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arxiv: 2606.25263 · v1 · pith:FM3XH7K2new · submitted 2026-06-24 · 🌌 astro-ph.GA

Initial Mass Functions of Young Stellar Clusters from the Gemini Spectroscopic Survey of Nearby Galaxies. II. Young Clusters in NGC 1313

Jae-Rim Koo , Hyun-Jeong Kim , Beomdu Lim This is my paper

Pith reviewed 2026-06-25 21:37 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords initial mass functionyoung stellar clustersNGC 1313spectroscopytop-light IMFstellar populationsIMF variationcluster mass
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The pith

Young clusters in NGC 1313 exhibit top-light initial mass functions that become more pronounced in more massive systems.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper studies the initial mass functions of 11 young stellar clusters in the galaxy NGC 1313 using integrated light spectra from the Gemini telescope. By fitting the spectra with simple stellar population models at subsolar metallicity, the authors derive ages, masses, and IMF power-law indices. They find that the IMF for stars above 0.8 solar masses has a shallower slope than the standard Salpeter or Kroupa IMF, indicating fewer high-mass stars. The data also show a trend where higher-mass clusters have even more top-light IMFs. These results caution against assuming a universal IMF for unresolved stellar systems.

Core claim

Utilizing constraints from absorption lines and Wolf-Rayet emission bands, the observed spectra of clusters aged 2.5 to 300 Myr with masses from 2.8×10^3 to 2.6×10^5 solar masses are matched to synthetic spectra. For stellar masses exceeding 0.8 solar masses, the power-law index Gamma of the underlying IMFs is smaller than the standard Salpeter/Kroupa IMF. A correlation exists where more massive clusters tend to possess top-light IMFs, consistent with trends in the Antennae Galaxies despite different mass scales.

What carries the argument

Simple stellar population model at fixed metallicity Z=0.008, fitted to spectral features including Wolf-Rayet bands to determine IMF slope Gamma.

If this is right

  • The IMF is not universal but varies with cluster mass.
  • More massive clusters have top-light IMFs.
  • Applying a standard IMF to unresolved systems may lead to inaccurate mass and star formation estimates.
  • Stochastic effects in low-mass clusters were accounted for via Monte Carlo simulations.
  • The trend aligns with observations in other galaxies like the Antennae.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the IMF varies systematically with cluster mass, models of galaxy formation must incorporate mass-dependent IMFs to accurately predict stellar populations.
  • This could imply that the upper end of the IMF is suppressed in denser or more massive environments.
  • Observations of integrated light in distant galaxies might need revision if top-light IMFs are common.
  • Further spectroscopy of clusters in additional galaxies could test whether the mass-IMF correlation is universal.

Load-bearing premise

The adopted simple stellar population model with fixed metallicity Z=0.008 and chosen spectral features accurately captures the integrated light without major contributions from nebular emission or multiple stellar populations.

What would settle it

A spectrum from a cluster in NGC 1313 that is better fit by a standard Salpeter IMF model than by a shallower Gamma model, or the absence of any mass-dependent trend in a larger sample.

Figures

Figures reproduced from arXiv: 2606.25263 by Beomdu Lim, Hyun-Jeong Kim, Jae-Rim Koo.

Figure 1
Figure 1. Figure 1: GMOS-S image of NGC 1313. The slit positions are shown by rectangular boxes with the cluster IDs. 2. DATA 2.1. Observation LEGUS published the catalogs of cluster candi￾dates spread over two Hubble fields in NGC 1313 (Adamo et al. 2017). These catalogs contain photomet￾ric data in five optical passbands and physical param￾eters of clusters, such as ages, masses, and reddening, inferred from analysis of the… view at source ↗
Figure 2
Figure 2. Figure 2: Flux-calibrated spectra of 11 clusters. The IDs of individual clusters are labeled in the upper right corner of each panel. The red curves represent the smoothed spectra to highlight spectral features. Astro-Python Code3 . To address the potential uncer￾tainties associated with slit loss, we assumed that the telescope was accurately positioned and tracked to keep the targets centered within the slit mask d… view at source ↗
Figure 3
Figure 3. Figure 3: Comparison between our synthetic photometry (from calibrated spectra) and LEGUS photometry. The blue and green dots represent photometric differences in the B and V bands, respectively. Simple stellar population models are essential for in￾terpreting the integrated light of unresolved stellar pop￾ulations. In this work, STARBURST99 (Leitherer et al. 1999, 2014) was used to derive the underlying IMFs and ph… view at source ↗
Figure 4
Figure 4. Figure 4: Synthetic spectra of the model clusters (106 M⊙) for three different metalicities (Z = 0.002 – blue, 0.008 – red, and 0.014 – black). The ages of the clusters are shown at the upper-right corner of each spectrum. The Kroupa IMF applied to all spectra. The integrated spectral features of clusters are char￾acterized by the evolutionary stage of the most massive stars, allowing us to infer the ages of the obs… view at source ↗
Figure 4
Figure 4. Figure 4: Continued. 4. > 5 Myr: Detectable He I λλ4387, 4922. 5. > 7 Myr : Detectable Ca II K, weak Mg II λ4481, and weak Mg I b triplet. 6. 10 Myr – 100 Myr : Ca II K line and detectable He I lines. 7. & 80 Myr : Mg II λ4481 comparable to He I λ4471. 8. 100 Myr – 1 Gyr : G-band, Ca II K, and Mg I b triplet (systematically age-dependent). Weak He I lines. Mg II λ4481 stronger than He I λ4471 [PITH_FULL_IMAGE:figur… view at source ↗
Figure 4
Figure 4. Figure 4: Continued. imately 6–7 Myr. The spectrum of cluster ID 10 in￾cludes the Ca II K absorption line; however, the Hα and [S II] λλ6717, 6731 emission lines are also detected (as shown in [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Variations of spectral features obtained from the synthetic integrated spectra of model clusters (Mcl = 106M⊙ and Z = 0.008). In the lower panels, the equivalent widths of blue and red bumps are obtained from the output of STARBURST99, N III λ4640 + C III λ4650 + He II λ4686 and C IV λ5808, respectively. in the observed spectrum with a high SNR. In addition, the strength of the Mg II λ4481 absorption line … view at source ↗
Figure 6
Figure 6. Figure 6: Normalized spectra of the observed clusters. To minimize spectral overlap, the intensities of strong emission lines (exceeding two times the normalized continuum) are deliberately limited. The IDs of the individual clusters are labeled in the upper-right corner of each spectrum. The spectral lines shown in [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Comparison between the observed spectra (black curves) and the best-matched synthetic spectra (red curves). Note that only the mean Galactic extinction was applied to the synthetic templates. The B- and V -band mean fluxes predicted by our Monte Carlo simulations are indicated by orange symbols, with the corresponding 1σ uncertainties denoted by error bars [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Comparison of the physical parameters obtained from this study with those derived in the LEGUS survey (Adamo et al. 2017). The left and right panels compare ages and cluster masses estimated in the two studies, respectively. The red symbols represent the results obtained after correct￾ing for internal extinction. In both panels, the horizontal and vertical lines denote the uncertainties associated with eac… view at source ↗
Figure 9
Figure 9. Figure 9: Relationship between physical parameters and the IMF slope (Γ). The left and right panels compare cluster masses and ages against Γ, respectively. The blue and red circles represent the results obtained without and with internal extinction correction, respectively, while the cyan and orange triangles denote the corresponding best-fit results from the STARBURST99 models. In both panels, the horizontal and v… view at source ↗
Figure 10
Figure 10. Figure 10: Flux distributions in the B-band generated from 10,000 Monte Carlo simulations for the ten observed clusters. Each panel represents an individual cluster, displaying the simulated histograms obtained using the IMF slope (Γ) from this study (blue) and under the assumption of a standard Salpeter/Kroupa IMF (red). The vertical solid line indicates the observed mean B-band flux of the spectrum, while the vert… view at source ↗
read the original abstract

We present a spectroscopic study of young stellar clusters in the barred spiral galaxy NGC 1313. Integrated light spectra of 11 clusters, obtained using the GMOS-S instrument on the 8.1 m Gemini South telescope, are analyzed using a simple stellar population model. A subsolar metallicity (Z = 0.008) is adopted, consistent with previous studies. Cluster ages are constrained primarily through absorption lines and prominent emission bands of Wolf-Rayet stars. Utilizing these constraints, we match the observed spectra with synthetic counterparts generated from the simple stellar population model, determining key physical parameters including age, cluster mass, and the underlying initial mass function (IMF). Furthermore, the impact of stochastic sampling on the derived parameters of several low-mass clusters is rigorously evaluated using Monte Carlo simulations. The sampled clusters exhibit ages ranging from 2.5 to 300 Myr and stellar masses between 2.8 x 10^3 Msun and 2.6 x 10^5 Msun. Notably, for stellar masses exceeding 0.8 Msun, the power-law index (Gamma) of the underlying IMFs is found to be smaller than the standard Salpeter/Kroupa IMF. Furthermore, a correlation is observed where more massive clusters tend to possess top-light IMFs. This finding aligns with trends observed in the young clusters of the Antennae Galaxies, despite the differing mass scales between the two systems. Our results suggest that applying a universal standard IMF to spatially unresolved systems warrants caution, given the inherent complexities revealed in this study.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript reports Gemini GMOS-S integrated-light spectroscopy of 11 young stellar clusters in NGC 1313. Ages (2.5–300 Myr) are constrained via absorption lines and Wolf-Rayet bands; spectra are then matched to SSP models at fixed Z=0.008 to derive cluster masses (2.8×10^3–2.6×10^5 M⊙) and the IMF power-law index Gamma above 0.8 M⊙. The central results are that Gamma is smaller than the Salpeter/Kroupa value and that more massive clusters exhibit more top-light IMFs; Monte Carlo simulations quantify stochastic sampling effects in the lower-mass systems.

Significance. If the model fits are robust, the work supplies direct evidence for IMF variation among young clusters and cautions against assuming a universal IMF for unresolved populations. The reported trend with cluster mass is consistent with findings in the Antennae, and the explicit Monte Carlo treatment of stochasticity is a methodological strength that improves reproducibility of the error budget.

major comments (2)
  1. [Abstract, paragraph on model adoption and age constraints] Abstract, paragraph on model adoption and age constraints: the claim that Gamma < Salpeter/Kroupa (and the mass correlation) is load-bearing on the assumption that the fixed-Z=0.008 SSP model reproduces the integrated spectra without significant nebular emission filling absorption features or unaccounted metallicity variations; no sensitivity tests to Z or added nebular components are described, leaving open the possibility that the inferred top-light slopes are systematic artifacts.
  2. [Monte Carlo simulations] Monte Carlo section: while stochastic sampling is evaluated for several low-mass clusters, the manuscript does not quantify how the derived Gamma–mass correlation changes when the Monte Carlo realizations are propagated through the full fitting pipeline, so it remains unclear whether the trend survives realistic age–mass–Gamma degeneracies.
minor comments (2)
  1. The exact mathematical definition of the power-law index Gamma (e.g., whether dN/dM ∝ M^Gamma with Gamma = −2.35 for Salpeter) should be stated explicitly when comparing to standard IMFs.
  2. A table listing individual cluster IDs, ages, masses, and Gamma values (with uncertainties) would improve traceability of the reported trends.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive report and the positive assessment of the work's significance. We respond to each major comment below.

read point-by-point responses

  1. Referee: [Abstract, paragraph on model adoption and age constraints] Abstract, paragraph on model adoption and age constraints: the claim that Gamma < Salpeter/Kroupa (and the mass correlation) is load-bearing on the assumption that the fixed-Z=0.008 SSP model reproduces the integrated spectra without significant nebular emission filling absorption features or unaccounted metallicity variations; no sensitivity tests to Z or added nebular components are described, leaving open the possibility that the inferred top-light slopes are systematic artifacts.

    Authors: The fixed metallicity Z=0.008 follows the value adopted in prior studies of NGC 1313. Age constraints rely primarily on Wolf-Rayet bands and absorption features, which are relatively insensitive to modest Z variations. We agree that explicit sensitivity tests would strengthen the analysis and will add tests varying Z around 0.008 together with an assessment of possible nebular emission contributions in the revised manuscript. revision: yes

  2. Referee: [Monte Carlo simulations] Monte Carlo section: while stochastic sampling is evaluated for several low-mass clusters, the manuscript does not quantify how the derived Gamma–mass correlation changes when the Monte Carlo realizations are propagated through the full fitting pipeline, so it remains unclear whether the trend survives realistic age–mass–Gamma degeneracies.

    Authors: The Monte Carlo realizations were used to evaluate stochastic effects on the parameters of the lowest-mass clusters. The reported Gamma–mass trend is driven by the higher-mass systems where stochastic sampling is negligible. We will nevertheless propagate the Monte Carlo realizations through the full fitting procedure and re-evaluate the correlation to quantify any impact from age–mass–Gamma degeneracies. revision: yes

Circularity Check

0 steps flagged

No circularity: IMF parameters are fitted outputs from independent spectra

full rationale

The paper constrains cluster ages from absorption lines and WR features, then fits SSP model spectra (at fixed Z=0.008) to the observed integrated light to obtain mass and Gamma. These fitted Gamma values and the reported mass correlation are direct results of applying the model to external Gemini GMOS-S data for 11 clusters; they are not presupposed by definition, obtained via self-citation chains, or renamed known results. The procedure is standard parameter inference with stated model assumptions and Monte Carlo checks for stochasticity; no load-bearing step reduces the claimed IMF variation to an input by construction.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The central claim depends on the validity of the adopted simple stellar population synthesis code, the fixed metallicity, and the assumption that spectral features uniquely constrain age and IMF slope; IMF parameters themselves are free parameters fitted to the data.

free parameters (2)
  • IMF power-law index Gamma
    Fitted per cluster by matching synthetic SSP spectra to observed absorption and emission features.
  • Cluster age and total mass
    Determined simultaneously with Gamma via spectral matching to the SSP grid.
axioms (2)
  • domain assumption Simple stellar population models with Z=0.008 accurately reproduce the integrated spectra of the clusters
    Invoked when generating synthetic spectra for comparison (abstract, model description paragraph).
  • domain assumption Stochastic sampling effects in low-mass clusters are fully captured by the Monte Carlo simulations performed
    Used to evaluate impact on derived parameters for several clusters.

pith-pipeline@v0.9.1-grok · 5831 in / 1519 out tokens · 30115 ms · 2026-06-25T21:37:07.405096+00:00 · methodology

discussion (0)

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Works this paper leans on

55 extracted references · 53 canonical work pages · 3 internal anchors

  1. [1]

    , archivePrefix = "arXiv", eprint =

    Adamo, A., Ryon, J. E., Messa, M., et al. 2017, ApJ, 841, 131, doi: 10.3847/1538-4357/aa7132 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M. , et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collaboration, Pr...

    work page doi:10.3847/1538-4357/aa7132 2017

  2. [2]

    R., & Meyer, M

    Bastian, N., Covey, K. R., & Meyer, M. R. 2010, ARA&A, 48, 339, doi: 10.1146/annurev-astro-082708-101642

    work page doi:10.1146/annurev-astro-082708-101642 2010

  3. [3]

    C., Sabbi, E., et al

    Calzetti, D., Lee, J. C., Sabbi, E., et al. 2015, AJ, 149, 51, doi: 10.1088/0004-6256/149/2/51

    work page doi:10.1088/0004-6256/149/2/51 2015

  4. [4]

    A&A , volume =

    Cantat-Gaudin, T., Jordi, C., Vallenari, A., et al. 2018, A&A, 618, A93, doi: 10.1051/0004-6361/201833476 Cervi˜ no, M. 2013, NewAR, 57, 123, doi: 10.1016/j.newar.2013.09.001

    work page doi:10.1051/0004-6361/201833476 2018

  5. [5]

    , keywords =

    Davies, B., Clark, J. S., Trombley, C., et al. 2012, MNRAS, 419, 1871, doi: 10.1111/j.1365-2966.2011.19736.x

    work page doi:10.1111/j.1365-2966.2011.19736.x 2012

  6. [6]

    , keywords =

    Deger, S., Lee, J. C., Whitmore, B. C., et al. 2022, MNRAS, 510, 32, doi: 10.1093/mnras/stab3213 Ekstr¨ om, S., Georgy, C., Eggenberger, P., et al. 2012, A&A, 537, A146, doi: 10.1051/0004-6361/201117751

    work page doi:10.1093/mnras/stab3213 2022

  7. [7]

    Elmegreen, B. G. 2000, ApJ, 539, 342, doi: 10.1086/309204

    work page doi:10.1086/309204 2000

  8. [8]

    Filippenko, A. V. 1982, PASP, 94, 715, doi: 10.1086/131052

    work page doi:10.1086/131052 1982

  9. [9]

    K., Johnson, K

    Finn, M. K., Johnson, K. E., Indebetouw, R., et al. 2024a, ApJ, 964, 13, doi: 10.3847/1538-4357/ad198a —. 2024b, ApJ, 964, 12, doi: 10.3847/1538-4357/ad1eec

    work page doi:10.3847/1538-4357/ad198a

  10. [10]

    doi:10.5281/zenodo.14712174 , version =

    Fouesneau, M. 2025, pyphot, pyphot v2.0.0, Zenodo, doi: 10.5281/zenodo.14712174

    work page doi:10.5281/zenodo.14712174 2025

  11. [11]

    2013, A&A, 558, A103, doi: 10.1051/0004-6361/201322178

    Georgy, C., Ekstr¨ om, S., Eggenberger, P., et al. 2013, A&A, 558, A103, doi: 10.1051/0004-6361/201322178

    work page doi:10.1051/0004-6361/201322178 2013

  12. [12]

    R., Christopher, M

    Greissl, J., Meyer, M. R., Christopher, M. H., & Scoville, N. Z. 2010, ApJ, 710, 1746, doi: 10.1088/0004-637X/710/2/1746

    work page doi:10.1088/0004-637x/710/2/1746 2010

  13. [13]

    Gunawardhana, M. L. P., Hopkins, A. M., Sharp, R. G., et al. 2011, MNRAS, 415, 1647, doi: 10.1111/j.1365-2966.2011.18800.x

    work page doi:10.1111/j.1365-2966.2011.18800.x 2011

  14. [14]

    2008, ApJ, 675, 1319, doi: 10.1086/524650

    Harayama, Y., Eisenhauer, F., & Martins, F. 2008, ApJ, 675, 1319, doi: 10.1086/524650

    work page doi:10.1086/524650 2008

  15. [15]

    2017, A&A, 603, A119, doi: 10.1051/0004-6361/201730550

    Hernandez, S., Larsen, S., Trager, S., Groot, P., & Kaper, L. 2017, A&A, 603, A119, doi: 10.1051/0004-6361/201730550

    work page doi:10.1051/0004-6361/201730550 2017

  16. [16]

    2022, AJ, 164, 89, doi: 10.3847/1538-3881/ac7ebe

    Jones, L. 2022, AJ, 164, 89, doi: 10.3847/1538-3881/ac7ebe

    work page doi:10.3847/1538-3881/ac7ebe 2022

  17. [17]

    W., Lu, J

    Hosek, Jr., M. W., Lu, J. R., Anderson, J., et al. 2019, ApJ, 870, 44, doi: 10.3847/1538-4357/aaef90

    work page doi:10.3847/1538-4357/aaef90 2019

  18. [18]

    2015, MNRAS, 446, 3797, doi: 10.1093/mnras/stu2329

    Hur, H., Park, B.-G., Sung, H., et al. 2015, MNRAS, 446, 3797, doi: 10.1093/mnras/stu2329

    work page doi:10.1093/mnras/stu2329 2015

  19. [19]

    A., Rizzi, L., Tully, R

    Jacobs, B. A., Rizzi, L., Tully, R. B., et al. 2009, AJ, 138, 332, doi: 10.1088/0004-6256/138/2/332

    work page doi:10.1088/0004-6256/138/2/332 2009

  20. [20]

    2025, AJ, 169, 7, doi: 10.3847/1538-3881/ad8e3b The IMFs of young clusters in NGC 1313 19

    Koo, J.-R., Kim, H.-J., & Lim, B. 2025, AJ, 169, 7, doi: 10.3847/1538-3881/ad8e3b The IMFs of young clusters in NGC 1313 19

    work page doi:10.3847/1538-3881/ad8e3b 2025

  21. [21]

    2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    work page doi:10.1046/j.1365-8711.2001.04022.x 2001

  22. [22]

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

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

    work page doi:10.1093/mnras/stv1374 2015

  23. [23]

    2023, Research Notes of the American Astronomical Society, 7, 214, doi: 10.3847/2515-5172/ad0044

    Labrie, K., Simpson, C., Cardenes, R., et al. 2023, Research Notes of the American Astronomical Society, 7, 214, doi: 10.3847/2515-5172/ad0044

    work page doi:10.3847/2515-5172/ad0044 2023

  24. [24]

    Disentangling the independently controllable factors of variation by interacting with the world

    Lada, C. J., & Lada, E. A. 2003, ARA&A, 41, 57, doi: 10.1146/annurev.astro.41.011802.094844

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1146/annurev.astro.41.011802.094844 2003

  25. [25]

    S., Mora, M

    Larsen, S. S., Mora, M. D., Brodie, J. P., & Richtler, T. 2007, in IAU Symposium, Vol. 241, Stellar Populations as Building Blocks of Galaxies, ed. A. Vazdekis & R. Peletier, 435–439, doi: 10.1017/S1743921307008708

    work page doi:10.1017/s1743921307008708 2007

  26. [26]

    N., & Thaddeus, P

    Leisawitz, D., Bash, F. N., & Thaddeus, P. 1989, ApJS, 70, 731, doi: 10.1086/191357

    work page doi:10.1086/191357 1989

  27. [27]

    2014, ApJS, 212, 14, doi: 10.1088/0067-0049/212/1/14

    Leitherer, C., Ekstr¨ om, S., Meynet, G., et al. 2014, ApJS, 212, 14, doi: 10.1088/0067-0049/212/1/14

    work page doi:10.1088/0067-0049/212/1/14 2014

  28. [28]

    Starburst99: Synthesis Models for Galaxies with Active Star Formation

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

    work page internal anchor Pith review doi:10.1086/313233 1999

  29. [29]

    R., Oskinova, L

    Liermann, A., Hamann, W. R., Oskinova, L. M., Todt, H., & Butler, K. 2010, A&A, 524, A82, doi: 10.1051/0004-6361/200912612

    work page doi:10.1051/0004-6361/200912612 2010

  30. [30]

    2013, AJ, 145, 46, doi: 10.1088/0004-6256/145/2/46

    Lim, B., Chun, M.-Y., Sung, H., et al. 2013, AJ, 145, 46, doi: 10.1088/0004-6256/145/2/46

    work page doi:10.1088/0004-6256/145/2/46 2013

  31. [31]

    2024, ApJ, 961, 72, doi: 10.3847/1538-4357/ad12c4

    Lim, B., Naz´ e, Y., Chang, S.-J., & Hutsem´ ekers, D. 2024, ApJ, 961, 72, doi: 10.3847/1538-4357/ad12c4

    work page doi:10.3847/1538-4357/ad12c4 2024

  32. [32]

    S., et al

    Lim, B., Sung, H., Bessell, M. S., et al. 2015, AJ, 149, 127, doi: 10.1088/0004-6256/149/4/127

    work page doi:10.1088/0004-6256/149/4/127 2015

  33. [33]

    2017, in IAU

    Lim, B., Sung, H., Hur, H., & Park, B.-G. 2017, in IAU

    2017

  34. [34]

    316, Formation, Evolution, and Survival of Massive Star Clusters, ed

    Symposium, Vol. 316, Formation, Evolution, and Survival of Massive Star Clusters, ed. C. Charbonnel & A. Nota, 357–358, doi: 10.1017/S1743921315010595 —. 2018, MNRAS, 477, 1993, doi: 10.1093/mnras/sty713

    work page doi:10.1017/s1743921315010595 2018

  35. [35]

    Marks, M., Kroupa, P., Dabringhausen, J., & Pawlowski, M. S. 2012, MNRAS, 422, 2246, doi: 10.1111/j.1365-2966.2012.20767.x

    work page doi:10.1111/j.1365-2966.2012.20767.x 2012

  36. [36]

    and Sabbi, Elena and Smith, Linda J

    Messa, M., Calzetti, D., Adamo, A., et al. 2021, ApJ, 909, 121, doi: 10.3847/1538-4357/abe0b5

    work page doi:10.3847/1538-4357/abe0b5 2021

  37. [37]

    , keywords =

    Miller, G. E., & Scalo, J. M. 1979, ApJS, 41, 513, doi: 10.1086/190629

    work page doi:10.1086/190629 1979

  38. [38]

    L., Freeman, K

    Peters, W. L., Freeman, K. C., Forster, J. R., Manchester, R. N., & Ables, J. G. 1994, MNRAS, 269, 1025, doi: 10.1093/mnras/269.4.1025

    work page doi:10.1093/mnras/269.4.1025 1994

  39. [39]

    2003, AJ, 126, 1916, doi: 10.1086/377623

    Porras, A., Christopher, M., Allen, L., et al. 2003, AJ, 126, 1916, doi: 10.1086/377623

    work page doi:10.1086/377623 2003

  40. [40]

    2015, ApJ, 799, 19, doi: 10.1088/0004-637X/799/1/19

    Qing, G., Wang, W., Liu, J.-F., & Yoachim, P. 2015, ApJ, 799, 19, doi: 10.1088/0004-637X/799/1/19

    work page doi:10.1088/0004-637x/799/1/19 2015

  41. [41]

    2018, ApJS, 235, 23, doi: 10.3847/1538-4365/aaa8e5

    Sabbi, E., Calzetti, D., Ubeda, L., et al. 2018, ApJS, 235, 23, doi: 10.3847/1538-4365/aaa8e5

    work page doi:10.3847/1538-4365/aaa8e5 2018

  42. [42]

    Salpeter, E. E. 1955, ApJ, 121, 161, doi: 10.1086/145971

    work page doi:10.1086/145971 1955

  43. [43]

    B., Solomon, P

    Sanders, D. B., Solomon, P. M., & Scoville, N. Z. 1984, ApJ, 276, 182, doi: 10.1086/161602 Schlafly, E. F., & Finkbeiner, D. P. 2011, ApJ, 737, 103, doi: 10.1088/0004-637X/737/2/103

    work page doi:10.1086/161602 1984

  44. [44]

    Debajyoti Sengupta, Stephen Mulligan, David Shih, John Andrew Raine, and Tobias Golling

    Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525, doi: 10.1086/305772

    work page internal anchor Pith review doi:10.1086/305772 1998

  45. [45]

    Silva-Villa, E., & Larsen, S. S. 2012, MNRAS, 423, 213, doi: 10.1111/j.1365-2966.2012.20797.x

    work page doi:10.1111/j.1365-2966.2012.20797.x 2012

  46. [46]

    J., et al

    Simpson, C., Labrie, K., Teal, D. J., et al. 2024, DRAGONS, 3.2.0, Zenodo, doi: 10.5281/zenodo.10841622

    work page doi:10.5281/zenodo.10841622 2024

  47. [47]

    2015, ApJ, 812, 39, doi: 10.1088/0004-637X/812/1/39

    Stanghellini, L., Magrini, L., & Casasola, V. 2015, ApJ, 812, 39, doi: 10.1088/0004-637X/812/1/39

    work page doi:10.1088/0004-637x/812/1/39 2015

  48. [48]

    Stone, R. P. S., & Baldwin, J. A. 1983, MNRAS, 204, 347, doi: 10.1093/mnras/204.2.347

    work page doi:10.1093/mnras/204.2.347 1983

  49. [49]

    Sung, H., & Bessell, M. S. 2004, AJ, 127, 1014, doi: 10.1086/381297

    work page doi:10.1086/381297 2004

  50. [50]

    2013, A&A, 554, A8, doi: 10.1051/0004-6361/201220294

    Suzuki, T., Kaneda, H., & Onaka, T. 2013, A&A, 554, A8, doi: 10.1051/0004-6361/201220294

    work page doi:10.1051/0004-6361/201220294 2013

  51. [51]

    R., & Roy, J.-R

    Walsh, J. R., & Roy, J.-R. 1997, MNRAS, 288, 726, doi: 10.1093/mnras/288.3.726

    work page doi:10.1093/mnras/288.3.726 1997

  52. [52]

    2004, MNRAS, 354, 1020, doi: 10.1111/j.1365-2966.2004.08261.x

    Weidner, C., & Kroupa, P. 2004, MNRAS, 348, 187, doi: 10.1111/j.1365-2966.2004.07340.x

    work page doi:10.1111/j.1365-2966.2004.07340.x 2004

  53. [53]

    Wouterloot, J. G. A., Brand, J., Burton, W. B., & Kwee, K. K. 1990, A&A, 230, 21

    1990

  54. [54]

    2025, AJ, 169, 214, doi: 10.3847/1538-3881/adba45

    Yang, G., Zhao, J., Yang, Y., et al. 2025, AJ, 169, 214, doi: 10.3847/1538-3881/adba45

    work page doi:10.3847/1538-3881/adba45 2025

  55. [55]

    W., & Friel, E

    Yong, D., Carney, B. W., & Friel, E. D. 2012, AJ, 144, 95, doi: 10.1088/0004-6256/144/4/95

    work page doi:10.1088/0004-6256/144/4/95 2012