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REVIEW 3 major objections 4 minor 199 references

Impact of Uncertainties in Spectral Energy Distribution Modelling on Inferred Galaxy Properties

T0 review · 3 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read The choice of stellar spectral library, not observational precision, sets the floor on how accurately galaxy masses, ages, and star formation rates can be inferred from SED fitting.

desk verdict A careful controlled SED-fitting uncertainty study whose headline numbers are inflated by a template library the authors themselves reject; the qualitative conclusion survives, but the abstract needs reframing. read the letter →

arxiv 2509.02741 v1 pith:HKXNF4EL submitted 2025-09-02 astro-ph.GA

Gareth T. Jones , Conor M. Byrne , Elizabeth R. Stanway This is my paper · ORCID
classification astro-ph.GA
keywords SEDfittingstellarpopulationsynthesisBPASSspectrallibrariesinitialmassfunctionmetallicityassumptionsEAGLEsimulationgalaxy
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper tries to establish that the underexamined modelling ingredients of spectral energy distribution (SED) fitting introduce systematic errors in galaxy properties that exceed the observational uncertainties reported by surveys. Using 18 galaxies from the EAGLE simulation, the authors generate mock SDSS spectra and VISTA photometry with one stellar population synthesis framework, BPASS v2.2.1, then refit them with variants that change only the stellar spectral library, initial mass function, or metallicity assumption. They find that switching spectral libraries shifts inferred stellar mass by $0.27\pm0.09$ dex, age by $0.19\pm0.11$ dex, and star formation rate by $1.4\pm1.0$ dex, enough to flip a galaxy's classification from star-forming to quiescent. The paper concludes that as survey data improve, modelling uncertainty, not measurement noise, will limit what can be said about galaxy evolution, so these choices must be part of any error budget.

What carries the argument

The central object is a controlled mock-observation loop: a set of 18 EAGLE galaxies at $z\simeq0$ whose particle data are turned into mock SDSS spectra and VISTA photometry using the default BPASS v2.2.1 population-synthesis models; these mock observations are then refit with the bagpipes SED-fitting code using BPASS variants in which only one ingredient changes, whether the stellar spectral library, the IMF slope, or the metallicity prescription. The loop converts hidden assumptions into a measured systematic scatter, because the deviation of each refit from the v2.2.1 result isolates the effect of that single choice while the true galaxy properties are known.

What would settle it

Fitting a sample of nearby galaxies with independently known stellar masses and star formation histories, from resolved stellar populations or dynamical measurements, using the same library variants; if the recovered scatter around the known values is much smaller than the quoted $0.27$ dex for mass and $1.4$ dex for star formation rate, the claim that spectral library choice sets the survey error floor would be refuted.

Watch

Extended reading notes

Core claim

The central claim is that the specific stellar spectral library embedded in a stellar population synthesis model is a dominant, hard-coded source of systematic uncertainty in SED fitting, larger than the observational noise quoted by large surveys. Working in a controlled setting where the truth is known, with mock spectra built from EAGLE galaxies through the default BPASS v2.2.1 framework, the paper shows that fitting with the AP or BaSeL libraries systematically biases inferred stellar masses higher by roughly 0.23 to 0.27 dex and ages higher by 0.17 to 0.19 dex, while BaSeL suppresses inferred star formation rates by up to 1.4 dex, sometimes reclassifying galaxies as quiescent. IMF slope changes shift masses and star formation rates at the 0.1 to 0.2 dex level, and fixing an incorrect metallicity biases mass and star formation rate even when the average effect over a stacked sample is small. The reconstructed cosmic mass assembly history changes by up to about 12 percent depending on the choices, and the authors contend that with upcoming wide surveys the field is entering a model-limited rather than observation-limited regime.

Load-bearing premise

The comparison rests on the assumption that a real galaxy's emission is well approximated by the BPASS v2.2.1 models, since the mock spectra are generated from that framework and then used as the reference for measuring offsets.

Editorial extensions

If this is right

  • Survey error bars on stellar mass and star formation rate that quote only observational noise (typically reported as less than 0.2 dex) understate the true uncertainty by roughly a factor of two or more.
  • Analyses of galaxy demographics should treat quiescent and star-forming fractions as partly model-dependent, since the BaSeL library alone can move galaxies across the classification boundary.
  • Reconstructed cosmic star formation and mass assembly histories carry up to roughly 10 to 12 percent systematic uncertainty at early times, dominated by spectral library and metallicity prescription choice.
  • For stacked samples of local massive galaxies above $10^9\,M_\odot$, fixing metallicity is acceptable, but only if the fixed value matches the sample's mass range and redshift.
  • Photometry-only surveys such as Euclid and Roman will not escape these systematics with better data; the paper suggests the bottleneck shifts to model assumptions.

Reading between the lines

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

  • The offsets' direction is sample dependent: the paper works with old, $z\sim0$ galaxies where red stellar populations dominate, so shallower IMFs imply higher inferred masses; a high-redshift young-population sample would plausibly show the opposite sign, as the paper's cited literature already suggests.
  • Because the mock observations are generated and fit within one BPASS family, the quoted scatter measures the internal flexibility of that framework; combining BPASS with structurally independent stellar population codes based on single-star isochrones would either bracket a wider systematic range or reveal that BPASS variants already span most of it.
  • A testable extension would reverse the loop: generate mock spectra from one of the alternative libraries as truth; if the recovered offsets do not mirror the v2.2.1-based ones, the modelling error budget cannot be summarized by a single number and must be reported per model pair.
  • The paper's warning about photometry-only surveys could be sharpened by running the same fitting with photometry alone; if the scatter does not shrink when spectroscopy is removed, the claim that spectroscopy increases sensitivity to library-induced systematics would need revision.
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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 / 4 minor

Summary. Using 18 z=0 galaxies from the EAGLE simulation, the authors generate mock SDSS spectra and VISTA YJH photometry with the BPASS v2.2.1 framework, then fit the mock observations with bagpipes using BPASS variants that vary the stellar spectral library (AP, BaSeL, C3K, CKC), the IMF shape, and the metallicity treatment (fixed, variable, evolving). All other fitting priors are identical. The paper reports offsets in derived stellar mass, age, SFR and extinction relative to the v2.2.1 reference fits, and shows that spectral-library choice can change mass, age and SFR by up to 0.27, 0.19 and 1.4 dex respectively, alter galaxy classifications between star-forming and quiescent, and shift reconstructed mass assembly histories by up to ~12 per cent. It concludes that SED modelling uncertainties exceed typical survey observational uncertainties and should be propagated in future survey analyses.

Significance. The controlled mock-fitting design is a genuine strength: identical priors, known input properties, a no-dust control, a spectrum-generation validation, and an IMF direction-reversal test make the sensitivity analysis easy to follow. The qualitative message—that hard-coded SPS assumptions introduce systematic offsets larger than quoted observational errors—is plausible and important for survey-based galaxy evolution studies, and the paper explicitly does not claim to identify the correct model. However, the quantitative headline is anchored to the BaSeL library, which the authors themselves conclude is unsuitable for these data, and the reported "absolute uncertainties" are mean offsets from one reference model rather than a model-to-model dispersion. These issues affect the abstract, the conclusions, and the survey-error-budget message, so they need to be addressed before the specific numbers can be used.

major comments (3)
  1. [§4.2, Table 3, Abstract, §9(i)] The headline SFR uncertainty of 1.4±1.0 dex and the star-forming-to-quiescent flip are driven entirely by the BaSeL grid, which the paper itself rejects. Table 3 assigns the 1.4 dex SFR offset to BaSeL, and Section 4.2 concludes that the low resolution of the BaSeL spectra renders them unsuitable for fitting to the high-quality simulated galaxies used in this study. If BaSeL is excluded, the largest library-induced offsets are 0.27 dex in mass and 0.52 dex in SFR (AP), with C3K and CKC below 0.05 dex; the qualitative conclusion survives, but the specific Abstract numbers and the classification-flip claim do not. Because the fits are framed as blind (Section 3.3), the paper needs either a quantitative model-comparison step (Bayesian evidence, chi-square, or posterior predictive checks) that justifies including or excluding BaSeL, or a restatement of the headline statistics based on libraries appropriate to SDSS-resolution data.
  2. [§9(i), Table 3] The quantities quoted as "absolute uncertainties" are mean offsets relative to the v2.2.1 reference, with the quoted scatter being the standard error of that mean, not a dispersion across model choices. For example, the mass offsets for AP and BaSeL (0.27 and 0.23 dex) are both positive, so the 0.27 dex value is a systematic bias of one model rather than the width of the model-induced scatter; similarly the 1.4 dex SFR number is the offset of BaSeL rather than a spread. The paper should separate systematic offsets from random scatter and report a model-to-model dispersion (e.g., standard deviation or full range across libraries) if these numbers are to be used as "uncertainties" in survey error budgets.
  3. [§3.2, Appendix A, §8] Because the mock observations are generated with BPASS v2.2.1 and every fit uses a BPASS variant with the same evolutionary tracks, binary treatment, dust prescription and SFH parameterisation, the quoted numbers measure internal sensitivity within the BPASS framework, not the total uncertainty of SED modelling. The paper is transparent about the v2.2.1 assumption in Section 3.2, but the Abstract and the survey-implications discussion (Section 8) phrase the results as uncertainties in "SED modelling" more generally. Appendix A provides relevant perspective: switching to single-star-only tracks changes mass by 0.18±0.11 dex and SFR by 0.48±0.18 dex (Table A1), comparable to several library differences. The headline numbers should therefore be described as lower bounds conditional on the BPASS framework rather than as absolute modelling uncertainties.
minor comments (4)
  1. [Table 1] In Table 1, the C03 row lists three numeric entries ('-2.3', '1.0', '300') under the four numeric columns; since the text says the C03 IMF has an exponential low-mass cutoff at 1 Msun and an upper slope of -2.3, the table formatting should be corrected or the row removed from the power-law parameter columns.
  2. [Figure 3 caption] The Figure 3 caption contains a duplicated word ('fromfrom') that should be removed.
  3. [Section 5] The phrase 'systemic uncertainties' near the end of Section 5 should be 'systematic uncertainties'.
  4. [Section 6.2] The statement that fixing metallicity at Z=0.012 or Z=0.022 produces SFR and mass offsets of ~0.2-0.4 dex is inferred from the trend in Fig. 11 rather than from fits run with those fixed values; this should be stated explicitly to avoid the impression that those offsets were directly measured.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper measures model sensitivity in a controlled mock setting and explicitly disclaims any derivation of the correct model.

full rationale

The paper's stated aim is to quantify how SED fitting results shift when the spectral library, IMF, or metallicity prescription is changed within a single SPS framework, not to derive the correct model. The mock observations are generated with BPASS v2.2.1 and the same framework serves as the reference ('Each galaxy spectrum is generated using the v2.2.1 default BPASS framework... We therefore assume that a galaxy's emission spectrum is well approximated by the BPASS v2.2.1 models'), but the paper explicitly disclaims any claim to determine the correct assumptions ('This study does not seek to determine the correct set of modelling assumptions to apply, but rather to quantify the uncertainties that arise by not correctly accounting for them'). The reported variations are thus conditional statements about model sensitivity, not predictions of true galaxy properties; no fitted parameter is renamed as a prediction, and no load-bearing conclusion reduces by construction to the input model. The alternative libraries include external grids (AP, BaSeL, CKC, C3K), and the mock spectra are validated against EAGLE catalogue photometry in Appendix B, providing an external check. Self-citations to BPASS papers describe the public code being used, but the quantitative results are produced by the fitting exercises in this paper, so the citations are not load-bearing circularity. The BaSeL-driven SFR scatter is large, but the paper itself flags BaSeL as unsuitable for high-quality simulated data; that is an internal consistency concern, not a circularity. Overall, the derivation chain is self-contained: input assumptions are varied, outputs are measured, and no claim is made that the outputs are independent of the inputs.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The analysis rests on a small number of hand-chosen inputs (dust attenuation, fitting metallicity, noise level, SFH binning) and on the domain assumption that BPASS v2.2.1, EAGLE, and the Salim et al. dust laws are adequate representations of real z=0 galaxies. The free parameters are not fitted to any external data; they are modeling choices that define the experiment. No new physical entities are introduced.

free parameters (4)
  • E(B-V) attenuation = 0.3 mag (uniform for all galaxies)
    Fixed dust attenuation chosen to mimic realistic survey conditions; not fitted, but a choice that could affect inferred properties if wrong.
  • Fixed fitting metallicity = Z = 0.014 (0.7 Zsun)
    Used for all spectral library and IMF fits; close to the EAGLE galaxy metallicities (0.014 to 0.024) but a fixed assumption.
  • Median mock noise = 3 percent of flux
    Assumed Gaussian noise level for synthetic SDSS spectra and VISTA photometry.
  • SFH bin edges = 12 bins with specified lookback times (0 to 13182 Myr)
    Non-parametric SFH binning adopted from Leja et al. (2019a); affects flexibility of SFH recovery.
assumptions (5)
  • domain assumption BPASS v2.2.1 default models approximate the true emission of EAGLE galaxies
    Mock spectra are generated with v2.2.1 (Section 3.2), making v2.2.1 the reference truth for measuring model-induced offsets.
  • domain assumption EAGLE L0025N0376 z=0 galaxies with M*>1e9 Msun are representative of the z=0 massive galaxy population
    Sample selection in Section 3.1; limits generalization to lower masses and higher redshifts.
  • domain assumption Salim et al. (2018) attenuation curves and the sSFR-based classification are appropriate for the mock observations
    Dust attenuation is applied and fitted using these laws (Sections 3.2 and 3.3).
  • domain assumption bagpipes non-parametric SFH with Student's-t priors recovers the true SFH sufficiently for the comparison
    Fitting method described in Section 3.3; SFH prior could bias inferred parameters.
  • domain assumption Nebular emission is negligible for the inferences
    Nebular emission is neglected in both model construction and fitting (Section 3.3).

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Pith. "Pith review of Impact of Uncertainties in Spectral Energy Distribution Modelling on Inferred Galaxy Properties." pith.science (2026). https://pith.science/paper/HKXNF4EL

@misc{pith2026250902741,
  author       = {Pith},
  title        = {Pith review of: Impact of Uncertainties in Spectral Energy Distribution Modelling on Inferred Galaxy Properties},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HKXNF4EL}},
  note         = {Machine review of arXiv:2509.02741}
}
abstract

Interpreting galaxy properties from astronomical surveys relies heavily on spectral energy distribution (SED) modelling, yet uncertainties in key model ingredients are often overlooked. By leveraging a $z\sim0$ galaxy sample from the EAGLE simulation, we generate synthetic SDSS spectral and VISTA photometric observations with controlled assumptions, to assess how variations in stellar spectral library, initial mass function (IMF) and metallicity prescriptions within the BPASS-framework affect inferred galaxy properties. Our analysis combines spectral fitting from 3800 to 9200 A with photometric constraints extending to 2.3 $\mu$m, enabling robust assessment across a broad wavelength baseline. Our findings reveal mass, age and star formation rate vary by $0.27\pm0.09$, $0.19\pm0.11$ and $1.4\pm1.0$ dex, respectively, greater than observational uncertainties reported in surveys. Notably, we find stellar spectral library choice is capable of transforming a galaxy from appearing star-forming to quiescent, while a fixed metallicity assumption yields systematic biases when the chosen metallicity is incorrect. These modelling differences impact the reconstructed total mass assembly history in galaxies by up to $\sim12$ percent and bias the demographic and star formation history conclusions drawn from surveys. As upcoming missions like Euclid, Roman and CASTOR aim to characterise galaxy evolution with unprecedented precision, our results highlight the need for careful propagation of SED modelling uncertainties and transparency in model selection.

Figures

Figures reproduced from arXiv: 2509.02741 by the authors.

Figure 1
Figure 1. Spectra generated from the BPASS framework using different stellar spectral libraries (top panel) and IMF prescriptions (bottom panel) for a 10 Myr old stellar population. The top panel includes v2.2.1 in brown, AP in blue, BaSeL in orange, C3K in green and CKC in pink. The bottom panel shows, in order from top to bottom, the shallow IMF in blue, C03 prescription in pink, default in brown, continuous in green, and s… view at source ↗
Figure 2
Figure 2. Same as [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Flowchart outlining the methodology used in our work. The blue box (upper left) describes the BPASS framework and the steps taken to generate simple stellar population models (Section 2). Different IMF and stellar spectral libraries are applied during the population and spectral synthesis steps, respectively, to generate models with varying underlying assumptions. The yellow box (lower left) represents our simulated… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Illustration of mock SDSS spectra produced using simulated galaxy ID 197376 when applying different stellar spectral libraries (top panel) and IMF prescriptions (bottom panel). Top panel shows the spectral libraries of v2.2.1 in brown, AP in blue, BaSeL in orange, C3K …
Figure 6
Figure 6. Figure 6: Inferred galaxy property difference between the v2.2.1 BPASS framework and all spectral library variations, plotted as a function of the values obtained using the v2.2.1 framework. The AP, BaSeL, C3K and CKC spectral libraries are represented by blue circles, orange sq…
Figure 8
Figure 8. Figure 8 [PITH_FULL_IMAGE:figures/full_fig_p011_8.png]
Figure 10
Figure 10. Figure 10: shows, for each galaxy, the difference in derived parameters between the two metallicity tests and the fixed-metallicity run, plotted as a function of the fixed-metallicity parameter values. The mean difference across all galaxies in inferred parameter values is prese…
Figure 12
Figure 12. Figure 12: bagpipes fits typically underestimate metallicities by about 10% of Solar, relative to the EAGLE values, while agreeing on the relative enrichment of different galaxies. The posterior uncertainty quoted by the fitting algorithm for any individual galaxy is substan￾tia…
Figure 13
Figure 13. Figure 13: Cumulative stellar mass fraction formed in all simulated galaxies fitted in this work, shown as a function of lookback time. The v2.2.1 BPASS framework with default IMF and fixed metallicity prescriptions highlight the comparison results plotted as the solid brown lin…

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Works this paper leans on

199 extracted references · 8 canonical work pages

  1. [1]

    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.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    N., et al., 2009, @doi [ ] 10.1088/0067-0049/182/2/543 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..543A 182, 543

    Abazajian K. N., et al., 2009, @doi [ ] 10.1088/0067-0049/182/2/543 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..543A 182, 543

    doi:10.1088/0067-0049/182/2/543 2009

  3. [3]

    arXiv:1902.05569

    Akeson R., et al., 2019, @doi [preprint] 10.48550/arXiv.1902.05569 , https://ui.adsabs.harvard.edu/abs/2019arXiv190205569A p. arXiv:1902.05569

    arXiv doi:10.48550/arxiv.1902.05569 2019

  4. [4]

    A., Barklem P

    Allende Prieto C., Koesterke L., Hubeny I., Bautista M. A., Barklem P. S., Nahar S. N., 2018, @doi [ ] 10.1051/0004-6361/201732484 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A..25A 618, A25

    doi:10.1051/0004-6361/201732484 2018

  5. [6]

    Astropy Collaboration et al., 2013, @doi [ ] 10.1051/0004-6361/201322068 , http://adsabs.harvard.edu/abs/2013A

    doi:10.1051/0004-6361/201322068 2013

  6. [7]

    Astropy Collaboration et al., 2018, @doi [ ] 10.3847/1538-3881/aabc4f , https://ui.adsabs.harvard.edu/abs/2018AJ....156..123A 156, 123

    doi:10.3847/1538-3881/aabc4f 2018

  7. [8]

    R., Meyer M

    Bastian N., Covey K. R., Meyer M. R., 2010, @doi [ ] 10.1146/annurev-astro-082708-101642 , https://ui.adsabs.harvard.edu/abs/2010ARA&A..48..339B 48, 339

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

  8. [9]

    R., Meyer M

    Bastian N., Covey K. R., Meyer M. R., 2011, in Johns-Krull C., Browning M. K., West A. A., eds, Astronomical Society of the Pacific Conference Series Vol. 448, 16th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun. p. 361

    2011

Show all 199 references
  1. [10]

    Bellstedt S., Robotham A. S. G., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2410.17698 , https://ui.adsabs.harvard.edu/abs/2024arXiv241017698B p. arXiv:2410.17698

    2024 doi arXiv

  2. [11]

    Bellstedt S., et al., 2020, @doi [ ] 10.1093/mnras/staa2620 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.5581B 498, 5581

    2020 doi

  3. [12]

    Bertelli G., Bressan A., Chiosi C., Fagotto F., Nasi E., 1994, , https://ui.adsabs.harvard.edu/abs/1994A&AS..106..275B 106, 275

    1994

  4. [13]

    A., Lu Y., Benson A., Katsianis A., Barraza M., 2019, @doi [ ] 10.3847/1538-4357/ab16ec , https://ui.adsabs.harvard.edu/abs/2019ApJ...877....6B 877, 6

    Blanc G. A., Lu Y., Benson A., Katsianis A., Barraza M., 2019, @doi [ ] 10.3847/1538-4357/ab16ec , https://ui.adsabs.harvard.edu/abs/2019ApJ...877....6B 877, 6

    2019 doi

  5. [14]

    K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

    Boquien M., Burgarella D., Roehlly Y., Buat V., Ciesla L., Corre D., Inoue A. K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

    2019 doi

  6. [16]

    Bravo M., Robotham A. S. G., Lagos C. d. P., Davies L. J. M., Bellstedt S., Thorne J. E., 2022, @doi [ ] 10.1093/mnras/stac321 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.511.5405B 511, 5405

    2022 doi

  7. [18]

    M., Eldridge J

    Briel M. M., Eldridge J. J., Stanway E. R., Stevance H. F., Chrimes A. A., 2022, @doi [ ] 10.1093/mnras/stac1100 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514.1315B 514, 1315

    2022 doi

  8. [20]

    arXiv:2502.12239

    Britavskiy N., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2502.12239 , https://ui.adsabs.harvard.edu/abs/2025arXiv250212239B p. arXiv:2502.12239

    2025 doi arXiv

  9. [22]

    M., Stanway E

    Byrne C. M., Stanway E. R., 2023, @doi [ ] 10.1093/mnras/stad832 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.521.4995B 521, 4995

    2023 doi

  10. [23]

    M., Stanway E

    Byrne C. M., Stanway E. R., Eldridge J. J., McSwiney L., Townsend O. T., 2022, @doi [ ] 10.1093/mnras/stac807 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.5329B 512, 5329

    2022 doi

  11. [24]

    M., Eldridge J

    Byrne C. M., Eldridge J. J., Stanway E. R., 2025, @doi [ ] 10.1093/mnras/staf178 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537.2433B 537, 2433

    2025 doi

  12. [25]

    J., Katz H., Witten C., Saxena A., Laporte N., Bunker A

    Cameron A. J., Katz H., Witten C., Saxena A., Laporte N., Bunker A. J., 2023, @doi [preprint] 10.48550/arXiv.2311.02051 , https://ui.adsabs.harvard.edu/abs/2023arXiv231102051C p. arXiv:2311.02051

    2023 doi arXiv

  13. [26]

    Cappellari M., et al., 2012, @doi [ ] 10.1038/nature10972 , https://ui.adsabs.harvard.edu/abs/2012Natur.484..485C 484, 485

    2012 doi

  14. [28]

    C., McLure R

    Carnall A. C., McLure R. J., Dunlop J. S., Dav \'e R., 2018, @doi [ ] 10.1093/mnras/sty2169 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.4379C 480, 4379

    2018 doi

  15. [29]

    Cassisi S., Castellani V., Ciarcelluti P., Piotto G., Zoccali M., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03457.x , https://ui.adsabs.harvard.edu/abs/2000MNRAS.315..679C 315, 679

    2000

  16. [30]

    Castelli F., 2005, Memorie della Societa Astronomica Italiana Supplementi, https://ui.adsabs.harvard.edu/abs/2005MSAIS...8...25C 8, 25

    2005

  17. [31]

    Chabrier G., 2003, @doi [ ] 10.1086/376392 , https://ui.adsabs.harvard.edu/abs/2003PASP..115..763C 115, 763

    2003 doi

  18. [32]

    Chauke P., et al., 2018, @doi [ ] 10.3847/1538-4357/aac324 , https://ui.adsabs.harvard.edu/abs/2018ApJ...861...13C 861, 13

    2018 doi

  19. [33]

    Chevallard J., Charlot S., 2016, @doi [ ] 10.1093/mnras/stw1756 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.1415C 462, 1415

    2016 doi

  20. [34]

    D., 2016, @doi [ ] 10.3847/0004-637X/823/2/102 , https://ui.adsabs.harvard.edu/abs/2016ApJ...823..102C 823, 102

    Choi J., Dotter A., Conroy C., Cantiello M., Paxton B., Johnson B. D., 2016, @doi [ ] 10.3847/0004-637X/823/2/102 , https://ui.adsabs.harvard.edu/abs/2016ApJ...823..102C 823, 102

    2016 doi

  21. [35]

    Chon S., Omukai K., Schneider R., 2021, @doi [ ] 10.1093/mnras/stab2497 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.4175C 508, 4175

    2021 doi

  22. [37]

    Coelho P. R. T., 2014, @doi [ ] 10.1093/mnras/stu365 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.440.1027C 440, 1027

    2014 doi

  23. [38]

    Coelho P. R. T., Bruzual G., Charlot S., 2020, @doi [ ] 10.1093/mnras/stz3023 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.2025C 491, 2025

    2020 doi

  24. [39]

    E., White M., 2009, @doi [ ] 10.1088/0004-637X/699/1/486 , https://ui.adsabs.harvard.edu/abs/2009ApJ...699..486C 699, 486

    Conroy C., Gunn J. E., White M., 2009, @doi [ ] 10.1088/0004-637X/699/1/486 , https://ui.adsabs.harvard.edu/abs/2009ApJ...699..486C 699, 486

    2009 doi

  25. [40]

    J., van Dokkum P

    Conroy C., Graves G. J., van Dokkum P. G., 2014, @doi [ ] 10.1088/0004-637X/780/1/33 , https://ui.adsabs.harvard.edu/abs/2014ApJ...780...33C 780, 33

    2014 doi

  26. [41]

    Cordier D., Pietrinferni A., Cassisi S., Salaris M., 2007, @doi [ ] 10.1086/509870 , https://ui.adsabs.harvard.edu/abs/2007AJ....133..468C 133, 468

    2007 doi

  27. [42]

    C., Fazio G

    C \^o te P., et al., 2012, in Clampin M. C., Fazio G. G., MacEwen H. A., Oschmann Jr. J. M., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 8442, Space Telescopes and Instrumentation 2012: Optical, Infrared, and Millimeter Wave. p. 844215...

    2012 doi

  28. [43]

    C \^o te P., et al., 2019, in Canadian Long Range Plan for Astronomy and Astrophysics White Papers. p. 18, @doi 10.5281/zenodo.3758463

    2019 doi

  29. [44]

    Courteau S., et al., 2014, @doi [Reviews of Modern Physics] 10.1103/RevModPhys.86.47 , https://ui.adsabs.harvard.edu/abs/2014RvMP...86...47C 86, 47

    2014 doi

  30. [45]

    A., et al., 2015, @doi [ ] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    Crain R. A., et al., 2015, @doi [ ] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    2015 doi

  31. [46]

    Cucciati O., et al., 2012, @doi [ ] 10.1051/0004-6361/201118010 , https://ui.adsabs.harvard.edu/abs/2012A&A...539A..31C 539, A31

    2012 doi

  32. [47]

    R., Hutter A., Dayal P., Gottl \"o ber S., Heintz K

    Cueto E. R., Hutter A., Dayal P., Gottl \"o ber S., Heintz K. E., Mason C., Trebitsch M., Yepes G., 2024, @doi [ ] 10.1051/0004-6361/202349017 , https://ui.adsabs.harvard.edu/abs/2024A&A...686A.138C 686, A138

    2024 doi

  33. [49]

    D'Silva J. C. J., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.03431 , https://ui.adsabs.harvard.edu/abs/2025arXiv250303431D p. arXiv:2503.03431

    2025 doi arXiv

  34. [50]

    Davidzon I., et al., 2017, @doi [ ] 10.1051/0004-6361/201730419 , https://ui.adsabs.harvard.edu/abs/2017A&A...605A..70D 605, A70

    2017 doi

  35. [51]

    Davies L. J. M., et al., 2016, @doi [ ] 10.1093/mnras/stw1342 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461..458D 461, 458

    2016 doi

  36. [52]

    C., Budav \'a ri T., 2003, @doi [ ] 10.1086/368111 , https://ui.adsabs.harvard.edu/abs/2003ApJ...587...25D 587, 25

    Dickinson M., Papovich C., Ferguson H. C., Budav \'a ri T., 2003, @doi [ ] 10.1086/368111 , https://ui.adsabs.harvard.edu/abs/2003ApJ...587...25D 587, 25

    2003 doi

  37. [53]

    Doi M., et al., 2010, @doi [ ] 10.1088/0004-6256/139/4/1628 , https://ui.adsabs.harvard.edu/abs/2010AJ....139.1628D 139, 1628

    2010 doi

  38. [54]

    Dolag K., Borgani S., Murante G., Springel V., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15034.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.399..497D 399, 497

    2009

  39. [56]

    Donada J., et al., 2023, @doi [ ] 10.1051/0004-6361/202245219 , https://ui.adsabs.harvard.edu/abs/2023A&A...675A..89D 675, A89

    2023 doi

  40. [57]

    P., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2010.18188.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413..971D 413, 971

    Driver S. P., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2010.18188.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413..971D 413, 971

    2011

  41. [58]

    P., et al., 2018, @doi [ ] 10.1093/mnras/stx2728 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.2891D 475, 2891

    Driver S. P., et al., 2018, @doi [ ] 10.1093/mnras/stx2728 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.2891D 475, 2891

    2018 doi

  42. [59]

    Drory N., Salvato M., Gabasch A., Bender R., Hopp U., Feulner G., Pannella M., 2005, @doi [ ] 10.1086/428044 , https://ui.adsabs.harvard.edu/abs/2005ApJ...619L.131D 619, L131

    2005 doi

  43. [60]

    M., Iglesias-P \'a ramo J., Moll \'a M., P \'e rez-Montero E., Kehrig C., Pilyugin L

    Duarte Puertas S., Vilchez J. M., Iglesias-P \'a ramo J., Moll \'a M., P \'e rez-Montero E., Kehrig C., Pilyugin L. S., Zinchenko I. A., 2022, @doi [ ] 10.1051/0004-6361/202141571 , https://ui.adsabs.harvard.edu/abs/2022A&A...666A.186D 666, A186

    2022 doi

  44. [61]

    J., Stanway E

    Eldridge J. J., Stanway E. R., Xiao L., McClelland L. A. S., Taylor G., Ng M., Greis S. M. L., Bray J. C., 2017, @doi [ ] 10.1017/pasa.2017.51 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...58E 34, e058

    2017 doi

  45. [62]

    arXiv:2405.13491

    Euclid Collaboration et al., 2024, @doi [preprint] 10.48550/arXiv.2405.13491 , https://ui.adsabs.harvard.edu/abs/2024arXiv240513491E p. arXiv:2405.13491

    2024 doi

  46. [63]

    J., Gorgas J., Peletier R

    Falc \'o n-Barroso J., S \'a nchez-Bl \'a zquez P., Vazdekis A., Ricciardelli E., Cardiel N., Cenarro A. J., Gorgas J., Peletier R. F., 2011, @doi [ ] 10.1051/0004-6361/201116842 , https://ui.adsabs.harvard.edu/abs/2011A&A...532A..95F 532, A95

    2011 doi

  47. [64]

    M., et al., 2009, @doi [ ] 10.1088/0004-637X/706/2/1364 , https://ui.adsabs.harvard.edu/abs/2009ApJ...706.1364F 706, 1364

    F \"o rster Schreiber N. M., et al., 2009, @doi [ ] 10.1088/0004-637X/706/2/1364 , https://ui.adsabs.harvard.edu/abs/2009ApJ...706.1364F 706, 1364

    2009 doi

  48. [65]

    Fu X., Bressan A., Marigo P., Girardi L., Montalb \'a n J., Chen Y., Nanni A., 2018, @doi [ ] 10.1093/mnras/sty235 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.476..496F 476, 496

    2018 doi

  49. [66]

    Geha M., et al., 2013, @doi [ ] 10.1088/0004-637X/771/1/29 , https://ui.adsabs.harvard.edu/abs/2013ApJ...771...29G 771, 29

    2013 doi

  50. [67]

    Genzel R., et al., 2015, @doi [ ] 10.1088/0004-637X/800/1/20 , https://ui.adsabs.harvard.edu/abs/2015ApJ...800...20G 800, 20

    2015 doi

  51. [68]

    Girardi L., Bressan A., Bertelli G., Chiosi C., 2000, @doi [ ] 10.1051/aas:2000126 , https://ui.adsabs.harvard.edu/abs/2000A&AS..141..371G 141, 371

    2000 doi

  52. [69]

    A., et al., 2011, @doi [ ] 10.1088/0067-0049/197/2/35 , https://ui.adsabs.harvard.edu/abs/2011ApJS..197...35G 197, 35

    Grogin N. A., et al., 2011, @doi [ ] 10.1088/0067-0049/197/2/35 , https://ui.adsabs.harvard.edu/abs/2011ApJS..197...35G 197, 35

    2011 doi

  53. [70]

    E., et al., 1998, @doi [ ] 10.1086/300645 , https://ui.adsabs.harvard.edu/abs/1998AJ....116.3040G 116, 3040

    Gunn J. E., et al., 1998, @doi [ ] 10.1086/300645 , https://ui.adsabs.harvard.edu/abs/1998AJ....116.3040G 116, 3040

    1998 doi

  54. [71]

    E., et al., 2006, @doi [ ] 10.1086/500975 , https://ui.adsabs.harvard.edu/abs/2006AJ....131.2332G 131, 2332

    Gunn J. E., et al., 2006, @doi [ ] 10.1086/500975 , https://ui.adsabs.harvard.edu/abs/2006AJ....131.2332G 131, 2332

    2006 doi

  55. [72]

    R., Gr \"a fener G., 2003, @doi [ ] 10.1051/0004-6361:20031308 , https://ui.adsabs.harvard.edu/abs/2003A&A...410..993H 410, 993

    Hamann W. R., Gr \"a fener G., 2003, @doi [ ] 10.1051/0004-6361:20031308 , https://ui.adsabs.harvard.edu/abs/2003A&A...410..993H 410, 993

    2003 doi

  56. [73]

    Han Y., Han Z., 2012, @doi [ ] 10.1088/0004-637X/749/2/123 , https://ui.adsabs.harvard.edu/abs/2012ApJ...749..123H 749, 123

    2012 doi

  57. [74]

    Han Y., Han Z., 2014, @doi [ ] 10.1088/0067-0049/215/1/2 , https://ui.adsabs.harvard.edu/abs/2014ApJS..215....2H 215, 2

    2014 doi

  58. [75]

    Han Y., Han Z., 2019, @doi [ ] 10.3847/1538-4365/aaeffa , https://ui.adsabs.harvard.edu/abs/2019ApJS..240....3H 240, 3

    2019 doi

  59. [76]

    Haskell P., Das S., Smith D. J. B., Cochrane R. K., Hayward C. C., Angl \'e s-Alc \'a zar D., 2024, @doi [ ] 10.1093/mnrasl/slae019 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.530L...7H 530, L7

    2024 doi

  60. [77]

    Y., 2024, @doi [ ] 10.1146/annurev-astro-052622-031748 , https://ui.adsabs.harvard.edu/abs/2024ARA&A..62...63H 62, 63

    Hennebelle P., Grudi \'c M. Y., 2024, @doi [ ] 10.1146/annurev-astro-052622-031748 , https://ui.adsabs.harvard.edu/abs/2024ARA&A..62...63H 62, 63

    2024 doi

  61. [79]

    M., 2018, @doi [ ] 10.1017/pasa.2018.29 , https://ui.adsabs.harvard.edu/abs/2018PASA...35...39H 35, e039

    Hopkins A. M., 2018, @doi [ ] 10.1017/pasa.2018.29 , https://ui.adsabs.harvard.edu/abs/2018PASA...35...39H 35, e039

    2018 doi

  62. [80]

    M., Beacom J

    Hopkins A. M., Beacom J. F., 2006, @doi [ ] 10.1086/506610 , https://ui.adsabs.harvard.edu/abs/2006ApJ...651..142H 651, 142

    2006 doi

  63. [81]

    Huertas-Company M., et al., 2016, @doi [ ] 10.1093/mnras/stw1866 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.4495H 462, 4495

    2016 doi

  64. [82]

    Ilbert O., et al., 2010, @doi [ ] 10.1088/0004-637X/709/2/644 , https://ui.adsabs.harvard.edu/abs/2010ApJ...709..644I 709, 644

    2010 doi

  65. [83]

    Ilbert O., et al., 2013, @doi [ ] 10.1051/0004-6361/201321100 , https://ui.adsabs.harvard.edu/abs/2013A&A...556A..55I 556, A55

    2013 doi

  66. [84]

    N., Tominaga N., Kobayashi C., Nomoto K., 2018, @doi [ ] 10.3847/1538-4357/aab3de , https://ui.adsabs.harvard.edu/abs/2018ApJ...857...46I 857, 46

    Ishigaki M. N., Tominaga N., Kobayashi C., Nomoto K., 2018, @doi [ ] 10.3847/1538-4357/aab3de , https://ui.adsabs.harvard.edu/abs/2018ApJ...857...46I 857, 46

    2018 doi

  67. [85]

    G., Gawiser E., Faber S

    Iyer K. G., Gawiser E., Faber S. M., Ferguson H. C., Kartaltepe J., Koekemoer A. M., Pacifici C., Somerville R. S., 2019, @doi [ ] 10.3847/1538-4357/ab2052 , https://ui.adsabs.harvard.edu/abs/2019ApJ...879..116I 879, 116

    2019 doi

  68. [86]

    D., Leja J., Conroy C., Speagle J

    Johnson B. D., Leja J., Conroy C., Speagle J. S., 2021, @doi [ ] 10.3847/1538-4365/abef67 , https://ui.adsabs.harvard.edu/abs/2021ApJS..254...22J 254, 22

    2021 doi

  69. [87]

    T., Stanway E

    Jones G. T., Stanway E. R., 2023, @doi [ ] 10.1093/mnras/stad2683 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.525.5720J 525, 5720

    2023 doi

  70. [88]

    T., Stanway E

    Jones G. T., Stanway E. R., Carnall A. C., 2022, @doi [ ] 10.1093/mnras/stac1667 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514.5706J 514, 5706

    2022 doi

  71. [89]

    Kauffmann G., et al., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06291.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.341...33K 341, 33

    2003

  72. [90]

    D., et al., 2014, @doi [ ] 10.1088/0004-637X/783/2/110 , https://ui.adsabs.harvard.edu/abs/2014ApJ...783..110K 783, 110

    Kelson D. D., et al., 2014, @doi [ ] 10.1088/0004-637X/783/2/110 , https://ui.adsabs.harvard.edu/abs/2014ApJ...783..110K 783, 110

    2014 doi

  73. [91]

    J., et al., 2024, @doi [ ] 10.1093/mnras/stad3499 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.5525K 527, 5525

    Kim S. J., et al., 2024, @doi [ ] 10.1093/mnras/stad3499 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.5525K 527, 5525

    2024 doi

  74. [92]

    C., 2011, @doi [ ] 10.1088/0004-637X/727/2/64 , https://ui.adsabs.harvard.edu/abs/2011ApJ...727...64K 727, 64

    Kirk H., Myers P. C., 2011, @doi [ ] 10.1088/0004-637X/727/2/64 , https://ui.adsabs.harvard.edu/abs/2011ApJ...727...64K 727, 64

    2011 doi

  75. [93]

    T., Sansom A

    Knowles A. T., Sansom A. E., Allende Prieto C., Vazdekis A., 2021, @doi [ ] 10.1093/mnras/stab1001 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.504.2286K 504, 2286

    2021 doi

  76. [94]

    M., et al., 2011, @doi [ ] 10.1088/0067-0049/197/2/36 , https://ui.adsabs.harvard.edu/abs/2011ApJS..197...36K 197, 36

    Koekemoer A. M., et al., 2011, @doi [ ] 10.1088/0067-0049/197/2/36 , https://ui.adsabs.harvard.edu/abs/2011ApJS..197...36K 197, 36

    2011 doi

  77. [95]

    A., Strom A

    Korhonen Cuestas N. A., Strom A. L., Miller T. B., Steidel C. C., Trainor R. F., Rudie G. C., Nu \ n ez E. H., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.10800 , https://ui.adsabs.harvard.edu/abs/2025arXiv250310800K p. arXiv:2503.10800

    2025 doi arXiv

  78. [96]

    Kriek M., Conroy C., 2013, @doi [ ] 10.1088/2041-8205/775/1/L16 , https://ui.adsabs.harvard.edu/abs/2013ApJ...775L..16K 775, L16

    2013 doi

  79. [98]

    Kroupa P., 2002, @doi [Science] 10.1126/science.1067524 , https://ui.adsabs.harvard.edu/abs/2002Sci...295...82K 295, 82

    2002 doi

  80. [99]

    A., Gilmore G., 1993, @doi [ ] 10.1093/mnras/262.3.545 , https://ui.adsabs.harvard.edu/abs/1993MNRAS.262..545K 262, 545

    Kroupa P., Tout C. A., Gilmore G., 1993, @doi [ ] 10.1093/mnras/262.3.545 , https://ui.adsabs.harvard.edu/abs/1993MNRAS.262..545K 262, 545

    1993 doi

  81. [100]

    D., Gilmore G., eds, Planets, Stars and Stellar Systems, Vol

    Kroupa P., Weidner C., Pflamm-Altenburg J., Thies I., Dabringhausen J., Marks M., Maschberger T., 2013, in Oswalt T. D., Gilmore G., eds, Planets, Stars and Stellar Systems, Vol. 5, Galactic Structure and Stellar Populations. Springer, Dordrecht, p. 115

    2013

  82. [101]

    arXiv:2410.07311

    Kroupa P., Gjergo E., Jerabkova T., Yan Z., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2410.07311 , https://ui.adsabs.harvard.edu/abs/2024arXiv241007311K p. arXiv:2410.07311

    2024 doi arXiv

  83. [102]

    L., 1970, SAO Special Report, https://ui.adsabs.harvard.edu/abs/1970SAOSR.309.....K 309

    Kurucz R. L., 1970, SAO Special Report, https://ui.adsabs.harvard.edu/abs/1970SAOSR.309.....K 309

    1970

  84. [103]

    L., 1992, in Barbuy B., Renzini A., eds, Proc

    Kurucz R. L., 1992, in Barbuy B., Renzini A., eds, Proc. IAU Symp. Vol. 149, The Stellar Populations of Galaxies. p. 225

    1992

  85. [104]

    L., 1993, SYNTHE spectrum synthesis programs and line data

    Kurucz R. L., 1993, SYNTHE spectrum synthesis programs and line data . Kurucz CD-ROM No. 18. Smithsonian Astrophysical Observatory, Cambridge, MA

    1993

  86. [105]

    Laigle C., et al., 2016, @doi [ ] 10.3847/0067-0049/224/2/24 , https://ui.adsabs.harvard.edu/abs/2016ApJS..224...24L 224, 24

    2016 doi

  87. [106]

    Le Floc'h E., et al., 2005, @doi [ ] 10.1086/432789 , https://ui.adsabs.harvard.edu/abs/2005ApJ...632..169L 632, 169

    2005 doi

  88. [107]

    D., Cannon J

    Lee H., Skillman E. D., Cannon J. M., Jackson D. C., Gehrz R. D., Polomski E. F., Woodward C. E., 2006, @doi [ ] 10.1086/505573 , https://ui.adsabs.harvard.edu/abs/2006ApJ...647..970L 647, 970

    2006 doi

  89. [108]

    D., Conroy C., van Dokkum P

    Leja J., Johnson B. D., Conroy C., van Dokkum P. G., Byler N., 2017, @doi [ ] 10.3847/1538-4357/aa5ffe , https://ui.adsabs.harvard.edu/abs/2017ApJ...837..170L 837, 170

    2017 doi

  90. [109]

    C., Johnson B

    Leja J., Carnall A. C., Johnson B. D., Conroy C., Speagle J. S., 2019a, @doi [ ] 10.3847/1538-4357/ab133c , https://ui.adsabs.harvard.edu/abs/2019ApJ...876....3L 876, 3

    doi

  91. [110]

    Leja J., et al., 2019b, @doi [ ] 10.3847/1538-4357/ab1d5a , https://ui.adsabs.harvard.edu/abs/2019ApJ...877..140L 877, 140

    doi

  92. [111]

    Lejeune T., Cuisinier F., Buser R., 1998, @doi [ ] 10.1051/aas:1998405 , https://ui.adsabs.harvard.edu/abs/1998A&AS..130...65L 130, 65

    1998 doi

  93. [112]

    S., Diaz M

    Levenhagen R. S., Diaz M. P., Coelho P. R. T., Hubeny I., 2017, @doi [ ] 10.3847/1538-4365/aa7681 , https://ui.adsabs.harvard.edu/abs/2017ApJS..231....1L 231, 1

    2017 doi

  94. [113]

    J., Le Fevre O., Hammer F., Crampton D., 1996, @doi [ ] 10.1086/309975 , https://ui.adsabs.harvard.edu/abs/1996ApJ...460L...1L 460, L1

    Lilly S. J., Le Fevre O., Hammer F., Crampton D., 1996, @doi [ ] 10.1086/309975 , https://ui.adsabs.harvard.edu/abs/1996ApJ...460L...1L 460, L1

    1996 doi

  95. [114]

    Liske J., et al., 2015, @doi [ ] 10.1093/mnras/stv1436 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452.2087L 452, 2087

    2015 doi

  96. [115]

    Liu S., Gu Y., Yuan Q., Lu S., Bao M., Fang G., Fan L., 2021, @doi [ ] 10.3847/1538-4357/ac2817 , https://ui.adsabs.harvard.edu/abs/2021ApJ...923...46L 923, 46

    2021 doi

  97. [116]

    D., Conroy C., Dav \'e R., 2020, @doi [ ] 10.3847/1538-4357/abbfa7 , https://ui.adsabs.harvard.edu/abs/2020ApJ...904...33L 904, 33

    Lower S., Narayanan D., Leja J., Johnson B. D., Conroy C., Dav \'e R., 2020, @doi [ ] 10.3847/1538-4357/abbfa7 , https://ui.adsabs.harvard.edu/abs/2020ApJ...904...33L 904, 33

    2020 doi

  98. [117]

    D., Conroy C., Dav \'e R., 2022, @doi [ ] 10.3847/1538-4357/ac6959 , https://ui.adsabs.harvard.edu/abs/2022ApJ...931...14L 931, 14

    Lower S., Narayanan D., Leja J., Johnson B. D., Conroy C., Dav \'e R., 2022, @doi [ ] 10.3847/1538-4357/ac6959 , https://ui.adsabs.harvard.edu/abs/2022ApJ...931...14L 931, 14

    2022 doi

  99. [118]

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

    2014 doi

  100. [119]

    C., Dickinson M

    Madau P., Ferguson H. C., Dickinson M. E., Giavalisco M., Steidel C. C., Fruchter A., 1996, @doi [ ] 10.1093/mnras/283.4.1388 , https://ui.adsabs.harvard.edu/abs/1996MNRAS.283.1388M 283, 1388

    1996 doi

  101. [120]

    Madau P., Pozzetti L., Dickinson M., 1998, @doi [ ] 10.1086/305523 , https://ui.adsabs.harvard.edu/abs/1998ApJ...498..106M 498, 106

    1998 doi

  102. [121]

    Maraston C., Daddi E., Renzini A., Cimatti A., Dickinson M., Papovich C., Pasquali A., Pirzkal N., 2006, @doi [ ] 10.1086/508143 , https://ui.adsabs.harvard.edu/abs/2006ApJ...652...85M 652, 85

    2006 doi

  103. [122]

    Marigo P., Girardi L., Bressan A., Groenewegen M. A. T., Silva L., Granato G. L., 2008, @doi [ ] 10.1051/0004-6361:20078467 , https://ui.adsabs.harvard.edu/abs/2008A&A...482..883M 482, 883

    2008 doi

  104. [124]

    McAlpine S., et al., 2016, @doi [Astronomy and Computing] 10.1016/j.ascom.2016.02.004 , https://ui.adsabs.harvard.edu/abs/2016A&C....15...72M 15, 72

    2016 doi

  105. [125]

    T., et al., 2020, @doi [ ] 10.3847/1538-4357/ab9ffc , https://ui.adsabs.harvard.edu/abs/2020ApJ...899...87M 899, 87

    Mendel J. T., et al., 2020, @doi [ ] 10.3847/1538-4357/ab9ffc , https://ui.adsabs.harvard.edu/abs/2020ApJ...899...87M 899, 87

    2020 doi

  106. [126]

    M \'e sz \'a ros S., et al., 2012, @doi [ ] 10.1088/0004-6256/144/4/120 , https://ui.adsabs.harvard.edu/abs/2012AJ....144..120M 144, 120

    2012 doi

  107. [127]

    Meynet G., Maeder A., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0006404 , https://ui.adsabs.harvard.edu/abs/2000A&A...361..101M 361, 101

    2000 doi arXiv

  108. [128]

    arXiv:2506.02123

    Mizener A., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2506.02123 , https://ui.adsabs.harvard.edu/abs/2025arXiv250602123M p. arXiv:2506.02123

    2025 doi arXiv

  109. [129]

    Moe M., Di Stefano R., 2017, @doi [ ] 10.3847/1538-4365/aa6fb6 , https://ui.adsabs.harvard.edu/abs/2017ApJS..230...15M 230, 15

    2017 doi

  110. [130]

    Muzzin A., et al., 2013, @doi [ ] 10.1088/0004-637X/777/1/18 , https://ui.adsabs.harvard.edu/abs/2013ApJ...777...18M 777, 18

    2013 doi

  111. [131]

    C., 2009, @doi [ ] 10.1051/0004-6361/200912497 , https://ui.adsabs.harvard.edu/abs/2009A&A...507.1793N 507, 1793

    Noll S., Burgarella D., Giovannoli E., Buat V., Marcillac D., Mu \ n oz-Mateos J. C., 2009, @doi [ ] 10.1051/0004-6361/200912497 , https://ui.adsabs.harvard.edu/abs/2009A&A...507.1793N 507, 1793

    2009 doi

  112. [133]

    Osborne C., Salim S., 2024, @doi [ ] 10.3847/1538-4357/ad17c8 , https://ui.adsabs.harvard.edu/abs/2024ApJ...962...59O 962, 59

    2024 doi

  113. [134]

    Pacifici C., et al., 2015, @doi [ ] 10.1093/mnras/stu2447 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.447..786P 447, 786

    2015 doi

  114. [135]

    Pacifici C., et al., 2023, @doi [ ] 10.3847/1538-4357/acacff , https://ui.adsabs.harvard.edu/abs/2023ApJ...944..141P 944, 141

    2023 doi

  115. [136]

    D., Xilouris E

    Paspaliaris E. D., Xilouris E. M., Nersesian A., Bianchi S., Georgantopoulos I., Masoura V. A., Magdis G. E., Plionis M., 2023, @doi [ ] 10.1051/0004-6361/202244796 , https://ui.adsabs.harvard.edu/abs/2023A&A...669A..11P 669, A11

    2023 doi

  116. [137]

    R., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2502.02644 , https://ui.adsabs.harvard.edu/abs/2025arXiv250202644P p

    Patrick L. R., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2502.02644 , https://ui.adsabs.harvard.edu/abs/2025arXiv250202644P p. arXiv:2502.02644

    2025 doi arXiv

  117. [138]

    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

    1998

  118. [139]

    G., et al., 2008, @doi [ ] 10.1086/523690 , https://ui.adsabs.harvard.edu/abs/2008ApJ...675..234P 675, 234

    P \'e rez-Gonz \'a lez P. G., et al., 2008, @doi [ ] 10.1086/523690 , https://ui.adsabs.harvard.edu/abs/2008ApJ...675..234P 675, 234

    2008 doi

  119. [140]

    Pietrinferni A., Cassisi S., Salaris M., Castelli F., 2004, @doi [ ] 10.1086/422498 , https://ui.adsabs.harvard.edu/abs/2004ApJ...612..168P 612, 168

    2004 doi

  120. [141]

    Pietrinferni A., Salaris M., Cassisi S., Savino A., Mucciarelli A., Hyder D., Hidalgo S., 2024, @doi [ ] 10.1093/mnras/stad3267 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.2065P 527, 2065

    2024 doi

  121. [142]

    Planck Collaboration et al., 2014, @doi [ ] 10.1051/0004-6361/201321529 , https://ui.adsabs.harvard.edu/abs/2014A&A...571A...1P 571, A1

    2014 doi

  122. [143]

    Pozzetti L., et al., 2007, @doi [ ] 10.1051/0004-6361:20077609 , https://ui.adsabs.harvard.edu/abs/2007A&A...474..443P 474, 443

    2007 doi

  123. [144]

    Pozzetti L., et al., 2010, @doi [ ] 10.1051/0004-6361/200913020 , https://ui.adsabs.harvard.edu/abs/2010A&A...523A..13P 523, A13

    2010 doi

  124. [145]

    Revalski M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad382c , https://ui.adsabs.harvard.edu/abs/2024ApJ...966..228R 966, 228

    2024 doi

  125. [146]

    Robotham A. S. G., Driver S. P., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18327.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.2570R 413, 2570

    2011

  126. [147]

    Robotham A. S. G., Bellstedt S., Lagos C. d. P., Thorne J. E., Davies L. J., Driver S. P., Bravo M., 2020, @doi [ ] 10.1093/mnras/staa1116 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.495..905R 495, 905

    2020 doi

  127. [148]

    Roman-Duval J., et al., 2025, @doi [ ] 10.3847/1538-4357/adc45b , https://ui.adsabs.harvard.edu/abs/2025ApJ...985..109R 985, 109

    2025 doi

  128. [149]

    Rowan-Robinson M., et al., 2016, @doi [ ] 10.1093/mnras/stw1169 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461.1100R 461, 1100

    2016 doi

  129. [150]

    Salaris M., Cassisi S., Pietrinferni A., Hidalgo S., 2022, @doi [ ] 10.1093/mnras/stab3359 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.5197S 509, 5197

    2022 doi

  130. [151]

    C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

    Salim S., Boquien M., Lee J. C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

    2018 doi

  131. [152]

    E., 1955, @doi [ ] 10.1086/145971 , https://ui.adsabs.harvard.edu/abs/1955ApJ...121..161S 121, 161

    Salpeter E. E., 1955, @doi [ ] 10.1086/145971 , https://ui.adsabs.harvard.edu/abs/1955ApJ...121..161S 121, 161

    1955 doi

  132. [153]

    Sana H., et al., 2012, @doi [Science] 10.1126/science.1223344 , https://ui.adsabs.harvard.edu/abs/2012Sci...337..444S 337, 444

    2012 doi

  133. [154]

    R., 2015, @doi [ ] 10.1051/0004-6361/201425356 , https://ui.adsabs.harvard.edu/abs/2015A&A...577A..13S 577, A13

    Sander A., Shenar T., Hainich R., G \' menez-Garc \' a A., Todt H., Hamann W. R., 2015, @doi [ ] 10.1051/0004-6361/201425356 , https://ui.adsabs.harvard.edu/abs/2015A&A...577A..13S 577, A13

    2015 doi

  134. [155]

    Santini P., et al., 2015, @doi [ ] 10.1088/0004-637X/801/2/97 , https://ui.adsabs.harvard.edu/abs/2015ApJ...801...97S 801, 97

    2015 doi

  135. [156]

    J., Lin H., Yee H

    Sawicki M. J., Lin H., Yee H. K. C., 1997, @doi [ ] 10.1086/118231 , https://ui.adsabs.harvard.edu/abs/1997AJ....113....1S 113, 1

    1997 doi

  136. [157]

    M., 1986, , https://ui.adsabs.harvard.edu/abs/1986FCPh...11....1S 11, 1

    Scalo J. M., 1986, , https://ui.adsabs.harvard.edu/abs/1986FCPh...11....1S 11, 1

    1986

  137. [158]

    Scalo J., V \'a zquez-Semadeni E., Chappell D., Passot T., 1998, @doi [ ] 10.1086/306099 , https://ui.adsabs.harvard.edu/abs/1998ApJ...504..835S 504, 835

    1998 doi

  138. [159]

    Schaller G., Schaerer D., Meynet G., Maeder A., 1992, , https://ui.adsabs.harvard.edu/abs/1992A&AS...96..269S 96, 269

    1992

  139. [160]

    Schaye J., et al., 2015, @doi [ ] 10.1093/mnras/stu2058 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.446..521S 446, 521

    2015 doi

  140. [161]

    Schiminovich D., et al., 2005, @doi [ ] 10.1086/427077 , https://ui.adsabs.harvard.edu/abs/2005ApJ...619L..47S 619, L47

    2005 doi

  141. [162]

    J., 2020, @doi [ ] 10.1146/annurev-astro-032620-020217 , https://ui.adsabs.harvard.edu/abs/2020ARA&A..58..577S 58, 577

    Smith R. J., 2020, @doi [ ] 10.1146/annurev-astro-032620-020217 , https://ui.adsabs.harvard.edu/abs/2020ARA&A..58..577S 58, 577

    2020 doi

  142. [163]

    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

    2002

  143. [164]

    N., Geach J

    Sobral D., Smail I., Best P. N., Geach J. E., Matsuda Y., Stott J. P., Cirasuolo M., Kurk J., 2013, @doi [ ] 10.1093/mnras/sts096 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.428.1128S 428, 1128

    2013 doi

  144. [165]

    arXiv:1503.03757

    Spergel D., et al., 2015, @doi [preprint] 10.48550/arXiv.1503.03757 , https://ui.adsabs.harvard.edu/abs/2015arXiv150303757S p. arXiv:1503.03757

    2015 doi arXiv

  145. [166]

    Springel V., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09655.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.364.1105S 364, 1105

    2005

  146. [167]

    Springel V., White S. D. M., Tormen G., Kauffmann G., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04912.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.328..726S 328, 726

    2001

  147. [168]

    Springel V., et al., 2005, @doi [ ] 10.1038/nature03597 , https://ui.adsabs.harvard.edu/abs/2005Natur.435..629S 435, 629

    2005 doi

  148. [169]

    Springel V., et al., 2018, @doi [ ] 10.1093/mnras/stx3304 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475..676S 475, 676

    2018 doi

  149. [170]

    R., Eldridge J

    Stanway E. R., Eldridge J. J., 2018, @doi [ ] 10.1093/mnras/sty1353 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479...75S 479, 75

    2018 doi

  150. [171]

    R., Eldridge J

    Stanway E. R., Eldridge J. J., 2023, @doi [ ] 10.1093/mnras/stad1185 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.522.4430S 522, 4430

    2023 doi

  151. [172]

    R., Chrimes A

    Stanway E. R., Chrimes A. A., Eldridge J. J., Stevance H. F., 2020a, @doi [ ] 10.1093/mnras/staa1166 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.495.4605S 495, 4605

    doi

  152. [173]

    R., Eldridge J

    Stanway E. R., Eldridge J. J., Chrimes A. A., 2020b, @doi [ ] 10.1093/mnras/staa2089 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.2201S 497, 2201

    doi

  153. [174]

    Straatman C. M. S., et al., 2016, @doi [ ] 10.3847/0004-637X/830/1/51 , https://ui.adsabs.harvard.edu/abs/2016ApJ...830...51S 830, 51

    2016 doi

  154. [175]

    Strateva I., et al., 2001, @doi [ ] 10.1086/323301 , https://ui.adsabs.harvard.edu/abs/2001AJ....122.1861S 122, 1861

    2001 doi

  155. [176]

    A., et al., 2022, @doi [ ] 10.3847/1538-4357/ac82b0 , https://ui.adsabs.harvard.edu/abs/2022ApJ...935..146S 935, 146

    Suess K. A., et al., 2022, @doi [ ] 10.3847/1538-4357/ac82b0 , https://ui.adsabs.harvard.edu/abs/2022ApJ...935..146S 935, 146

    2022 doi

  156. [177]

    Sutherland W., et al., 2015, @doi [ ] 10.1051/0004-6361/201424973 , https://ui.adsabs.harvard.edu/abs/2015A&A...575A..25S 575, A25

    2015 doi

  157. [178]

    S., Krumholz M

    Tanvir T. S., Krumholz M. R., 2024, @doi [ ] 10.1093/mnras/stad3581 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.7306T 527, 7306

    2024 doi

  158. [179]

    N., Franx M., Brinchmann J., van der Wel A., van Dokkum P

    Taylor E. N., Franx M., Brinchmann J., van der Wel A., van Dokkum P. G., 2010, @doi [ ] 10.1088/0004-637X/722/1/1 , https://ui.adsabs.harvard.edu/abs/2010ApJ...722....1T 722, 1

    2010 doi

  159. [180]

    Thatte N., et al., 2021, @doi [The Messenger] 10.18727/0722-6691/5215 , https://ui.adsabs.harvard.edu/abs/2021Msngr.182....7T 182, 7

    2021 doi

  160. [181]

    arXiv:1706.09899

    The EAGLE team 2017, @doi [preprint] 10.48550/arXiv.1706.09899 , https://ui.adsabs.harvard.edu/abs/2017arXiv170609899T p. arXiv:1706.09899

    2017 doi arXiv

  161. [182]

    Thies I., Kroupa P., 2007, @doi [ ] 10.1086/522512 , https://ui.adsabs.harvard.edu/abs/2007ApJ...671..767T 671, 767

    2007 doi

  162. [183]

    E., et al., 2022, @doi [ ] 10.1093/mnras/stab3208 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4940T 509, 4940

    Thorne J. E., et al., 2022, @doi [ ] 10.1093/mnras/stab3208 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4940T 509, 4940

    2022 doi

  163. [184]

    M., 1968, @doi [ ] 10.1086/149455 , https://ui.adsabs.harvard.edu/abs/1968ApJ...151..547T 151, 547

    Tinsley B. M., 1968, @doi [ ] 10.1086/149455 , https://ui.adsabs.harvard.edu/abs/1968ApJ...151..547T 151, 547

    1968 doi

  164. [185]

    F., Panter B., Jimenez R., 2009, @doi [ ] 10.1088/0067-0049/185/1/1 , https://ui.adsabs.harvard.edu/abs/2009ApJS..185....1T 185, 1

    Tojeiro R., Wilkins S., Heavens A. F., Panter B., Jimenez R., 2009, @doi [ ] 10.1088/0067-0049/185/1/1 , https://ui.adsabs.harvard.edu/abs/2009ApJS..185....1T 185, 1

    2009 doi

  165. [186]

    W., et al., 2015, @doi [ ] 10.1093/mnras/stv1461 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452.2879T 452, 2879

    Trayford J. W., et al., 2015, @doi [ ] 10.1093/mnras/stv1461 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452.2879T 452, 2879

    2015 doi

  166. [187]

    A., et al., 2004, @doi [ ] 10.1086/423264 , https://ui.adsabs.harvard.edu/abs/2004ApJ...613..898T 613, 898

    Tremonti C. A., et al., 2004, @doi [ ] 10.1086/423264 , https://ui.adsabs.harvard.edu/abs/2004ApJ...613..898T 613, 898

    2004 doi

  167. [188]

    Trinca A., Schneider R., Maiolino R., Valiante R., Graziani L., Volonteri M., 2023, @doi [ ] 10.1093/mnras/stac3768 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.4753T 519, 4753

    2023 doi

  168. [189]

    I., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.21936 , https://ui.adsabs.harvard.edu/abs/2025arXiv250321936V p

    Villase \ n or J. I., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.21936 , https://ui.adsabs.harvard.edu/abs/2025arXiv250321936V p. arXiv:2503.21936

    2025 doi arXiv

  169. [190]

    S., et al., 2023, @doi [ ] 10.1051/0004-6361/202245650 , https://ui.adsabs.harvard.edu/abs/2023A&A...675A.154V 675, A154

    Vink J. S., et al., 2023, @doi [ ] 10.1051/0004-6361/202245650 , https://ui.adsabs.harvard.edu/abs/2023A&A...675A.154V 675, A154

    2023 doi

  170. [191]

    Vogelsberger M., et al., 2014, @doi [ ] 10.1093/mnras/stu1536 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.1518V 444, 1518

    2014 doi

  171. [192]

    J., et al., 2008, @doi [ ] 10.1051/0004-6361:200810704 , https://ui.adsabs.harvard.edu/abs/2008A&A...491..713W 491, 713

    Walcher C. J., et al., 2008, @doi [ ] 10.1051/0004-6361:200810704 , https://ui.adsabs.harvard.edu/abs/2008A&A...491..713W 491, 713

    2008 doi

  172. [193]

    Walcher J., Groves B., Budav \'a ri T., Dale D., 2011, @doi [ ] 10.1007/s10509-010-0458-z , https://ui.adsabs.harvard.edu/abs/2011Ap&SS.331....1W 331, 1

    2011 doi

  173. [194]

    J., Cowley W., Trayford J

    Wang L., Pearson W. J., Cowley W., Trayford J. W., Béthermin M., Gruppioni C., Hurley P., Micha owski M. J., 2019, @doi [ ] 10.1051/0004-6361/201834093 , https://ui.adsabs.harvard.edu/abs/2019A&A...624A..98W 624, A98

    2019 doi

  174. [195]

    Wang Y., et al., 2022, @doi [ ] 10.3847/1538-4357/ac4973 , https://ui.adsabs.harvard.edu/abs/2022ApJ...928....1W 928, 1

    2022 doi

  175. [196]

    Wang B., et al., 2024, @doi [ ] 10.3847/1538-4357/ad187c , https://ui.adsabs.harvard.edu/abs/2024ApJ...963...74W 963, 74

    2024 doi

  176. [197]

    R., et al., 2022, @doi [ ] 10.3847/1538-4365/ac3078 , https://ui.adsabs.harvard.edu/abs/2022ApJS..258...11W 258, 11

    Weaver J. R., et al., 2022, @doi [ ] 10.3847/1538-4365/ac3078 , https://ui.adsabs.harvard.edu/abs/2022ApJS..258...11W 258, 11

    2022 doi

  177. [198]

    R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    Weaver J. R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    2023 doi

  178. [199]

    Westera P., Lejeune T., Buser R., Cuisinier F., Bruzual G., 2002, @doi [ ] 10.1051/0004-6361:20011493 , https://ui.adsabs.harvard.edu/abs/2002A&A...381..524W 381, 524

    2002 doi

  179. [200]

    M., Trentham N., Hopkins A

    Wilkins S. M., Trentham N., Hopkins A. M., 2008, @doi [ ] 10.1111/j.1365-2966.2008.12885.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.385..687W 385, 687

    2008

  180. [201]

    M., Lovell C

    Wilkins S. M., Lovell C. C., Stanway E. R., 2019, @doi [ ] 10.1093/mnras/stz2894 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.5359W 490, 5359

    2019 doi

  181. [202]

    arXiv:2310.18464

    Woodrum C., et al., 2023, @doi [preprint] 10.48550/arXiv.2310.18464 , https://ui.adsabs.harvard.edu/abs/2023arXiv231018464W p. arXiv:2310.18464

    2023 doi arXiv

  182. [203]

    Worthey G., 1994, @doi [ ] 10.1086/192096 , https://ui.adsabs.harvard.edu/abs/1994ApJS...95..107W 95, 107

    1994 doi

  183. [204]

    Wuyts S., et al., 2007, @doi [ ] 10.1086/509708 , https://ui.adsabs.harvard.edu/abs/2007ApJ...655...51W 655, 51

    2007 doi

  184. [205]

    R., Eldridge J

    Xiao L., Stanway E. R., Eldridge J. J., 2018, @doi [ ] 10.1093/mnras/sty646 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.477..904X 477, 904

    2018 doi

  185. [206]

    Yang G., et al., 2020, @doi [ ] 10.1093/mnras/stz3001 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491..740Y 491, 740

    2020 doi

  186. [207]

    Yang G., et al., 2022, @doi [ ] 10.3847/1538-4357/ac4971 , https://ui.adsabs.harvard.edu/abs/2022ApJ...927..192Y 927, 192

    2022 doi

  187. [208]

    M., Kauffmann G., Guo Q., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20595.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.422..215Y 422, 215

    Yates R. M., Kauffmann G., Guo Q., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20595.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.422..215Y 422, 215

    2012

  188. [209]

    G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

    York D. G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

    2000 doi

  189. [210]

    Y., 2016, @doi [ ] 10.3847/0004-637X/820/2/114 , https://ui.adsabs.harvard.edu/abs/2016ApJ...820..114Y 820, 114

    Yu H., Wang F. Y., 2016, @doi [ ] 10.3847/0004-637X/820/2/114 , https://ui.adsabs.harvard.edu/abs/2016ApJ...820..114Y 820, 114

    2016 doi

  190. [211]

    E., Pessev P

    Zaritsky D., Colucci J. E., Pessev P. M., Bernstein R. A., Chandar R., 2014, @doi [ ] 10.1088/0004-637X/796/2/71 , https://ui.adsabs.harvard.edu/abs/2014ApJ...796...71Z 796, 71

    2014 doi

  191. [212]

    H., Haghi H., Kroupa P., 2025, @doi [ ] 10.1093/mnras/staf091 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537.2782Z 537, 2782

    Zonoozi A. H., Haghi H., Kroupa P., 2025, @doi [ ] 10.1093/mnras/staf091 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537.2782Z 537, 2782

    2025 doi

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