of 10

    New KCWI spectroscopy of two ultra-low-metallicity galaxies shows Fe/O ratios near solar, implying enrichment by bright hypernovae or pair-instability supernovae.

Reference graph

Works this paper leans on

141 extracted references · 12 canonical work pages · cited by 4 Pith papers

  1. [1]

    2021, in MOBSTER-1 virtual conference: Stellar Variability as a Probe of Magnetic Fields in Massive Stars, 22, 10.5281/zenodo.5525465

    Agrawal , P., Hurley , J., Stevenson , S., Sz \'e csi , D., & Flynn , C. 2021, in MOBSTER-1 virtual conference: Stellar Variability as a Probe of Magnetic Fields in Massive Stars, 22, 10.5281/zenodo.5525465

    work page doi:10.5281/zenodo.5525465 2021

  2. [2]

    J., & Scott , P

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

    arXiv 2009

  3. [3]

    A., de Koter , A., et al

    Backs , F., Brands , S. A., de Koter , A., et al. 2024, arXiv e-prints, arXiv:2411.06884, 10.48550/arXiv.2411.06884

    arXiv doi:10.48550/arxiv.2411.06884 2024

  4. [4]

    A., James , B

    Berg , D. A., James , B. L., King , T., et al. 2022, , 261, 31, 10.3847/1538-4365/ac6c03

    doi:10.3847/1538-4365/ac6c03 2022

  5. [5]

    A., Skillman , E

    Berg , D. A., Skillman , E. D., Chisholm , J., et al. 2024, , 971, 87, 10.3847/1538-4357/ad5292

    doi:10.3847/1538-4357/ad5292 2024

  6. [6]

    M., Gr \" a fener, G., Vink, J

    Bestenlehner, J. M., Gr \" a fener, G., Vink, J. S., et al. 2014, The VLT-FLAMES tarantula survey: XVII. Physical and wind properties of massive stars at the top of the main sequence , EDP Sciences, 10.1051/0004-6361/201423643

    doi:10.1051/0004-6361/201423643 2014

  7. [7]

    M., Crowther , P

    Bestenlehner , J. M., Crowther , P. A., Caballero-Nieves , S. M., et al. 2020, , 499, 1918, 10.1093/mnras/staa2801

    doi:10.1093/mnras/staa2801 2020

  8. [8]

    O., Puls , J., & Najarro , F

    Bj \"o rklund , R., Sundqvist , J. O., Puls , J., & Najarro , F. 2021, , 648, A36, 10.1051/0004-6361/202038384

    doi:10.1051/0004-6361/202038384 2021

Show all 141 references
  1. [9]

    2019, , 622, A103, 10.1051/0004-6361/201834156

    Boquien , M., Burgarella , D., Roehlly , Y., et al. 2019, , 622, A103, 10.1051/0004-6361/201834156

    2019 doi

  2. [10]

    C., Lanz , T., Hillier , D

    Bouret , J. C., Lanz , T., Hillier , D. J., et al. 2015, , 449, 1545, 10.1093/mnras/stv379

    2015 doi

  3. [11]

    A., de Koter , A., Bestenlehner , J

    Brands , S. A., de Koter , A., Bestenlehner , J. M., et al. 2022, , 663, A36, 10.1051/0004-6361/202142742

    2022 doi

  4. [12]

    S., Berger , E., Neijssel , C

    Broekgaarden , F. S., Berger , E., Neijssel , C. J., et al. 2021, , 508, 5028, 10.1093/mnras/stab2716

    2021 doi

  5. [13]

    E., Cantiello , M., et al

    Brott , I., de Mink , S. E., Cantiello , M., et al. 2011, , 530, A115, 10.1051/0004-6361/201016113

    2011 doi

  6. [14]

    2003, , 344, 1000, 10.1046/j.1365-8711.2003.06897.x

    Bruzual , G., & Charlot , S. 2003, , 344, 1000, 10.1046/j.1365-8711.2003.06897.x

    2003

  7. [15]

    J., Conroy , C., & Johnson , B

    Byler , N., Dalcanton , J. J., Conroy , C., & Johnson , B. D. 2017, , 840, 44, 10.3847/1538-4357/aa6c66

    2017 doi

  8. [16]

    M., Eldridge , J

    Byrne , C. M., Eldridge , J. J., & Stanway , E. R. 2025, , 537, 2433, 10.1093/mnras/staf178

    2025 doi

  9. [17]

    L., & Storchi-Bergmann , T

    Calzetti , D., Kinney , A. L., & Storchi-Bergmann , T. 1994, , 429, 582, 10.1086/174346

    1994 doi

  10. [18]

    J., Katz , H., Rey , M

    Cameron , A. J., Katz , H., Rey , M. P., & Saxena , A. 2023, , 523, 3516, 10.1093/mnras/stad1579

    2023 doi

  11. [19]

    P., Puls, J., Sundqvist, J

    Carneiro, L. P., Puls, J., Sundqvist, J. O., & Hoffmann, T. L. 2016, Astronomy and Astrophysics, 590, 10.1051/0004-6361/201527718

    2016 doi

  12. [20]

    2015, , 452, 1068, 10.1093/mnras/stv1281

    Chen , Y., Bressan , A., Girardi , L., et al. 2015, , 452, 1068, 10.1093/mnras/stv1281

    2015 doi

  13. [21]

    2018, , 616, A30, 10.1051/0004-6361/201832758

    Chisholm , J., Gazagnes , S., Schaerer , D., et al. 2018, , 616, A30, 10.1051/0004-6361/201832758

    2018 doi

  14. [22]

    2016, , 823, 102, 10.3847/0004-637X/823/2/102

    Choi , J., Dotter , A., Conroy , C., et al. 2016, , 823, 102, 10.3847/0004-637X/823/2/102

    2016 doi

  15. [23]

    Conroy , C., & Gunn , J. E. 2010, , 712, 833, 10.1088/0004-637X/712/2/833

    2010 doi

  16. [24]

    E., & White , M

    Conroy , C., Gunn , J. E., & White , M. 2009, , 699, 486, 10.1088/0004-637X/699/1/486

    2009 doi

  17. [25]

    A., & Castro , N

    Crowther , P. A., & Castro , N. 2024, , 527, 9023, 10.1093/mnras/stad3698

    2024 doi

  18. [26]

    A., Schnurr , O., Hirschi , R., et al

    Crowther , P. A., Schnurr , O., Hirschi , R., et al. 2010, , 408, 731, 10.1111/j.1365-2966.2010.17167.x

    2010

  19. [27]

    A., Caballero-Nieves , S

    Crowther , P. A., Caballero-Nieves , S. M., Bostroem , K. A., et al. 2016, , 458, 624, 10.1093/mnras/stw273

    2016 doi

  20. [28]

    E., McLure , R

    Cullen , F., Shapley , A. E., McLure , R. J., et al. 2021, , 505, 903, 10.1093/mnras/stab1340

    2021 doi

  21. [29]

    C., Scholte , D., et al

    Cullen , F., Carnall , A. C., Scholte , D., et al. 2025, arXiv e-prints, arXiv:2501.11099, 10.48550/arXiv.2501.11099

    2025 doi arXiv

  22. [30]

    de Jager , C., Nieuwenhuijzen , H., & van der Hucht , K. A. 1988, , 72, 259

    1988

  23. [31]

    2016, , 222, 8, 10.3847/0067-0049/222/1/8

    Dotter , A. 2016, , 222, 8, 10.3847/0067-0049/222/1/8

    2016 doi

  24. [32]

    2024, arXiv e-prints, arXiv:2412.01623, 10.48550/arXiv.2412.01623

    Dottorini , D., Calabr \`o , A., Pentericci , L., et al. 2024, arXiv e-prints, arXiv:2412.01623, 10.48550/arXiv.2412.01623

    2024 doi arXiv

  25. [33]

    2021, , 652, A137, 10.1051/0004-6361/202141222

    Eggenberger , P., Ekstr \"o m , S., Georgy , C., et al. 2021, , 652, A137, 10.1051/0004-6361/202141222

    2021 doi

  26. [34]

    2012, , 537, A146, 10.1051/0004-6361/201117751

    Ekstr \"o m , S., Georgy , C., Eggenberger , P., et al. 2012, , 537, A146, 10.1051/0004-6361/201117751

    2012 doi

  27. [35]

    J., & Stanway , E

    Eldridge , J. J., & Stanway , E. R. 2022, arXiv e-prints, arXiv:2202.01413. 2202.01413

    2022 arXiv

  28. [36]

    J., Stanway , E

    Eldridge , J. J., Stanway , E. R., Xiao , L., et al. 2017, , 34, e058, 10.1017/pasa.2017.51

    2017 doi

  29. [37]

    J., & Tout , C

    Eldridge , J. J., & Tout , C. A. 2004, , 353, 87, 10.1111/j.1365-2966.2004.08041.x

    2004

  30. [38]

    F., Najarro , F., Gilmore , D., et al

    Figer , D. F., Najarro , F., Gilmore , D., et al. 2002, , 581, 258, 10.1086/344154

    2002 doi

  31. [39]

    R., Jaskot , A

    Flury , S. R., Jaskot , A. E., Ferguson , H. C., et al. 2022, , 260, 1, 10.3847/1538-4365/ac5331

    2022 doi

  32. [40]

    J., Bavera , S

    Fragos , T., Andrews , J. J., Bavera , S. S., et al. 2023, , 264, 45, 10.3847/1538-4365/ac90c1

    2023 doi

  33. [41]

    P., Chisholm , J., et al

    Fujimoto , S., Naidu , R. P., Chisholm , J., et al. 2025, arXiv e-prints, arXiv:2501.11678, 10.48550/arXiv.2501.11678

    2025 doi arXiv

  34. [42]

    J., & Alejandro Urbaneja , M

    Garcia , M., Herrero , A., Najarro , F., Lennon , D. J., & Alejandro Urbaneja , M. 2014, , 788, 64, 10.1088/0004-637X/788/1/64

    2014 doi

  35. [43]

    A., et al

    Geen , S., Agrawal , P., Crowther , P. A., et al. 2023, , 135, 021001, 10.1088/1538-3873/acb6b5

    2023 doi

  36. [44]

    2013, , 558, A103, 10.1051/0004-6361/201322178

    Georgy , C., Ekstr \"o m , S., Eggenberger , P., et al. 2013, , 558, A103, 10.1051/0004-6361/201322178

    2013 doi

  37. [45]

    E., Groh , J

    G \"o tberg , Y., de Mink , S. E., Groh , J. H., Leitherer , C., & Norman , C. 2019, , 629, A134, 10.1051/0004-6361/201834525

    2019 doi

  38. [46]

    E., McQuinn , M., et al

    G \"o tberg , Y., de Mink , S. E., McQuinn , M., et al. 2020, , 634, A134, 10.1051/0004-6361/201936669

    2020 doi

  39. [47]

    Gr \"a fener , G., & Hamann , W. R. 2008, , 482, 945, 10.1051/0004-6361:20066176

    2008 doi

  40. [48]

    Gr \" a fener, G., Koesterke, L., & Hamann, W. R. 2002, Astronomy and Astrophysics, 387, 244, 10.1051/0004-6361:20020269

    2002 doi

  41. [49]

    S., & Kewley , L

    Grasha , K., Roy , A., Sutherland , R. S., & Kewley , L. J. 2021, , 908, 241, 10.3847/1538-4357/abd6bf

    2021 doi

  42. [50]

    H., Ekstr \"o m , S., Georgy , C., et al

    Groh , J. H., Ekstr \"o m , S., Georgy , C., et al. 2019, , 627, A24, 10.1051/0004-6361/201833720

    2019 doi

  43. [51]

    2019, , 621, A85, 10.1051/0004-6361/201833787

    Hainich , R., Ramachandran , V., Shenar , T., et al. 2019, , 621, A85, 10.1051/0004-6361/201833787

    2019 doi

  44. [52]

    2024 a , , 688, A105, 10.1051/0004-6361/202245588

    Hawcroft , C., Sana , H., Mahy , L., et al. 2024 a , , 688, A105, 10.1051/0004-6361/202245588

    2024 doi

  45. [53]

    2024 b , , 690, A126, 10.1051/0004-6361/202348478

    Hawcroft , C., Mahy , L., Sana , H., et al. 2024 b , , 690, A126, 10.1051/0004-6361/202348478

    2024 doi

  46. [54]

    J., & Miller, D

    Hillier, D. J., & Miller, D. L. 1998, The Astrophysical Journal, 496, 407, 10.1086/305350

    1998 doi

  47. [55]

    I., Schaerer , D., Thuan , T

    Izotov , Y. I., Schaerer , D., Thuan , T. X., et al. 2016, , 461, 3683, 10.1093/mnras/stw1205

    2016 doi

  48. [56]

    M., Horch , E

    Kalari , V. M., Horch , E. P., Salinas , R., et al. 2022, , 935, 162, 10.3847/1538-4357/ac8424

    2022 doi

  49. [57]

    2022, , 259, 21, 10.3847/1538-4365/ac426d

    Kimm , T., Bieri , R., Geen , S., et al. 2022, , 259, 21, 10.3847/1538-4365/ac426d

    2022 doi

  50. [58]

    2015, , 573, A71, 10.1051/0004-6361/201424356

    K \"o hler , K., Langer , N., de Koter , A., et al. 2015, , 573, A71, 10.1051/0004-6361/201424356

    2015 doi

  51. [59]

    2009, , 396, 462, 10.1111/j.1365-2966.2009.14717.x

    Kotulla , R., Fritze , U., Weilbacher , P., & Anders , P. 2009, , 396, 462, 10.1111/j.1365-2966.2009.14717.x

    2009

  52. [60]

    2002, Science, 295, 82, 10.1126/science.1067524

    Kroupa , P. 2002, Science, 295, 82, 10.1126/science.1067524

    2002 doi

  53. [61]

    2017, , 606, A31, 10.1051/0004-6361/201730723

    Krti c ka , J., & Kub \'a t , J. 2017, , 606, A31, 10.1051/0004-6361/201730723

    2017 doi

  54. [62]

    R., Fumagalli , M., da Silva , R

    Krumholz , M. R., Fumagalli , M., da Silva , R. L., Rendahl , T., & Parra , J. 2015, , 452, 1447, 10.1093/mnras/stv1374

    2015 doi

  55. [63]

    2000, , 38, 613, 10.1146/annurev.astro.38.1.613

    Kudritzki , R.-P., & Puls , J. 2000, , 38, 613, 10.1146/annurev.astro.38.1.613

    2000 doi

  56. [64]

    2024, arXiv e-prints, arXiv:2406.11997, 10.48550/arXiv.2406.11997

    Kumari , N., Smit , R., Witstok , J., et al. 2024, arXiv e-prints, arXiv:2406.11997, 10.48550/arXiv.2406.11997

    2024 doi arXiv

  57. [65]

    2023, , 678, A60, 10.1051/0004-6361/202347179

    Kummer , F., Toonen , S., & de Koter , A. 2023, , 678, A60, 10.1051/0004-6361/202347179

    2023 doi

  58. [66]

    2012, , 50, 107, 10.1146/annurev-astro-081811-125534

    Langer , N. 2012, , 50, 107, 10.1146/annurev-astro-081811-125534

    2012 doi

  59. [67]

    2004, , 425, 881, 10.1051/0004-6361:200400044

    Le Borgne , D., Rocca-Volmerange , B., Prugniel , P., et al. 2004, , 425, 881, 10.1051/0004-6361:200400044

    2004 doi

  60. [68]

    2024, , 527, 9480, 10.1093/mnras/stad3838

    Lecroq , M., Charlot , S., Bressan , A., et al. 2024, , 527, 9480, 10.1093/mnras/stad3838

    2024 doi

  61. [69]

    2020, Galaxies, 8, 13, 10.3390/galaxies8010013

    Leitherer , C. 2020, Galaxies, 8, 13, 10.3390/galaxies8010013

    2020 doi

  62. [70]

    2014, , 212, 14, 10.1088/0067-0049/212/1/14

    Leitherer , C., Ekstr \"o m , S., Meynet , G., et al. 2014, , 212, 14, 10.1088/0067-0049/212/1/14

    2014 doi

  63. [71]

    A., Bresolin , F., et al

    Leitherer , C., Ortiz Ot \'a lvaro , P. A., Bresolin , F., et al. 2010, , 189, 309, 10.1088/0067-0049/189/2/309

    2010 doi

  64. [72]

    1992, , 401, 596, 10.1086/172089

    Leitherer , C., Robert , C., & Drissen , L. 1992, , 401, 596, 10.1086/172089

    1992 doi

  65. [73]

    D., et al

    Leitherer , C., Schaerer , D., Goldader , J. D., et al. 1999, , 123, 3, 10.1086/313233

    1999 doi

  66. [74]

    1997, , 125, 229, 10.1051/aas:1997373

    Lejeune , T., Cuisinier , F., & Buser , R. 1997, , 125, 229, 10.1051/aas:1997373

    1997 doi

  67. [75]

    M., Leitherer , C., Ekstrom , S., Meynet , G., & Schaerer , D

    Levesque , E. M., Leitherer , C., Ekstrom , S., Meynet , G., & Schaerer , D. 2012, , 751, 67, 10.1088/0004-637X/751/1/67

    2012 doi

  68. [76]

    2024, arXiv e-prints, arXiv:2412.01358, 10.48550/arXiv.2412.01358

    Llerena , M., Pentericci , L., Napolitano , L., et al. 2024, arXiv e-prints, arXiv:2412.01358, 10.48550/arXiv.2412.01358

    2024 doi arXiv

  69. [77]

    E., Clark , J

    Lohr , M. E., Clark , J. S., Najarro , F., et al. 2018, , 617, A66, 10.1051/0004-6361/201832670

    2018 doi

  70. [78]

    1994, , 287, 803

    Maeder , A., & Meynet , G. 1994, , 287, 803

    1994

  71. [79]

    2000, , 361, 159, 10.48550/arXiv.astro-ph/0006405

    ---. 2000, , 361, 159, 10.48550/arXiv.astro-ph/0006405

    2000 doi arXiv

  72. [80]

    2024, , 62, 21, 10.1146/annurev-astro-052722-105936

    Marchant , P., & Bodensteiner , J. 2024, , 62, 21, 10.1146/annurev-astro-052722-105936

    2024 doi

  73. [81]

    2017, , 604, A55, 10.1051/0004-6361/201630188

    Marchant , P., Langer , N., Podsiadlowski , P., et al. 2017, , 604, A55, 10.1051/0004-6361/201630188

    2017 doi

  74. [82]

    Marcolino , W. L. F., Bouret , J. C., Rocha-Pinto , H. J., Bernini-Peron , M., & Vink , J. S. 2022, , 511, 5104, 10.1093/mnras/stac452

    2022 doi

  75. [83]

    O., et al

    Marques-Chaves , R., Schaerer , D., Amor \' n , R. O., et al. 2022, , 663, L1, 10.1051/0004-6361/202243598

    2022 doi

  76. [84]

    2023, , 679, A137, 10.1051/0004-6361/202347514

    Martinet , S., Meynet , G., Ekstr \"o m , S., Georgy , C., & Hirschi , R. 2023, , 679, A137, 10.1051/0004-6361/202347514

    2023 doi

  77. [85]

    J., Paumard , T., et al

    Martins , F., Hillier , D. J., Paumard , T., et al. 2008, , 478, 219, 10.1051/0004-6361:20078469

    2008 doi

  78. [86]

    2022, arXiv e-prints, arXiv:2202.13703

    Martins , F., & Palacios , A. 2022, arXiv e-prints, arXiv:2202.13703. 2202.13703

    2022 arXiv

  79. [87]

    2025, arXiv e-prints, arXiv:2505.02993, 10.48550/arXiv.2505.02993

    Martins , F., Palacios , A., Schaerer , D., & Marques-Chaves , R. 2025, arXiv e-prints, arXiv:2505.02993, 10.48550/arXiv.2505.02993

    2025 doi arXiv

  80. [88]

    2023, , 678, A159, 10.1051/0004-6361/202346732

    Martins , F., Schaerer , D., Marques-Chaves , R., & Upadhyaya , A. 2023, , 678, A159, 10.1051/0004-6361/202346732

    2023 doi

  81. [89]

    2023, , 673, A50, 10.1051/0004-6361/202345895

    Me s tri \'c , U., Vanzella , E., Upadhyaya , A., et al. 2023, , 673, A50, 10.1051/0004-6361/202345895

    2023 doi

  82. [90]

    2021, , 506, 4781, 10.1093/mnras/stab1969

    Mill \'a n-Irigoyen , I., Moll \'a , M., Cervi \ n o , M., et al. 2021, , 506, 4781, 10.1093/mnras/stab1969

    2021 doi

  83. [91]

    R., Mart \' n-Hern \'a ndez , N

    Mokiem , M. R., Mart \' n-Hern \'a ndez , N. L., Lenorzer , A., de Koter , A., & Tielens , A. G. G. M. 2004, , 419, 319, 10.1051/0004-6361:20040074

    2004 doi

  84. [92]

    R., de Koter , A., Vink , J

    Mokiem , M. R., de Koter , A., Vink , J. S., et al. 2007, , 473, 603, 10.1051/0004-6361:20077545

    2007 doi

  85. [93]

    1998, , 128, 471, 10.1051/aas:1998388

    Mowlavi , N., Schaerer , D., Meynet , G., et al. 1998, , 128, 471, 10.1051/aas:1998388

    1998 doi

  86. [94]

    B., Mirocha , J., Chisholm , J., Furlanetto , S

    Mu \ n oz , J. B., Mirocha , J., Chisholm , J., Furlanetto , S. R., & Mason , C. 2024, , 535, L37, 10.1093/mnrasl/slae086

    2024 doi

  87. [95]

    J., Groh , J

    Murphy , L. J., Groh , J. H., Ekstr \"o m , S., et al. 2021, , 501, 2745, 10.1093/mnras/staa3803

    2021 doi

  88. [96]

    F., Hillier , D

    Najarro , F., Figer , D. F., Hillier , D. J., & Kudritzki , R. P. 2004, , 611, L105, 10.1086/423955

    2004 doi

  89. [97]

    2024, , 684, A169, 10.1051/0004-6361/202346979

    Nandal , D., Meynet , G., Ekstr \"o m , S., et al. 2024, , 684, A169, 10.1051/0004-6361/202346979

    2024 doi

  90. [98]

    Nugis , T., & Lamers , H. J. G. L. M. 2000, , 360, 227

    2000

  91. [99]

    J., Shapley , A., Faisst , A

    Pahl , A. J., Shapley , A., Faisst , A. L., et al. 2020, , 493, 3194, 10.1093/mnras/staa355

    2020 doi

  92. [100]

    W., Hoffmann, T

    Pauldrach, A. W., Hoffmann, T. L., & Lennon, M. 2001, Astronomy and Astrophysics, 375, 161, 10.1051/0004-6361:20010805

    2001 doi

  93. [101]

    R., Wang , C., & Marchant , P

    Pauli , D., Langer , N., Aguilera-Dena , D. R., Wang , C., & Marchant , P. 2022, , 667, A58, 10.1051/0004-6361/202243965

    2022 doi

  94. [102]

    2013, , 208, 4, 10.1088/0067-0049/208/1/4

    Paxton , B., Cantiello , M., Arras , P., et al. 2013, , 208, 4, 10.1088/0067-0049/208/1/4

    2013 doi

  95. [103]

    2021, , 908, 102, 10.3847/1538-4357/abd4d5

    Pietrinferni , A., Hidalgo , S., Cassisi , S., et al. 2021, , 908, 102, 10.3847/1538-4357/abd4d5

    2021 doi

  96. [104]

    2019, , 490, 978, 10.1093/mnras/stz2616

    Plat , A., Charlot , S., Bruzual , G., et al. 2019, , 490, 978, 10.1093/mnras/stz2616

    2019 doi

  97. [105]

    O., & Sen , K

    Puls , J., Najarro , F., Sundqvist , J. O., & Sen , K. 2020, , 642, A172, 10.1051/0004-6361/202038464

    2020 doi

  98. [106]

    A., Venero, R., et al

    Puls, J., Urbaneja, M. A., Venero, R., et al. 2005, Astronomy and Astrophysics, 435, 669, 10.1051/0004-6361:20042365

    2005 doi

  99. [107]

    E., Chisholm , J., Welch , B., et al

    Rivera-Thorsen , T. E., Chisholm , J., Welch , B., et al. 2024, arXiv e-prints, arXiv:2404.08884, 10.48550/arXiv.2404.08884

    2024 doi arXiv

  100. [108]

    R., Taylor , J

    Roman-Duval , J., Proffitt , C. R., Taylor , J. M., et al. 2020, Research Notes of the American Astronomical Society, 4, 205, 10.3847/2515-5172/abca2f

    2020 doi

  101. [109]

    2024, arXiv e-prints, arXiv:2410.13254, 10.48550/arXiv.2410.13254

    Roy , N., Heckman , T., Henry , A., et al. 2024, arXiv e-prints, arXiv:2410.13254, 10.48550/arXiv.2410.13254

    2024 doi arXiv

  102. [110]

    N., Vink , J

    Sabhahit , G. N., Vink , J. S., Higgins , E. R., & Sander , A. A. C. 2022, , 514, 3736, 10.1093/mnras/stac1410

    2022 doi

  103. [111]

    E., de Koter, A., et al

    Sana, H., de Mink, S. E., de Koter, A., et al. 2012, Science, 337, 444, 10.1126/science.1223344

    2012 doi

  104. [112]

    E., et al

    Sana , H., de Koter , A., de Mink , S. E., et al. 2013, , 550, A107, 10.1051/0004-6361/201219621

    2013 doi

  105. [113]

    F., Barrera-Ballesteros , J

    S \'a nchez , S. F., Barrera-Ballesteros , J. K., Lacerda , E., et al. 2022, , 262, 36, 10.3847/1538-4365/ac7b8f

    2022 doi

  106. [114]

    2015, , 577, A13, 10.1051/0004-6361/201425356

    Sander , A., Shenar , T., Hainich , R., et al. 2015, , 577, A13, 10.1051/0004-6361/201425356

    2015 doi

  107. [115]

    Sander , A. A. C., & Vink , J. S. 2020, , 499, 873, 10.1093/mnras/staa2712

    2020 doi

  108. [116]

    Sander , A. A. C., Bouret , J. C., Bernini-Peron , M., et al. 2024, , 689, A30, 10.1051/0004-6361/202449829

    2024 doi

  109. [118]

    2024, arXiv e-prints, arXiv:2407.12122, 10.48550/arXiv.2407.12122

    Schaerer , D., Guibert , J., Marques-Chaves , R., & Martins , F. 2024, arXiv e-prints, arXiv:2407.12122, 10.48550/arXiv.2407.12122

    2024 doi arXiv

  110. [119]

    N., Moffat , A

    Schnurr , O., Casoli , J., Chen \'e , A. N., Moffat , A. F. J., & St-Louis , N. 2008, , 389, L38, 10.1111/j.1745-3933.2008.00517.x

    2008

  111. [120]

    C., Ramachandran , V., Sander , A

    Sch \"o sser , E. C., Ramachandran , V., Sander , A. A. C., et al. 2025, , 696, L3, 10.1051/0004-6361/202554027

    2025 doi

  112. [121]

    P., Charlot , S., et al

    Senchyna , P., Stark , D. P., Charlot , S., et al. 2021, , 503, 6112, 10.1093/mnras/stab884

    2021 doi

  113. [122]

    J., Crowther , P

    Smith , L. J., Crowther , P. A., Calzetti , D., & Sidoli , F. 2016, , 823, 38, 10.3847/0004-637X/823/1/38

    2016 doi

  114. [123]

    J., Oey , M

    Smith , L. J., Oey , M. S., Hernandez , S., et al. 2023, , 958, 194, 10.3847/1538-4357/ad00b4

    2023 doi

  115. [124]

    C., Strom , A

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

    2016 doi

  116. [125]

    2017, Nature Communications, 8, 14906, 10.1038/ncomms14906

    Stevenson , S., Vigna-G \'o mez , A., Mandel , I., et al. 2017, Nature Communications, 8, 14906, 10.1038/ncomms14906

    2017 doi

  117. [126]

    L., Rudie , G

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

    2022 doi

  118. [127]

    O., & Puls , J

    Sundqvist , J. O., & Puls , J. 2018, , 619, A59, 10.1051/0004-6361/201832993

    2018 doi

  119. [128]

    J., Skinner , C

    Sylvester , R. J., Skinner , C. J., & Barlow , M. J. 1998, , 301, 1083, 10.1046/j.1365-8711.1998.02078.x

    1998

  120. [129]

    2022, , 658, A125, 10.1051/0004-6361/202141536

    Sz \'e csi , D., Agrawal , P., W \"u nsch , R., & Langer , N. 2022, , 658, A125, 10.1051/0004-6361/202141536

    2022 doi

  121. [130]

    G., Chisholm , J., Sander , A

    Telford , O. G., Chisholm , J., Sander , A. A. C., et al. 2024, , 974, 85, 10.3847/1538-4357/ad697e

    2024 doi

  122. [131]

    2024, , 686, A185, 10.1051/0004-6361/202449184

    Upadhyaya , A., Marques-Chaves , R., Schaerer , D., et al. 2024, , 686, A185, 10.1051/0004-6361/202449184

    2024 doi

  123. [132]

    T., Groenewegen , M

    van Loon , J. T., Groenewegen , M. A. T., de Koter , A., et al. 1999, , 351, 559, 10.48550/arXiv.astro-ph/9909416

    1999 doi arXiv

  124. [133]

    2016, , 463, 3409, 10.1093/mnras/stw2231

    Vazdekis , A., Koleva , M., Ricciardelli , E., R \"o ck , B., & Falc \'o n-Barroso , J. 2016, , 463, 3409, 10.1093/mnras/stw2231

    2016 doi

  125. [134]

    S., de Koter , A., & Lamers , H

    Vink , J. S., de Koter , A., & Lamers , H. J. G. L. M. 2001, , 369, 574, 10.1051/0004-6361:20010127

    2001 doi

  126. [135]

    S., Muijres , L

    Vink , J. S., Muijres , L. E., Anthonisse , B., et al. 2011, , 531, A132, 10.1051/0004-6361/201116614

    2011 doi

  127. [136]

    S., & Sander , A

    Vink , J. S., & Sander , A. A. C. 2021, , 504, 2051, 10.1093/mnras/stab902

    2021 doi

  128. [137]

    S., Mehner , A., Crowther , P

    Vink , J. S., Mehner , A., Crowther , P. A., et al. 2023, , 675, A154, 10.1051/0004-6361/202245650

    2023 doi

  129. [138]

    E., Rigby , J

    Welch , B., Rivera-Thorsen , T. E., Rigby , J. R., et al. 2025, , 980, 33, 10.3847/1538-4357/ada76c

    2025 doi

  130. [139]

    2014, , 781, 122, 10.1088/0004-637X/781/2/122

    Wofford , A., Leitherer , C., Chandar , R., & Bouret , J.-C. 2014, , 781, 122, 10.1088/0004-637X/781/2/122

    2014 doi

  131. [140]

    2023, , 523, 3949, 10.1093/mnras/stad1622

    Wofford , A., Sixtos , A., Charlot , S., et al. 2023, , 523, 3949, 10.1093/mnras/stad1622

    2023 doi

  132. [141]

    R., & Eldridge , J

    Xiao , L., Stanway , E. R., & Eldridge , J. J. 2018, , 477, 904, 10.1093/mnras/sty646

    2018 doi

  133. [142]

    2022, , 511, 2814, 10.1093/mnras/stac230

    Yusof , N., Hirschi , R., Eggenberger , P., et al. 2022, , 511, 2814, 10.1093/mnras/stac230

    2022 doi

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.