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Explaining the Weak Evolution of the High-Redshift Mass-Metallicity Relation with Galaxy Burst Cycles

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

Pith's one-line read A simplified burst-cycle model explains the nearly constant mass-metallicity relation at z = 5–12 by a cancellation between inflow metallicity and metal production efficiency.

desk verdict A parameter-free burst-cycle decomposition that convincingly explains the flat high-redshift MZR in FIRE-2 via cancellation between inflow metallicity and metal production efficiency; the reset assumption is softer than the paper admits but not fatal. read the letter →

arxiv 2505.22712 v2 pith:GF6VBTKT submitted 2025-05-28 astro-ph.GA

classification astro-ph.GA
keywords mass-metallicityrelationburstystarformationgalacticoutflowswindrecyclingFIRE-2simulationsgas-phasemetallicityfundamentalhigh-redshiftgalaxies
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

This paper asks why galaxies at z = 5–12 show a mass-metallicity relation that barely changes with cosmic time, and answers with a burst-cycle mechanism rather than gas fractions. Using the FIRE-2 simulations, the authors argue that strong stellar feedback following bursty star formation evacuates and resets each galaxy's interstellar medium, splitting its history into discrete burst cycles. Within a cycle, gas-phase metallicity is set by two quantities only: the average metallicity of inflowing gas and the metal mass returned by stars per unit inflowing gas mass. They show that, at fixed stellar mass, the first rises with decreasing redshift while the second falls, and the two trends cancel almost exactly, holding the MZR flat from z = 12 to z = 5. The paper also finds a secondary anti-correlation between metallicity and H-alpha-derived star formation rate that weakens under rest-UV selection.

What carries the argument

The load-bearing machinery is the burst-cycle decomposition of a galaxy's history, in which intense feedback evacuates the ISM on a 10–30 Myr timescale within 70–200 Myr cycles, followed by the Reduced Burst Model identity $Z_{\rm gas} \approx Z_{\rm in}^{\rm avg} + \varepsilon_Z$. The identity is obtained from the full gas-regulator expression by starting integration just after an outflow-driven reset, making initial gas and metal masses negligible, and dropping outflow and astration terms that are small during most of a cycle. It isolates the two quantities whose opposite redshift trends produce the constant MZR, and the measured scaling of its numerator and denominator terms ($\propto M_\star^{1.12}$ versus $\propto M_\star^{0.75}$) yields the MZR slope.

What would settle it

Compute, for each burst cycle in a FIRE-2-like simulation, the ratio of gas mass present at cycle start to the integrated inflow over that cycle; if the median ratio is not small (say $\lesssim 0.1$) across the z = 5–12 sample, the ISM-reset premise fails and the cancellation explanation cannot be the driver. Observationally, a mass-complete JWST sample showing more than about 0.1 dex of MZR normalization evolution from z = 12 to z = 5 would also contradict the prediction.

Watch

Extended reading notes

Core claim

The paper's central claim is that the nearly flat high-redshift MZR in FIRE-2 is produced by a cancellation inside the Reduced Burst Model: within a burst cycle, $Z_{\rm gas} \approx Z_{\rm in}^{\rm avg} + \varepsilon_Z$, where $Z_{\rm in}^{\rm avg}$ is the cycle-averaged metallicity of inflowing gas and $\varepsilon_Z$ is the metal mass returned by stars per unit inflowing gas mass. At fixed stellar mass, as redshift falls from 12 to 5, $Z_{\rm in}^{\rm avg}$ rises because more previously ejected, enriched gas is recycled back into the galaxy, while $\varepsilon_Z$ falls because less star formation occurs per unit inflow; the two trends nearly cancel, so the summed metallicity stays constant. The same model reproduces the MZR slope through the power-law scalings of the metal-inflow and metal-return integrals with stellar mass. The paper additionally claims that gas-phase metallicity at fixed stellar mass anticorrelates with H$\alpha$-derived star formation rate, an FMR-like signal that is weakened under rest-UV selection and absent for UV-continuum SFR.

Load-bearing premise

The entire cancellation explanation rests on the assumption that feedback-driven outflows empty the galaxy's ISM at the start of each burst cycle, so that gas and metals retained from earlier cycles are negligible; the authors themselves note this assumption begins to fail for the most massive galaxies and at lower redshift.

Editorial extensions

If this is right

  • The weak evolution of the high-redshift MZR is driven by baryon-cycle processes, not by saturated or weakly evolving gas fractions, so closed-box and leaky-box explanations are incomplete.
  • As redshift decreases, wind recycling enriches the gas flowing into galaxies while the star formation efficiency per inflow declines; these two trends are measurable and continue down to z = 5.
  • The slope of the MZR follows from the model's scaling relations: integrated metal inflow and metal return scale roughly as $M_\star^{1.12}$ while integrated gas inflow scales as $M_\star^{0.75}$, giving the measured slope of about 0.37.
  • The simulations predict an FMR-like inverse relation between gas-phase metallicity and H-alpha-derived star formation rate at fixed stellar mass, but the signal weakens when only rest-UV-selected galaxies are considered, which has direct consequences for JWST samples.
  • The Reduced Burst Model applies to any galaxy population whose histories separate into burst cycles, even if that population's MZR evolves; the framework can therefore be transported to other simulations and regimes.

Reading between the lines

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

  • Editorial inference: if the cancellation is generic, the constancy of the high-redshift MZR is not an equilibrium but a transient balance; simulations with weaker feedback and more retained gas between bursts should show growing MZR normalization by z = 5.
  • Editorial inference: the burst-cycle picture predicts that abundance-ratio diagnostics such as alpha-to-iron ratios should vary with phase within a cycle (inflow, starburst, outflow), so phase-resolved JWST spectra could test the model directly.
  • Editorial inference: the SFR-indicator dependence of the FMR-like signal implies that apparent evolution of the FMR at high redshift may be partly a selection effect and partly a timescale effect, and surveys using H-alpha versus UV-continuum SFR estimators may find systematically different metallicity offsets.
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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. This paper analyzes a high-redshift (z = 5–12) suite of FIRE-2 cosmological zoom-in simulations to explain the weak evolution of the gas-phase mass–metallicity relation (MZR). The authors divide galaxy histories into 'burst cycles' bounded by feedback-driven outflows that reset the interstellar medium, and from the full gas-regulator model they derive a 'Reduced Burst Model' in which the gas-phase metallicity is approximately Z_in^avg + ε_Z, the sum of the time-averaged inflow metallicity and the stellar metal production efficiency per unit inflow (Eq. 6). They show that this reduced model reproduces the simulated MZR and the full gas-regulator predictions, and that the weak redshift evolution arises from a cancellation: as redshift decreases, Z_in^avg increases while ε_Z decreases. They additionally study a secondary dependence of metallicity on Hα-derived star formation rate, find an FMR-like signal in the mass-complete sample, and show that this signal is weakened when only rest-UV-selected (JWST-like) galaxies are considered.

Significance. If the central claim holds, the paper provides a concrete, physically motivated alternative to gas-fraction-based explanations of the high-redshift MZR, and it identifies inflow metallicity and star-formation efficiency as the key baryon-cycle drivers. The analysis is grounded in explicit particle and galaxy tracking, and the reduced model is checked against both the full gas-regulator expression and direct simulation measurements, with no free parameters tuned to match the MZR. The FMR selection-effect result is also timely for interpreting JWST metallicity samples. However, the derivation of Eq. (6) leans on the burst-reset assumption, and the paper does not directly quantify the residual ISM at cycle starts; the authors themselves note that the model is expected to break down at high stellar mass and at lower redshift. Those gaps make the scope of the central claim larger than the current evidence directly supports.

major comments (3)
  1. [Sections 3 and 4.1] The reduction from Eq. (2) to Eq. (6) assumes that M_gas,i and M_Z,i are negligible at the start of each burst cycle, but the burst-cycle definition in Section 4.1 allows a new cycle to begin at a local gas-mass minimum that is as high as 50% of the previous cycle's peak gas mass. Consequently, the residual ISM can be comparable to the integrated inflow terms for a substantial fraction of cycles, especially at high stellar mass. Because the full gas-regulator model (Eq. 2) and the reduced model (Eq. 6) are evaluated over the same cycle boundaries, agreement in Fig. 4 does not by itself establish that the initial terms are negligible. Please report the binned distributions of M_gas,i / ∫ M_in dt and M_Z,i / ∫ (M_Z,in + M_Z,R) dt as functions of stellar mass and redshift, and show directly that the reduced-model predictions and the Z_in^avg–ε_Z cancellation in Fig. 5 are robust when cycles with large residual ISM are removed.
  2. [Section 5.3 and Fig. 5] The paper presents the cancellation as holding the MZR approximately constant for z = 5–12 over the full stellar mass range, yet Section 5.3 states that deviations at M_star ≳ 10^9 M_sun may be due to gas retained between burst cycles, which is precisely the regime where the reset assumption underlying Eq. (6) is expected to fail. Please quantify the offsets between the reduced-model predictions and the FIRE-2 MZR in each mass bin (e.g., median offset and scatter in the highest-mass bin) and explicitly test whether the weak-evolution and cancellation conclusions hold when the analysis is restricted to M_star ≲ 10^9 M_sun. If the conclusions do not extend to the high-mass end, the scope of the central claim should be revised.
  3. [Section 5.2 and Appendix A] The interpretation that the decrease in ε_Z is driven by the decrease in the star formation efficiency SFE = ∫ SFR dt / ∫ M_in dt is not directly demonstrated, because ε_Z is defined using the total stellar metal return rate M_Z,R, which includes returns from stellar populations formed in earlier burst cycles as well as from the current cycle. Please show that returns from stars formed within the current cycle dominate M_Z,R (or separate the two contributions) and verify that the ε_Z–SFE relation holds when only current-cycle returns are used. Without this check, the physical explanation for the ε_Z evolution remains suggestive rather than established.
minor comments (4)
  1. [Section 1] The phrase 'cosmic baron cycle' should read 'cosmic baryon cycle'.
  2. [Figure 4 caption] In the right panel of Fig. 4, the expression 'Zavg_in + Z' should read 'Zavg_in + ε_Z' for consistency with Eq. (6).
  3. [Section 5.3] There is a duplicated word: 'the near-perfect cancellation between between Z_avg_in and ε_Z' should have only one 'between'.
  4. [Figure 5 caption] The middle and right panels label the metal production efficiency as 'Z' rather than 'ε_Z'; please correct the notation to match the text.

Circularity Check

1 steps flagged · score 2.0 of 10

Minor tautology in the reduced-model 'prediction', but no fitted parameter or self-citation chain forces the central cancellation claim.

  1. other [Section 3, Eq. (6); validation in Section 4.2 and Fig. 4.]
    "Zgas ≈ Z avg in + εZ. (6) ... Figure 4 shows that metallicities calculated from the full 'Gas-Regulator Model' (equation 2) are in general agreement with values measured directly from the simulations by Marszewski et al. (2024), matching the prediction of weak evolution in the MZR for z ≳ 5."

    The reduced-model output is a rearrangement of the same conservation accounting used to define Z_gas, evaluated with inflow and stellar-return integrals measured from the same FIRE-2 particle histories. Agreement with the simulated MZR therefore checks the bookkeeping and the burst-reset approximations rather than providing an out-of-sample prediction. The central claim that Z_in^avg and ε_Z evolve in opposite directions and cancel is an empirical decomposition of the simulation data, not a result forced by a fitted parameter, so the circularity is mild.

full rationale

The paper derives Eq. (6) from the exact conservation identity Eq. (2) by explicitly stating and later testing approximations (negligible initial ISM, short evacuation times, outflow metals near ISM metallicity). No parameter is fitted to the MZR; the quantities Z_in^avg and ε_Z are measured independently from inflow and stellar-return histories. The agreement between the reduced model and the FIRE-2 MZR is a consistency check of these approximations, which is a legitimate use of simulation bookkeeping. The cancellation between Z_in^avg and ε_Z is an empirical finding, and the paper also provides physically motivated explanations (wind recycling and declining star formation efficiency). Self-citations to Marszewski et al. (2024) supply the reference MZR but are not used to forbid alternatives or to import an unverified uniqueness theorem. The paper itself flags the key assumption's limitations in Section 5.3, noting that high-mass galaxies may retain gas between burst cycles and that the model is expected to break down at lower redshift. Those are robustness concerns, not circularity. Overall, the central derivation is self-contained and the circularity burden is low.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The model itself has no fitting parameters, and the two components (Z_in^avg and epsilon_Z) are directly measured from the simulations. The main epistemic weight rests on the FIRE-2 subgrid model and on the burst-reset approximation; these are tested only internally against the full gas-regulator expression, not against independent external data.

free parameters (2)
  • M_min_gas = 7000 M_sun
    Minimum gas mass defining the start/end of burst cycles, chosen as the coarsest baryonic mass resolution in the suite; tests show insensitivity over 0-1e5 M_sun (Section 4.1).
  • Cycle-end gas mass threshold = 50% of peak gas mass
    Used to define the end of a burst cycle at a local gas mass minimum; a hand-chosen threshold that sets the cycle boundaries and thus the integration limits for all model quantities.
assumptions (5)
  • domain assumption FIRE-2 simulation subgrid physics (star formation, stellar feedback, metal yields, turbulent diffusion) accurately represents high-redshift galaxy formation.
    The entire analysis is based on FIRE-2 zoom-in simulations; if the subgrid model is inaccurate, the burst cycles and decomposition may not apply to real galaxies (Section 2.1).
  • ad hoc to paper Stars form with a metallicity equal to the current gas-phase metallicity, so the astration terms cancel in Equation (2).
    Invoked in Section 3 to cancel integral(Mdot_Z,SFR) against Z_gas times integral(SFR); the text states this is measured to be small, but the cancellation itself is an assumed condition.
  • ad hoc to paper The ISM is effectively reset at the start of each burst cycle, making M_gas,i and M_Z,i negligible.
    Used to go from Equation (2) to (3); tested indirectly by agreement with the full model, but not directly measured.
  • ad hoc to paper Outflow terms are negligible because the evacuation timescale (10-30 Myr) is much shorter than the burst cycle (70-200 Myr) and outflow metallicity equals gas metallicity.
    Used to drop outflow terms in Equation (4); supported by Appendix C, but the timescale ratio is only about 6, so outflows act for a non-negligible fraction of the cycle.
  • domain assumption BPASS v2.2 spectral synthesis models with nebular emission correctly predict H-alpha and UV continuum luminosities from simulated stellar populations.
    Used in Section 5.5 to derive SFR_Halpha and SFR_UV; errors in these models would affect the FMR analysis.

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Cite this review

Pith. "Pith review of Explaining the Weak Evolution of the High-Redshift Mass-Metallicity Relation with Galaxy Burst Cycles." pith.science (2026). https://pith.science/paper/GF6VBTKT

@misc{pith2026250522712,
  author       = {Pith},
  title        = {Pith review of: Explaining the Weak Evolution of the High-Redshift Mass-Metallicity Relation with Galaxy Burst Cycles},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GF6VBTKT}},
  note         = {Machine review of arXiv:2505.22712}
}
abstract

Recent observations suggest a nearly constant gas-phase mass-metallicity relation (MZR) at $z \gtrsim 5$, in agreement with many theoretical predictions. This lack of evolution contrasts with observations at $z \lesssim 3$, which find an increasing normalization of the MZR with decreasing redshift. We analyze a high-redshift suite of FIRE-2 cosmological zoom-in simulations to identify the physical drivers of the MZR. Previous studies have explained the weak evolution of the high-redshift MZR in terms of weakly evolving or saturated gas fractions, but we find this alone does not explain the evolution in FIRE-2. Instead, stellar feedback following intense bursts of star formation drives enriched gas out of galaxies, resetting their interstellar medium and separating their histories into distinct ``burst cycles". We develop the ``Reduced Burst Model", a simplified gas-regulator model that successfully reproduces the simulated MZR and identifies the dominant drivers of its evolution. As redshift decreases, the metallicity of inflows within burst cycles increases at fixed stellar mass due to increased wind recycling of enriched gas. Meanwhile, the metal mass produced by stars per inflowing gas mass within these cycles decreases because of decreased star formation per gas mass inflowing into the galaxy. The effects of these two processes on the median metallicity largely cancel, holding the MZR constant for $z = 5 - 12$. At fixed stellar mass, the simulations predict lower gas metallicities at higher $\rm H\alpha$-derived star formation rates, in qualitative agreement with the fundamental metallicity relation (FMR), but this effect is reduced in rest UV-selected samples.

Figures

Figures reproduced from arXiv: 2505.22712 by the authors.

Figure 1
Figure 1. The high-redshift gas-phase MZR in FIRE-2 for z = 5 − 12 from Marszewski et al. (2024) (black solid line) and in observations from z = 3 − 11. All observational data (fits, binned means, and individual galaxies) are colored by redshift. Observational best fits are shown at z ∼ 3.3 from Sanders et al. (2021) (solid line) and at z ∼ 7 from Chemerynska et al. (2024) (diagonal hatching representing uncertainty in the be… view at source ↗
Figure 2
Figure 2. Star formation rate (upper) and stellar/gas/metal mass (lower) time series for an example high-redshift FIRE-2 galaxy with a stellar mass of M⋆ = 1.8 × 108M⊙ at z = 5. The star formation rate (black) is characterized by strong bursts. The stellar mass (blue) grows over time via these bursts. Intense stellar feedback following the starbursts drives strong outflows, decimating the gas mass (orange) and gas-phase metal… view at source ↗
Figure 3
Figure 3. Channels by which galaxies can gain and lose metals and gas in the full “Gas-Regulator Model” (left; equation 2) and the “Reduced Burst Model” (right; equation 6). The full “Gas-Regulator Model” includes all possible channels (i.e., inflows, outflows, star formation, and stellar mass return). The “Reduced Burst Model” includes only the channels relevant for explaining the form and evolution of the MZR in the scenari… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: MZR of FIRE-2 galaxies predicted by the full “Gas-Regulator Model” (left; equation 2) and the “Reduced Burst Model” (right; equation 6) at z ∼ 5.5 (blue), 6.5 (orange), 8.0 (green), and 10.5 (red). Smaller, transparent points represent predicted metallicities of indivi…
Figure 5
Figure 5. Figure 5: Average inflow metallicity Z avg in (left), metal production efficiency εZ (middle), and their sum (right) as a function of stellar mass at z ∼ 5.5 (blue), 6.5 (orange), 8.0 (green), and 10.5 (red). Empty squares represent stellar-mass-binned median values. Smaller, tr…
Figure 6
Figure 6. Figure 6: Signal for an FMR-like relation with SFRHα (top) and SFRUV (bottom) as the secondary parameters for our complete sample of galaxies (left) and for an “observable” (L1560 > 2 × 1043 erg/s, representative of a JADES-Deep-like survey) sample of galaxies (right). Within ea…
Figure 7
Figure 7. Figure 7: Star formation efficiency (defined here as SFE = R SFR dt/ R M˙ in dt) as a function of stellar mass at z ∼ 5.5 (blue), 6.5 (orange), 8.0 (green), and 10.5 (red). Smaller, transparent points represent the measured quantities integrated over individual galaxy burst cycl…
Figure 8
Figure 8. Figure 8: The scaling relations of M˙ Z,in (left), M˙ Z,R (middle), and M˙ in (right) with stellar mass at z ∼ 5.5 (blue), 6.5 (orange), 8.0 (green), and 10.5 (red). Smaller, transparent points represent the measurements of individual galaxies at each snapshot within burst cycle…
Figure 9
Figure 9. Figure 9: The stellar-mass-binned median burst cycle (squares with solid lines) and evacuation (circles with dashed lines) time scales for galaxies in our sample at z ∼ 5.5 (blue), 6.5 (orange), 8.0 (green), and 10.5 (red). Both timescales are weakly dependent on stellar mass bu…

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Works this paper leans on

73 extracted references · 2 canonical work pages

  1. [1]

    1989, , 53, 197, 10.1016/0016-7037(89)90286-X

    Anders , E., & Grevesse , N. 1989, , 53, 197, 10.1016/0016-7037(89)90286-X

  2. [2]

    2017, , 470, 4698, 10.1093/mnras/stx1517

    Angl \'e s-Alc \'a zar , D., Faucher-Gigu \`e re , C.-A., Kere s , D., et al. 2017, , 470, 4698, 10.1093/mnras/stx1517

  3. [3]

    2024, , 532, L14, 10.1093/mnrasl/slae036

    Bassini , L., Feldmann , R., Gensior , J., et al. 2024, , 532, L14, 10.1093/mnrasl/slae036

  4. [4]

    S., Maiolino , R., Kennicutt , R., et al

    Bothwell , M. S., Maiolino , R., Kennicutt , R., et al. 2013, , 433, 1425, 10.1093/mnras/stt817

  5. [5]

    J., Curtis-Lake , E., et al

    Boyett , K., Bunker , A. J., Curtis-Lake , E., et al. 2024, , 535, 1796, 10.1093/mnras/stae2430

  6. [6]

    J., Saxena , A., Cameron , A

    Bunker , A. J., Saxena , A., Cameron , A. J., et al. 2023, arXiv e-prints, arXiv:2302.07256, 10.48550/arXiv.2302.07256

  7. [7]

    2024, , 976, L15, 10.3847/2041-8213/ad8dc9

    Chemerynska , I., Atek , H., Dayal , P., et al. 2024, , 976, L15, 10.3847/2041-8213/ad8dc9

  8. [8]

    J., Ma , X., Hopkins , P

    Colbrook , M. J., Ma , X., Hopkins , P. F., & Squire , J. 2017, , 467, 2421, 10.1093/mnras/stx261

Show all 73 references
  1. [9]

    2023, , 518, 425, 10.1093/mnras/stac2737

    Curti , M., D'Eugenio , F., Carniani , S., et al. 2023, , 518, 425, 10.1093/mnras/stac2737

  2. [10]

    2024, , 684, A75, 10.1051/0004-6361/202346698

    Curti , M., Maiolino , R., Curtis-Lake , E., et al. 2024, , 684, A75, 10.1051/0004-6361/202346698

  3. [11]

    Dayal , P., Ferrara , A., & Dunlop , J. S. 2013, , 430, 2891, 10.1093/mnras/stt083

  4. [12]

    L., Patton , D

    Ellison , S. L., Patton , D. R., Simard , L., & McConnachie , A. W. 2008, , 672, L107, 10.1086/527296

  5. [13]

    K., Shapley , A

    Erb , D. K., Shapley , A. E., Pettini , M., et al. 2006, , 644, 813, 10.1086/503623

  6. [14]

    N., et al

    Escala , I., Wetzel , A., Kirby , E. N., et al. 2018, , 474, 2194, 10.1093/mnras/stx2858

  7. [15]

    2018, , 473, 3717, 10.1093/mnras/stx2595

    Faucher-Gigu \`e re , C.-A. 2018, , 473, 3717, 10.1093/mnras/stx2595

  8. [16]

    2009, , 703, 1416, 10.1088/0004-637X/703/2/1416

    Faucher-Gigu \`e re , C.-A., Lidz , A., Zaldarriaga , M., & Hernquist , L. 2009, , 703, 1416, 10.1088/0004-637X/703/2/1416

  9. [17]

    2015, , 449, 3274, 10.1093/mnras/stv552

    Feldmann , R. 2015, , 449, 3274, 10.1093/mnras/stv552

  10. [18]

    2023, , 522, 3831, 10.1093/mnras/stad1205

    Feldmann , R., Quataert , E., Faucher-Gigu \`e re , C.-A., et al. 2023, , 522, 3831, 10.1093/mnras/stad1205

  11. [19]

    S., et al

    Feldmann , R., Boylan-Kolchin , M., Bullock , J. S., et al. 2025, , 536, 988, 10.1093/mnras/stae2633

  12. [20]

    2008, , 385, 2181, 10.1111/j.1365-2966.2008.12991.x

    Finlator , K., & Dav \'e , R. 2008, , 385, 2181, 10.1111/j.1365-2966.2008.12991.x

  13. [21]

    A., Gurvich , A

    Flores Vel \'a zquez , J. A., Gurvich , A. B., Faucher-Gigu \`e re , C.-A., et al. 2021, , 501, 4812, 10.1093/mnras/staa3893

  14. [22]

    M., Torrey , P., Ellison , S., et al

    Garcia , A. M., Torrey , P., Ellison , S., et al. 2024, , 531, 1398, 10.1093/mnras/stae1252

  15. [23]

    M., Torrey , P., Ellison , S

    Garcia , A. M., Torrey , P., Ellison , S. L., et al. 2025, , 536, 119, 10.1093/mnras/stae2587

  16. [24]

    C., Lu , Y., et al

    Guo , Y., Koo , D. C., Lu , Y., et al. 2016, , 822, 103, 10.3847/0004-637X/822/2/103

  17. [25]

    L., Finlator , K., & Dressler , A

    Henry , A., Martin , C. L., Finlator , K., & Dressler , A. 2013 a , , 769, 148, 10.1088/0004-637X/769/2/148

  18. [26]

    2013 b , , 776, L27, 10.1088/2041-8205/776/2/L27

    Henry , A., Scarlata , C., Dom \' nguez , A., et al. 2013 b , , 776, L27, 10.1088/2041-8205/776/2/L27

  19. [27]

    Hopkins , P. F. 2015, , 450, 53, 10.1093/mnras/stv195

  20. [28]

    F., Kere s , D., O \ n orbe , J., et al

    Hopkins , P. F., Kere s , D., O \ n orbe , J., et al. 2014, , 445, 581, 10.1093/mnras/stu1738

  21. [29]

    F., Wetzel , A., Kere s , D., et al

    Hopkins , P. F., Wetzel , A., Kere s , D., et al. 2018, , 480, 800, 10.1093/mnras/sty1690

  22. [30]

    F., Wetzel , A., Wheeler , C., et al

    Hopkins , P. F., Wetzel , A., Wheeler , C., et al. 2023, , 519, 3154, 10.1093/mnras/stac3489

  23. [31]

    Y.-Y., \'A lvarez-M \'a rquez , J., Coe , D., et al

    Hsiao , T. Y.-Y., \'A lvarez-M \'a rquez , J., Coe , D., et al. 2024, arXiv e-prints, arXiv:2404.16200. 2404.16200

  24. [32]

    C., & Evans , N

    Kennicutt , R. C., & Evans , N. J. 2012, , 50, 531, 10.1146/annurev-astro-081811-125610

  25. [33]

    A., Strom , A

    Korhonen Cuestas , N. A., Strom , A. L., Miller , T. B., et al. 2025, , 984, 188, 10.3847/1538-4357/adc5f7

  26. [34]

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

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

  27. [35]

    2020, , 494, 1988, 10.1093/mnras/staa880

    Langan , I., Ceverino , D., & Finlator , K. 2020, , 494, 1988, 10.1093/mnras/staa880

  28. [36]

    2023, arXiv e-prints, arXiv:2307.06336, 10.48550/arXiv.2307.06336

    Langeroodi , D., & Hjorth , J. 2023, arXiv e-prints, arXiv:2307.06336, 10.48550/arXiv.2307.06336

  29. [37]

    D., Cannon , J

    Lee , H., Skillman , E. D., Cannon , J. M., et al. 2006, , 647, 970, 10.1086/505573

  30. [38]

    D., et al

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

  31. [39]

    F., Serrano , A., & Torres-Peimbert , S

    Lequeux , J., Peimbert , M., Rayo , J. F., Serrano , A., & Torres-Peimbert , S. 1979, , 80, 155

  32. [40]

    J., Carollo , C

    Lilly , S. J., Carollo , C. M., Pipino , A., Renzini , A., & Peng , Y. 2013, , 772, 119, 10.1088/0004-637X/772/2/119

  33. [41]

    J., D'Eugenio , F., Maiolino , R., et al

    Looser , T. J., D'Eugenio , F., Maiolino , R., et al. 2024, , 629, 53, 10.1038/s41586-024-07227-0

  34. [42]

    F., Faucher-Gigu \`e re , C.-A., et al

    Ma , X., Hopkins , P. F., Faucher-Gigu \`e re , C.-A., et al. 2016, , 456, 2140, 10.1093/mnras/stv2659

  35. [43]

    F., Boylan-Kolchin , M., et al

    Ma , X., Hopkins , P. F., Boylan-Kolchin , M., et al. 2018 a , , 477, 219, 10.1093/mnras/sty684

  36. [44]

    F., Garrison-Kimmel , S., et al

    Ma , X., Hopkins , P. F., Garrison-Kimmel , S., et al. 2018 b , , 478, 1694, 10.1093/mnras/sty1024

  37. [45]

    C., Casey , C

    Ma , X., Hayward , C. C., Casey , C. M., et al. 2019, , 487, 1844, 10.1093/mnras/stz1324

  38. [46]

    J., Ziegler , B

    Maier , C., Lilly , S. J., Ziegler , B. L., et al. 2014, , 792, 3, 10.1088/0004-637X/792/1/3

  39. [47]

    2010, , 408, 2115, 10.1111/j.1365-2966.2010.17291.x

    Mannucci , F., Cresci , G., Maiolino , R., Marconi , A., & Gnerucci , A. 2010, , 408, 2115, 10.1111/j.1365-2966.2010.17291.x

  40. [48]

    C., & Feldmann , R

    Marszewski , A., Sun , G., Faucher-Gigu \`e re , C.-A., Hayward , C. C., & Feldmann , R. 2024, , 967, L41, 10.3847/2041-8213/ad4cee

  41. [49]

    2024, arXiv e-prints, arXiv:2402.14084, 10.48550/arXiv.2402.14084

    Morishita , T., Stiavelli , M., Grillo , C., et al. 2024, arXiv e-prints, arXiv:2402.14084, 10.48550/arXiv.2402.14084

  42. [50]

    L., Kere s , D., Faucher-Gigu \`e re , C.-A., et al

    Muratov , A. L., Kere s , D., Faucher-Gigu \`e re , C.-A., et al. 2017, , 468, 4170, 10.1093/mnras/stx667

  43. [51]

    2023, arXiv e-prints, arXiv:2301.12825, 10.48550/arXiv.2301.12825

    Nakajima , K., Ouchi , M., Isobe , Y., et al. 2023, arXiv e-prints, arXiv:2301.12825, 10.48550/arXiv.2301.12825

  44. [52]

    2022, , 513, 5621, 10.1093/mnras/stac1281

    Pallottini , A., Ferrara , A., Gallerani , S., et al. 2022, , 513, 5621, 10.1093/mnras/stac1281

  45. [53]

    B., Angl \'e s-Alc \'a zar , D., et al

    Pandya , V., Fielding , D. B., Angl \'e s-Alc \'a zar , D., et al. 2021, , 508, 2979, 10.1093/mnras/stab2714

  46. [54]

    S., & Shankar , F

    Peeples , M. S., & Shankar , F. 2011, , 417, 2962, 10.1111/j.1365-2966.2011.19456.x

  47. [55]

    2020, , 641, A6, 10.1051/0004-6361/201833910

    Planck Collaboration , Aghanim , N., Akrami , Y., et al. 2020, , 641, A6, 10.1051/0004-6361/201833910

  48. [56]

    E., Tacchella , S., Johnson , B

    Robertson , B. E., Tacchella , S., Johnson , B. D., et al. 2023, Nature Astronomy, 7, 611, 10.1038/s41550-023-01921-1

  49. [57]

    E., Stefanon , M., Bouwens , R., et al

    Rowland , L. E., Stefanon , M., Bouwens , R., et al. 2025, arXiv e-prints, arXiv:2501.10559, 10.48550/arXiv.2501.10559

  50. [58]

    L., Shapley , A

    Sanders , R. L., Shapley , A. E., Kriek , M., et al. 2015, , 799, 138, 10.1088/0004-637X/799/2/138

  51. [59]

    L., Shapley , A

    Sanders , R. L., Shapley , A. E., Jones , T., et al. 2021, , 914, 19, 10.3847/1538-4357/abf4c1

  52. [60]

    2024, arXiv e-prints, arXiv:2408.07974, 10.48550/arXiv.2408.07974

    Sarkar , A., Chakraborty , P., Vogelsberger , M., et al. 2024, arXiv e-prints, arXiv:2408.07974, 10.48550/arXiv.2408.07974

  53. [61]

    C., et al

    Scholte , D., Cullen , F., Carnall , A. C., et al. 2025, arXiv e-prints, arXiv:2502.10499, 10.48550/arXiv.2502.10499

  54. [62]

    R., & Eldridge , J

    Stanway , E. R., & Eldridge , J. J. 2018, , 479, 75, 10.1093/mnras/sty1353

  55. [63]

    C., Rudie , G

    Steidel , C. C., Rudie , G. C., Strom , A. L., et al. 2014, , 795, 165, 10.1088/0004-637X/795/2/165

  56. [64]

    C., & Shen , X

    Sun , G., Faucher-Gigu \`e re , C.-A., Hayward , C. C., & Shen , X. 2023 a , , 526, 2665, 10.1093/mnras/stad2902

  57. [65]

    C., et al

    Sun , G., Faucher-Gigu \`e re , C.-A., Hayward , C. C., et al. 2023 b , , 955, L35, 10.3847/2041-8213/acf85a

  58. [66]

    2019, , 484, 5587, 10.1093/mnras/stz243

    Torrey , P., Vogelsberger , M., Marinacci , F., et al. 2019, , 484, 5587, 10.1093/mnras/stz243

  59. [67]

    A., Heckman , T

    Tremonti , C. A., Heckman , T. M., Kauffmann , G., et al. 2004, , 613, 898, 10.1086/423264

  60. [68]

    2023, , 518, 3557, 10.1093/mnras/stac2654

    Ucci , G., Dayal , P., Hutter , A., et al. 2023, , 518, 3557, 10.1093/mnras/stac2654

  61. [69]

    M., Vijayan , A

    Wilkins , S. M., Vijayan , A. P., Lovell , C. C., et al. 2023, , 519, 3118, 10.1093/mnras/stac3280

  62. [70]

    2014, , 437, 3647, 10.1093/mnras/stt2185

    Yabe , K., Ohta , K., Iwamuro , F., et al. 2014, , 437, 3647, 10.1093/mnras/stt2185

  63. [71]

    J., Bresolin , F., Kewley , L

    Zahid , H. J., Bresolin , F., Kewley , L. J., Coil , A. L., & Dav \'e , R. 2012, , 750, 120, 10.1088/0004-637X/750/2/120

  64. [72]

    J., Geller , M

    Zahid , H. J., Geller , M. J., Kewley , L. J., et al. 2013, , 771, L19, 10.1088/2041-8205/771/2/L19

  65. [73]

    J., Kewley , L

    Zahid , H. J., Kewley , L. J., & Bresolin , F. 2011, , 730, 137, 10.1088/0004-637X/730/2/137

Pith tools

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