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Effect of gas accretion on $\alpha$-element bimodality in Milky Way-mass galaxies in the FIRE-2 simulations

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read Late infall of metal-poor gas from the circumgalactic medium creates the low-alpha stellar sequence in Milky Way-mass galaxies.

desk verdict Useful FIRE-2 census tying low-alpha sequences to late metal-poor gas accretion, but the classification thresholds and sample selection need scrutiny before the correlation is taken as established. read the letter →

arxiv 2501.12342 v1 pith:ULRYNNKM submitted 2025-01-21 astro-ph.GA

Hanna Parul , Jeremy Bailin , Sarah R. Loebman , Andrew Wetzel , Megan Barry , Binod Bhattarai This is my paper · ORCID
classification astro-ph.GA
keywords alpha-elementbimodalitylow-alphasequencegasaccretioncircumgalacticmediumFIRE-2simulations[Fe/H]-[Mg/Fe]planediskgalaxyevolutionMilkyWayanalogues
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 some disk galaxies show two distinct stellar populations on the iron-magnesium abundance plane—a high-alpha sequence of old, hot stars and a low-alpha sequence of younger, colder stars—whereas others show only one. Using 11 simulated Milky Way-mass galaxies, it finds that the low-alpha sequence appears in galaxies that have recently accreted large amounts of metal-poor gas from the circumgalactic medium; this gas lands in the outer disk, dilutes the interstellar medium, and grows the gas disk. Galaxies without such late accretion remain unimodal or only weakly bimodal. If correct, the bimodality seen in the Milky Way and some other disks is a direct signature of late-time gas accretion, not an inevitable outcome of disk formation.

What carries the argument

The load-bearing object is the $[\mathrm{Fe/H}]$–$[\mathrm{Mg/Fe}]$ abundance plane, with Mg used as the $\alpha$ element most purely produced by core-collapse supernovae in the simulation. The paper separates high- and low-$\alpha$ sequences by locating double peaks in $[\mathrm{Mg/Fe}]$ within narrow $[\mathrm{Fe/H}]$ bins. The causal analysis then rests on accretion diagnostics: gas particles with negative radial velocity inside a 10 kpc shell are tracked over the final ~8 Gyr, their mass-weighted metallicity distributions are compared across time, and the radius where gas surface density falls below 5 solar masses per square kiloparsec tracks disk growth. The mechanism that carries the argument is that metal-poor, relatively high-angular-momentum gas from the circumgalactic medium joins the galaxy in the outskirts, dilutes the star-forming interstellar medium, and fuels the young, extended low-$\alpha$ population.

What would settle it

Track the four strong-bimodal galaxies analyzed in the companion paper: if any shows a clear low-alpha sequence without a concurrent rise in metal-poor gas inflow and gas-disk growth over the last 5–6 Gyr, the claimed mechanism fails. Alternatively, find a simulated or observed Milky Way-mass galaxy whose low-alpha sequence formed while its accretion was declining and metal-rich.

Watch

Extended reading notes

Core claim

The paper argues that the presence of a low-$\alpha$ sequence on the $[\mathrm{Fe/H}]$–$[\mathrm{Mg/Fe}]$ plane is not a universal property of disk galaxies but a symptom of late-time metal-poor gas accretion. In five of eleven simulated Milky Way-mass galaxies, two distinct stellar sequences emerge: an old, kinematically hot, centrally concentrated high-$\alpha$ population and a younger, cooler low-$\alpha$ population that extends to the outer disk. Comparing gas inflow over the last 8 Gyr, the bimodal galaxies are the ones whose circumgalactic gas becomes increasingly metal-poor and abundant, settles at large radii, and grows the gas disk; unimodal galaxies show declining, more metal-rich inflow. The paper further shows that both smooth CGM accretion and gas-rich mergers can deliver this gas, producing somewhat different bimodal patterns: smooth accretion builds a metal-poor tail at large radii, while mergers dilute $[\mathrm{Fe/H}]$ across all radii and can rapidly shift stars to lower $[\mathrm{Mg/Fe}]$.

Load-bearing premise

The analysis assumes the 11 simulated galaxies are a representative sample of Milky Way-mass galaxies; four galaxies with stronger bimodality are deferred to a companion paper, and if those galaxies lack the late metal-poor inflow, the proposed causal link would not cover all bimodal cases.

Editorial extensions

If this is right

  • In the FIRE-2 sample, alpha-element bimodality is not universal: five galaxies are bimodal, three are unimodal, two are weakly bimodal, and one is strongly bimodal, so the Milky Way's two sequences are a common but not guaranteed outcome.
  • The low-alpha population in bimodal galaxies is younger, kinematically cooler, and more radially extended than the high-alpha population, matching the qualitative age and kinematic split seen in the Milky Way.
  • Bimodal galaxies show rising metal-poor gas inflow and gas-disk growth over the last 5–6 Gyr, whereas non-bimodal galaxies show declining inflow and little disk growth; the onset of low-alpha star formation lags the accretion by 1–2 Gyr.
  • Both smooth accretion from the circumgalactic medium and gas-rich mergers can supply the metal-poor gas, but they leave distinguishable patterns: smooth accretion creates an extended metal-poor tail in the outer disk, while mergers cause rapid dilution in $[\mathrm{Fe/H}]$ at all radii.
  • A galaxy can experience a metal-poor merger without becoming bimodal if the merger happens during the bursty star-formation phase, so the timing of accretion relative to star-formation mode matters.

Reading between the lines

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

  • If the causal link holds, a Milky Way-mass galaxy with a prominent low-alpha sequence should also show a current or recent extended, low-metallicity gas reservoir at large radii; this is testable with atomic-hydrogen and molecular-gas mapping of nearby disks.
  • The four strong-bimodal galaxies deferred to the companion paper are a natural falsification check: if they acquired their low-alpha sequences without a late metal-poor inflow, the proposed mechanism is not the only route to bimodality.
  • The FIRE-2 picture resembles the two-infall chemical-evolution scenario, but with the second infall realized as prolonged cosmological accretion rather than a single delayed episode, which may change how the Milky Way's age–$[\mathrm{Fe/H}]$ relation is interpreted.
  • One might predict that galaxies with long steady star-formation phases and extended gas disks are more likely to show bimodality, since those are the conditions under which late metal-poor gas can form a distinct young low-alpha population.
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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. The manuscript analyzes 11 Milky Way-mass galaxies from the FIRE-2 cosmological zoom-in simulations and classifies them by the presence of double sequences on the [Fe/H]-[Mg/Fe] plane. Five galaxies are classified as bimodal, two as weakly-bimodal, three as non-bimodal, and one (m12b) as strongly-bimodal and deferred to a companion paper. Using a peak-finding algorithm on [Mg/Fe] distributions in narrow [Fe/H] bins, the paper then compares the gas accretion histories of these categories over the last 8 Gyr. It reports that bimodal galaxies experience increasing inflow of metal-poor gas over the past 5-6 Gyr, grow larger gas disks, and form a low-alpha sequence from stars born in the diluted outer gas disk. The paper contrasts smooth CGM accretion with gas-rich mergers as two delivery mechanisms and concludes that both can produce bimodal patterns, with slightly different morphologies. The analysis is built on public FIRE-2 simulations, and the paper is explicit that its agreement with Milky Way trends is qualitative; it also states several limitations, including the deferral of the strongest bimodal cases to Barry et al. (in prep).

Significance. If the central correlation is robust, the paper makes a valuable contribution by showing that alpha-bimodality in Milky Way-mass galaxies is not a universal feature and that its presence in FIRE-2 is tied to late-time accretion of metal-poor gas. The accretion metrics (inflow mass, gas disk size, infall metallicity) are defined independently of the bimodality classification, so the observed correlation is not forced by construction. The paper also benefits from using the publicly available FIRE-2 simulations, from stating data availability, and from candidly acknowledging that the simulated bimodal sequences are less separated than in the Milky Way. However, the small number of galaxies, an internal inconsistency in the peak-detection thresholds, and the absence of significance tests currently limit the strength of the central claim; these issues are identifiable and likely fixable within the manuscript's scope.

major comments (3)
  1. [Section 3.1 and Appendix A] The classification threshold is not uniquely specified: Section 3.1 states that find_peaks is applied with 'a prominence of at least 0.3' and a peak separation of 0.025 dex, while Appendix A states that the same procedure uses a prominence of 0.03 and the same 0.025 dex separation. These thresholds differ by an order of magnitude, and the number of [Fe/H] bins in which a double peak is detected depends directly on this parameter. The weakly-bimodal class is then admitted only after separately lowering the peak distance to 0.015 dex, so the three categories are defined under different detection criteria. Because the entire accretion-history contrast in Figs. 5-7 is computed over these categories, the central claim of the paper is sensitive to this choice. Please specify a single, justified detection criterion, verify that the categorical assignments in Table 1 are stable to reasonable threshold variations (e.g., a grid in prominence and distance), and report the resulting category assignments. The extrapolation of the separation line into the converging region for Louise and Remus, described in Section 3.1, should also be quantified as a source of uncertainty.
  2. [Section 3.3, Figs. 5-6] The claim that bimodal galaxies experience 'rapidly increasing' inflow and 'significant growth of the gas disk' is based on median tracks for 5 bimodal, 2 weakly-bimodal, and 3 non-bimodal galaxies, with shaded 1-sigma spreads. No significance test is applied to the differences between categories, and with n=5, 2, 3 the visual separation could be driven by one or two galaxies (for example, Louise has the largest R_edge,gas and R_infall in Table 1). The word 'significant' in the abstract and Section 5 is therefore not supported by a statistical test. Please add a permutation or bootstrap test that compares the bimodal and non-bimodal distributions of inflow mass and gas-disk radius at fixed lookback times (e.g., at 2, 4, and 6 Gyr ago), and report effect sizes or p-values. This is load-bearing because the abstract's causal statement about recent infall is inferred from the category contrast in these figures.
  3. [Section 1 and Section 3.1] The sample of 11 galaxies is not demonstrated to be representative of Milky Way-mass FIRE-2 systems, because Section 1 states that 'four additional galaxies with stronger bimodality' are examined in the companion paper Barry et al. (in prep), and Section 3.1 defers the strongly-bimodal case m12b to that same paper. If those systems were included, the bimodal fraction (currently 5 of 11) and the contrast in accretion histories could change materially, and the paper's conclusion that bimodality is specifically tied to late metal-poor gas accretion would not be falsifiable within this manuscript's scope. Please state the selection criteria that produced the 11 galaxies, or include the deferred systems in at least a summary comparison (e.g., their inflow mass and disk-size tracks) so the reader can assess whether the central correlation holds across the full FIRE-2 Milky Way-mass sample.
minor comments (4)
  1. [Section 1] There is a typo in 'NIHAO-UHD simluations'; it should be 'simulations'.
  2. [Figure 1 caption] The caption relies on frame colors ('red frame', 'blue frame', 'navy frame') to identify galaxy categories; please add explicit panel letters or symbols so the figure is interpretable without color.
  3. [Table 1 and Section 3.3] The column 'R_infall' is described as 'the radius of the 10-kpc shell enclosing gas infall particles'; this wording is ambiguous about whether the shell is a spherical shell of thickness 10 kpc or a shell starting at a radius 10 kpc. Please clarify the geometric definition in the text or caption.
  4. [Section 3.4] The text refers first to 'Fig. 9' for the metallicity distributions and then to 'Fig. 8' for the radial distribution; since these are sequential sections, it would be easier for the reader if the figures were referenced in the order they are discussed, or if each reference carried a brief content descriptor.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the central claim is an empirical correlation between independently defined bimodality classes and gas accretion metrics.

full rationale

The paper's central claim is an empirical correlation extracted from simulation outputs, not a fitted derivation. The bimodality classification is based on peak finding in [Mg/Fe] distributions (Section 3.1 and Appendix A), while the gas accretion metrics — inflow mass through a 10-kpc shell (Section 3.3), gas disk edge at a fixed surface-density threshold (Section 3.3), and metallicity distributions of inflowing gas (Section 3.4) — are defined independently of the classification. No parameter is fitted to the bimodality categories and then used to 'predict' those same categories; the lagged correlation between low-α fraction and inflow/disk size (Fig. 7) is measured, not constructed. The reliance on FIRE-2 method papers (Hopkins et al. 2018; Wetzel et al. 2016; Garrison-Kimmel et al. 2019) is a normal citation of public, externally validated simulations, and no uniqueness theorem or ansatz from the authors' prior work is invoked to force the conclusion. The paper defers strong-bimodality cases to Barry et al. (in prep) and uses a prominence threshold that differs between Section 3.1 (0.3) and Appendix A (0.03); these are scope and robustness concerns, not circularity. The accretion metrics and the bimodality labels are not related by construction, so the abstract's claim about recent metal-poor infall is a genuine interpretation of the simulation data rather than a restatement of the classification criteria.

Assumptions & free parameters 8 free parameters · 4 assumptions · 0 invented entities

The central claim rests on a chain of hand-set analysis thresholds (peak detection, disk selection, aperture, gas disk edge, infall shell, onset fraction) and on domain assumptions about the fidelity and representativeness of the FIRE-2 simulations. No new physical entities are introduced.

free parameters (8)
  • Peak distance threshold for bimodality = 0.025 dex, lowered to 0.015 for weakly bimodal
    Hand-set threshold for minimum separation between two peaks in the [Mg/Fe] distribution; changing it changes which galaxies are classified as bimodal.
  • Peak prominence threshold = 0.3 (Section 3.1) or 0.03 (Appendix A)
    Hand-set parameter for peak detection in scipy.signal.find_peaks; the two values in the paper are inconsistent, affecting reproducibility of the classification.
  • Circularity cut for disk selection = epsilon > 0.2
    Standard selection from Yu et al. (2021) to define disk stars; affects which stars are included in the abundance plane.
  • Stellar aperture radius = R98 (radius enclosing 98% of stars at z=0)
    Choice of aperture affects visibility of the metal-poor tail of the low-alpha sequence; changing the aperture could alter classification.
  • Gas disk edge surface density threshold = 5 M_sun/pc^2
    Definition of gas disk edge used to measure disk size growth; a different threshold would change the measured sizes.
  • Infall shell geometry = 10 kpc shell, inner radius R_infall listed in Table 1
    Hand-chosen inner radius (to exceed current gas disk) and shell thickness; affects the measured inflow mass and accretion timing.
  • Low-alpha onset fraction threshold = 20% of new stars in low-alpha sequence
    Threshold used to define when the low-alpha sequence begins; a different value shifts the onset times in Table 1.
  • Satellite assignment criteria = 0.8 R_halo and 2 v_circ
    Adopted from Santistevan et al. (2020) to classify gas as originating from satellite galaxies; this choice affects the M_sat/M_infall fractions.
assumptions (4)
  • domain assumption FIRE-2 simulations faithfully model the star formation, feedback, and chemical enrichment physics that set [Mg/Fe] ratios.
    The entire analysis assumes that simulated abundance patterns are indicative of real galaxies; if the sub-grid models for SNIa/SNII yields or metal diffusion are inaccurate, the bimodality classification and its link to gas accretion would not transfer to the real Milky Way.
  • domain assumption The 11 galaxies studied are representative of the Milky Way-mass galaxy population.
    The paper does not describe how the 11 galaxies were selected among all FIRE-2 Milky Way-mass runs and defers four strongly bimodal systems to a companion paper, so sample completeness is assumed.
  • domain assumption Mg is a valid representative alpha element and the [Fe/H]-[Mg/Fe] plane is a sufficient diagnostic of alpha-element bimodality.
    The analysis uses only Mg among alpha elements; real bimodality may appear differently for other alpha elements (e.g., Si, O), and the conclusions could depend on this choice.
  • domain assumption The gas tracking method correctly identifies accreted gas and its origin.
    Gas inflow is defined as particles with negative radial velocity within a 10 kpc shell at selected snapshots; this proxy may miss or misidentify some accretion events, and the origin assignment depends on halo membership criteria.

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Pith. "Pith review of Effect of gas accretion on $\alpha$-element bimodality in Milky Way-mass galaxies in the FIRE-2 simulations." pith.science (2026). https://pith.science/paper/ULRYNNKM

@misc{pith2026250112342,
  author       = {Pith},
  title        = {Pith review of: Effect of gas accretion on $\alpha$-element bimodality in Milky Way-mass galaxies in the FIRE-2 simulations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ULRYNNKM}},
  note         = {Machine review of arXiv:2501.12342}
}
abstract

We analyse the stellar distributions on the [Fe/H]-[Mg/Fe] plane for 11 Milky Way-mass galaxies from the FIRE-2 cosmological baryonic zoom-in simulations. Alpha-element bimodality, in the form of two separate sequences on the [Fe/H]-[Mg/Fe] plane, is not a universal feature of disk galaxies. Five galaxies demonstrate double sequences with the $\alpha$-enriched one being older and kinematically hotter, in qualitative agreement with the high-$\alpha$ and low-$\alpha$ populations in the Milky Way disk; three galaxies have unimodal distribution, two show weakly-bimodal features where low-$\alpha$ sequence is visible only over a short range of metallicities, and one show strong bimodality with a different slope of high-$\alpha$ population. We examine the galaxies' gas accretion history over the last 8 Gyr, when bimodal sequences emerge, and demonstrate that the presence of the low-$\alpha$ sequence in the bimodal galaxies is related to the recent infall of metal-poor gas from the circumgalactic medium that joins the galaxy in the outskirts and induces significant growth of the gas disks compared to their non-bimodal counterparts. We also analyse the sources of the accreted gas and illustrate that both gas-rich mergers and smooth accretion of ambient gas can be the source of the accreted gas, and create slightly different bimodal patterns.

Figures

Figures reproduced from arXiv: 2501.12342 by the authors.

Figure 1
Figure 1. Distributions on the [Fe/H]-[Mg/Fe] plane for disk stars with formation radius smaller than 𝑅98 at 𝑧 = 0. Panels (a) - (e) in red frame show bimodal galaxies, (f) – “extreme” case with multiple sequences, (g), (h) in blue frame – weakly bimodal galaxies, (i) - (k) inside navy frame – non-bimodal galaxies. The red curve on panels (a) - (e) shows the separation between high- and low-𝛼 sequences. in our sample: iron en… view at source ↗
Figure 2
Figure 2. Left: distribution of [Mg/Fe] for stars with [Fe/H] = −0.47±0.05 in Louise. Black dashed lines indicate the location of the peaks in the distribution, red lines marks the location of the minimum between two peaks, separating stars belonging to the low- and high-𝛼 sequences. Right: distribution of [Mg/Fe] for stars binned by [Fe/H], red dots mark the position of minimum, when two peaks are detected. Louise has mergin… view at source ↗
Figure 3
Figure 3. 2D histograms of distribution on [Fe/H] - [Mg/Fe] colored by age of stars for Louise (left) and m12i (right). In both galaxies the high-𝛼 sequence has a wide scatter in [Mg/Fe] and is formed by old stars, and then becomes narrower for stars younger than ≈6 Gyrs [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Elemental evolution tracks for stars binned by birth radii in Louise (left) and m12i (right). The dots mark the age of the stars with corresponding median [Fe/H] and [Mg/Fe]. The greyscale histogram in the background shows the total distribution of the disk stars forme…
Figure 5
Figure 5. Figure 5: Time evolution of the mass of the gas inflow (see 3.3 for defini￾tion) normalized over the mass of gas in the galaxy at 𝑡bursty which roughly corresponds to the disk settling time. Bimodal galaxies experience increasing inflow over the past 5-6 Gyrs. galaxies have diff…
Figure 7
Figure 7. Figure 7: Fraction of stars in the low-𝛼 sequence for bimodal galaxies. upper envelope evolves from [Fe/H]≈-0.6 to -0.25 and matches the median metallicity of the host galaxy at that time, which could be explained by enrichment of the inner CGM with strong outflows that are ubiq…
Figure 8
Figure 8. Figure 8: Radial distribution of accreted gas inflow at 𝑧 = 0, with radius normalized by 𝑅98,∗, the radius enclosing 98% of the stellar mass. In bimodal galaxies, accreted inflow demonstrates a more extended spatial configuration, while in non-bimodal and weakly-bimodal galaxies…
Figure 9
Figure 9. Figure 9: Mass-weighted metallicity distributions of the inflowing gas over time. The red vertical line marks the end of bursty star formation, while the pink dashed line indicates the onset of the low-𝛼 sequence. While all galaxies demonstrate similar distributions with a sharp…
Figure 10
Figure 10. Figure 10: Top: elemental evolution tracks for stars binned by birth radii in m12f. Middle: time evolution of [Fe/H] at different radii. Colours are the same as in the top panel. Bottom: Orbits of three satellites that contribute the most to the gas inflow, colored by mass ratio…
Figure 11
Figure 11. Figure 11: Distribution of stars in m12f on [Fe/H]-[Mg/Fe] plane in three radial bins. Despite being overall weakly bimodal, m12f shows very clear double sequences at certain radii. outer regions via the “shrinking disk” mechanism. In this case, the formation of high-alpha disk …

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Works this paper leans on

107 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]

    G., Navarro J

    Abadi M. G., Navarro J. F., Steinmetz M., Eke V. R., 2003, @doi [ ] 10.1086/378316 , https://ui.adsabs.harvard.edu/abs/2003ApJ...597...21A 597, 21

    doi:10.1086/378316 2003

  3. [3]

    Z., et al., 2013, @doi [ ] 10.1051/0004-6361/201321520 , https://ui.adsabs.harvard.edu/abs/2013A&A...554A..44A 554, A44

    Adibekyan V. Z., et al., 2013, @doi [ ] 10.1051/0004-6361/201321520 , https://ui.adsabs.harvard.edu/abs/2013A&A...554A..44A 554, A44

    doi:10.1051/0004-6361/201321520 2013

  4. [4]

    Agertz O., et al., 2021, @doi [ ] 10.1093/mnras/stab322 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.5826A 503, 5826

    doi:10.1093/mnras/stab322 2021

  5. [5]

    Anders F., et al., 2014, @doi [ ] 10.1051/0004-6361/201323038 , https://ui.adsabs.harvard.edu/abs/2014A&A...564A.115A 564, A115

    doi:10.1051/0004-6361/201323038 2014

  6. [6]

    H., Weinberg D

    Andrews B. H., Weinberg D. H., Sch \"o nrich R., Johnson J. A., 2017, @doi [ ] 10.3847/1538-4357/835/2/224 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..224A 835, 224

    doi:10.3847/1538-4357/835/2/224 2017

  7. [7]

    F., Quataert E., Murray N., 2017, @doi [ ] 10.1093/mnras/stx1517 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4698A 470, 4698

    Angl \'e s-Alc \'a zar D., Faucher-Gigu \`e re C.-A., Kere s D., Hopkins P. F., Quataert E., Murray N., 2017, @doi [ ] 10.1093/mnras/stx1517 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4698A 470, 4698

    doi:10.1093/mnras/stx1517 2017

  8. [8]

    E., Arora A., Hopkins P

    Ansar S., Pearson S., Sanderson R. E., Arora A., Hopkins P. F., Wetzel A., Cunningham E. C., Quinn J., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2309.16811 , https://ui.adsabs.harvard.edu/abs/2023arXiv230916811A p. arXiv:2309.16811

    arXiv doi:10.48550/arxiv.2309.16811 2023

Show all 107 references
  1. [9]

    arXiv:2407.07985

    Beane A., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.07985 , https://ui.adsabs.harvard.edu/abs/2024arXiv240707985B p. arXiv:2407.07985

    2024 doi arXiv

  2. [10]

    arXiv:2410.21580

    Beane A., Johnson J., Semenov V., Hernquist L., Chandra V., Conroy C., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2410.21580 , https://ui.adsabs.harvard.edu/abs/2024arXiv241021580B p. arXiv:2410.21580

    2024 doi arXiv

  3. [11]

    A., Wetzel A., Loebman S

    Bellardini M. A., Wetzel A., Loebman S. R., Faucher-Gigu \`e re C.-A., Ma X., Feldmann R., 2021, @doi [ ] 10.1093/mnras/stab1606 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.4586B 505, 4586

    2021 doi

  4. [12]

    A., Wetzel A., Loebman S

    Bellardini M. A., Wetzel A., Loebman S. R., Bailin J., 2022, @doi [ ] 10.1093/mnras/stac1637 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514.4270B 514, 4270

    2022 doi

  5. [13]

    Bensby T., Feltzing S., 2012, in European Physical Journal Web of Conferences. p. 04001 ( @eprint arXiv 1110.0905 ), @doi 10.1051/epjconf/20121904001

    2012 arXiv

  6. [14]

    S., Yong D., Mel \'e ndez J., 2011, @doi [ ] 10.1088/2041-8205/735/2/L46 , https://ui.adsabs.harvard.edu/abs/2011ApJ...735L..46B 735, L46

    Bensby T., Alves-Brito A., Oey M. S., Yong D., Mel \'e ndez J., 2011, @doi [ ] 10.1088/2041-8205/735/2/L46 , https://ui.adsabs.harvard.edu/abs/2011ApJ...735L..46B 735, L46

    2011 doi

  7. [15]

    S., 2014, @doi [ ] 10.1051/0004-6361/201322631 , https://ui.adsabs.harvard.edu/abs/2014A&A...562A..71B 562, A71

    Bensby T., Feltzing S., Oey M. S., 2014, @doi [ ] 10.1051/0004-6361/201322631 , https://ui.adsabs.harvard.edu/abs/2014A&A...562A..71B 562, A71

    2014 doi

  8. [16]

    Binney J., Vasiliev E., 2024, @doi [ ] 10.1093/mnras/stad3312 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.1915B 527, 1915

    2024 doi

  9. [17]

    W., 2012, @doi [ ] 10.1088/0004-637X/751/2/131 , https://ui.adsabs.harvard.edu/abs/2012ApJ...751..131B 751, 131

    Bovy J., Rix H.-W., Hogg D. W., 2012, @doi [ ] 10.1088/0004-637X/751/2/131 , https://ui.adsabs.harvard.edu/abs/2012ApJ...751..131B 751, 131

    2012 doi

  10. [18]

    Buck T., 2020, @doi [ ] 10.1093/mnras/stz3289 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.5435B 491, 5435

    2020 doi

  11. [19]

    Buder S., et al., 2018, @doi [ ] 10.1093/mnras/sty1281 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.4513B 478, 4513

    2018 doi

  12. [20]

    Buder S., et al., 2021, @doi [ ] 10.1093/mnras/stab1242 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.506..150B 506, 150

    2021 doi

  13. [21]

    arXiv:2310.13050

    Chandra V., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2310.13050 , https://ui.adsabs.harvard.edu/abs/2023arXiv231013050C p. arXiv:2310.13050

    2023 doi arXiv

  14. [22]

    R., Sharma S., Bland-Hawthorn J., Kobayashi C., Karakas A

    Chen B., Hayden M. R., Sharma S., Bland-Hawthorn J., Kobayashi C., Karakas A. I., 2023, @doi [ ] 10.1093/mnras/stad1568 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.3791C 523, 3791

    2023 doi

  15. [23]

    Chiappini C., Matteucci F., Gratton R., 1997, @doi [ ] 10.1086/303726 , https://ui.adsabs.harvard.edu/abs/1997ApJ...477..765C 477, 765

    1997 doi

  16. [24]

    R., Grand R

    Ciuc a I., Kawata D., Miglio A., Davies G. R., Grand R. J. J., 2021, @doi [ ] 10.1093/mnras/stab639 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.2814C 503, 2814

    2021 doi

  17. [25]

    J., et al., 2019, @doi [ ] 10.1093/mnras/stz104 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.3476C 484, 3476

    Clarke A. J., et al., 2019, @doi [ ] 10.1093/mnras/stz104 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.3476C 484, 3476

    2019 doi

  18. [26]

    J., et al., 2023, @doi [ ] 10.3847/1538-3881/accc83 , https://ui.adsabs.harvard.edu/abs/2023AJ....166...80D 166, 80

    Dalcanton J. J., et al., 2023, @doi [ ] 10.3847/1538-3881/accc83 , https://ui.adsabs.harvard.edu/abs/2023AJ....166...80D 166, 80

    2023 doi

  19. [27]

    O., Johnson J

    Dubay L. O., Johnson J. A., Johnson J. W., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2404.08059 , https://ui.adsabs.harvard.edu/abs/2024arXiv240408059D p. arXiv:2404.08059

    2024 doi arXiv

  20. [28]

    Escala I., et al., 2018, @doi [ ] 10.1093/mnras/stx2858 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.2194E 474, 2194

    2018 doi

  21. [29]

    Faucher-Gigu \`e re C.-A., Lidz A., Zaldarriaga M., Hernquist L., 2009, @doi [ ] 10.1088/0004-637X/703/2/1416 , https://ui.adsabs.harvard.edu/abs/2009ApJ...703.1416F 703, 1416

    2009 doi

  22. [30]

    Fuhrmann K., 1998, , https://ui.adsabs.harvard.edu/abs/1998A&A...338..161F 338, 161

    1998

  23. [31]

    Gaia Collaboration et al., 2023, @doi [ ] 10.1051/0004-6361/202243511 , https://ui.adsabs.harvard.edu/abs/2023A&A...674A..38G 674, A38

    2023 doi

  24. [32]

    J., Wetzel A., Hopkins P

    Gandhi P. J., Wetzel A., Hopkins P. F., Shappee B. J., Wheeler C., Faucher-Gigu \`e re C.-A., 2022, @doi [ ] 10.1093/mnras/stac2228 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.1941G 516, 1941

    2022 doi

  25. [33]

    Garrison-Kimmel S., et al., 2017, @doi [ ] 10.1093/mnras/stx1710 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.1709G 471, 1709

    2017 doi

  26. [34]

    Garrison-Kimmel S., et al., 2018, @doi [ ] 10.1093/mnras/sty2513 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.4133G 481, 4133

    2018 doi

  27. [35]

    Garrison-Kimmel S., et al., 2019a, @doi [ ] 10.1093/mnras/stz1317 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.1380G 487, 1380

    doi

  28. [36]

    Garrison-Kimmel S., et al., 2019b, @doi [ ] 10.1093/mnras/stz2507 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.4574G 489, 4574

    doi

  29. [37]

    Gilmore G., Reid N., 1983, @doi [ ] 10.1093/mnras/202.4.1025 , https://ui.adsabs.harvard.edu/abs/1983MNRAS.202.1025G 202, 1025

    1983 doi

  30. [38]

    L., Wetzel A., Bellardini M

    Graf R. L., Wetzel A., Bellardini M. A., Bailin J., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2402.15614 , https://ui.adsabs.harvard.edu/abs/2024arXiv240215614G p. arXiv:2402.15614

    2024 doi arXiv

  31. [39]

    Grand R. J. J., et al., 2018, @doi [ ] 10.1093/mnras/stx3025 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.3629G 474, 3629

    2018 doi

  32. [40]

    B., et al., 2023, @doi [ ] 10.1093/mnras/stac3712 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.2598G 519, 2598

    Gurvich A. B., et al., 2023, @doi [ ] 10.1093/mnras/stac3712 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.2598G 519, 2598

    2023 doi

  33. [41]

    Hafen Z., et al., 2022, @doi [ ] 10.1093/mnras/stac1603 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514.5056H 514, 5056

    2022 doi

  34. [42]

    R., et al., 2015, @doi [ ] 10.1088/0004-637X/808/2/132 , https://ui.adsabs.harvard.edu/abs/2015ApJ...808..132H 808, 132

    Hayden M. R., et al., 2015, @doi [ ] 10.1088/0004-637X/808/2/132 , https://ui.adsabs.harvard.edu/abs/2015ApJ...808..132H 808, 132

    2015 doi

  35. [43]

    R., Recio-Blanco A., de Laverny P., Mikolaitis S., Worley C

    Hayden M. R., Recio-Blanco A., de Laverny P., Mikolaitis S., Worley C. C., 2017, @doi [ ] 10.1051/0004-6361/201731494 , https://ui.adsabs.harvard.edu/abs/2017A&A...608L...1H 608, L1

    2017 doi

  36. [44]

    D., Katz D., G \'o mez A., 2013, @doi [ ] 10.1051/0004-6361/201321397 , https://ui.adsabs.harvard.edu/abs/2013A&A...560A.109H 560, A109

    Haywood M., Di Matteo P., Lehnert M. D., Katz D., G \'o mez A., 2013, @doi [ ] 10.1051/0004-6361/201321397 , https://ui.adsabs.harvard.edu/abs/2013A&A...560A.109H 560, A109

    2013 doi

  37. [45]

    Haywood M., Di Matteo P., Lehnert M., Snaith O., Fragkoudi F., Khoperskov S., 2018, @doi [ ] 10.1051/0004-6361/201731363 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A..78H 618, A78

    2018 doi

  38. [46]

    D., Di Matteo P., Khoperskov S., 2019, @doi [ ] 10.1051/0004-6361/201834155 , https://ui.adsabs.harvard.edu/abs/2019A&A...625A.105H 625, A105

    Haywood M., Snaith O., Lehnert M. D., Di Matteo P., Khoperskov S., 2019, @doi [ ] 10.1051/0004-6361/201834155 , https://ui.adsabs.harvard.edu/abs/2019A&A...625A.105H 625, A105

    2019 doi

  39. [47]

    F., 2015, @doi [ ] 10.1093/mnras/stv195 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450...53H 450, 53

    Hopkins P. F., 2015, @doi [ ] 10.1093/mnras/stv195 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450...53H 450, 53

    2015 doi

  40. [48]

    F., et al., 2018, @doi [ ] 10.1093/mnras/sty1690 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480..800H 480, 800

    Hopkins P. F., et al., 2018, @doi [ ] 10.1093/mnras/sty1690 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480..800H 480, 800

    2018 doi

  41. [49]

    Imig J., et al., 2023, @doi [ ] 10.3847/1538-4357/ace9b8 , https://ui.adsabs.harvard.edu/abs/2023ApJ...954..124I 954, 124

    2023 doi

  42. [50]

    R., Thielemann F.-K., 1999, @doi [ ] 10.1086/313278 , https://ui.adsabs.harvard.edu/abs/1999ApJS..125..439I 125, 439

    Iwamoto K., Brachwitz F., Nomoto K., Kishimoto N., Umeda H., Hix W. R., Thielemann F.-K., 1999, @doi [ ] 10.1086/313278 , https://ui.adsabs.harvard.edu/abs/1999ApJS..125..439I 125, 439

    1999 doi

  43. [51]

    G., Tout C

    Izzard R. G., Tout C. A., Karakas A. I., Pols O. R., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07446.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.350..407I 350, 407

    2004

  44. [52]

    W., et al., 2021, @doi [ ] 10.1093/mnras/stab2718 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.4484J 508, 4484

    Johnson J. W., et al., 2021, @doi [ ] 10.1093/mnras/stab2718 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.4484J 508, 4484

    2021 doi

  45. [53]

    Khoperskov S., Haywood M., Snaith O., Di Matteo P., Lehnert M., Vasiliev E., Naroenkov S., Berczik P., 2021, @doi [ ] 10.1093/mnras/staa3996 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.501.5176K 501, 5176

    2021 doi

  46. [54]

    Kobayashi C., Bhattacharya S., Arnaboldi M., Gerhard O., 2023, @doi [ ] 10.3847/2041-8213/acf7c7 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956L..14K 956, L14

    2023 doi

  47. [55]

    Kordopatis G., et al., 2013, @doi [ ] 10.1093/mnras/stt1804 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.436.3231K 436, 3231

    2013 doi

  48. [56]

    Kroupa P., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04022.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.322..231K 322, 231

    2001

  49. [57]

    Kubryk M., Prantzos N., Athanassoula E., 2015, @doi [ ] 10.1051/0004-6361/201424171 , https://ui.adsabs.harvard.edu/abs/2015A&A...580A.126K 580, A126

    2015 doi

  50. [58]

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

    1999 doi

  51. [59]

    Lian J., et al., 2020a, @doi [ ] 10.1093/mnras/staa867 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.2561L 494, 2561

    doi

  52. [60]

    Lian J., et al., 2020b, @doi [ ] 10.1093/mnras/staa2078 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.2371L 497, 2371

    doi

  53. [61]

    Lian J., et al., 2020c, @doi [ ] 10.1093/mnras/staa2205 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.3557L 497, 3557

    doi

  54. [62]

    R., Ro s kar R., Debattista V

    Loebman S. R., Ro s kar R., Debattista V. P., Ivezi \'c Z ., Quinn T. R., Wadsley J., 2011, @doi [ ] 10.1088/0004-637X/737/1/8 , https://ui.adsabs.harvard.edu/abs/2011ApJ...737....8L 737, 8

    2011 doi

  55. [63]

    L., et al., 2015, @doi [Research in Astronomy and Astrophysics] 10.1088/1674-4527/15/8/002 , https://ui.adsabs.harvard.edu/abs/2015RAA....15.1095L 15, 1095

    Luo A. L., et al., 2015, @doi [Research in Astronomy and Astrophysics] 10.1088/1674-4527/15/8/002 , https://ui.adsabs.harvard.edu/abs/2015RAA....15.1095L 15, 1095

    2015 doi

  56. [64]

    F., Wetzel A

    Ma X., Hopkins P. F., Wetzel A. R., Kirby E. N., Angl \'e s-Alc \'a zar D., Faucher-Gigu \`e re C.-A., Kere s D., Quataert E., 2017, @doi [ ] 10.1093/mnras/stx273 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.467.2430M 467, 2430

    2017 doi

  57. [65]

    T., et al., 2017, @doi [ ] 10.1093/mnras/stx1774 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.3057M 471, 3057

    Mackereth J. T., et al., 2017, @doi [ ] 10.1093/mnras/stx1774 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.3057M 471, 3057

    2017 doi

  58. [66]

    T., Crain R

    Mackereth J. T., Crain R. A., Schiavon R. P., Schaye J., Theuns T., Schaller M., 2018, @doi [ ] 10.1093/mnras/sty972 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.477.5072M 477, 5072

    2018 doi

  59. [67]

    R., et al., 2017, @doi [ ] 10.3847/1538-3881/aa784d , https://ui.adsabs.harvard.edu/abs/2017AJ....154...94M 154, 94

    Majewski S. R., et al., 2017, @doi [ ] 10.3847/1538-3881/aa784d , https://ui.adsabs.harvard.edu/abs/2017AJ....154...94M 154, 94

    2017 doi

  60. [68]

    Mannucci F., Della Valle M., Panagia N., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10501.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.370..773M 370, 773

    2006

  61. [69]

    Marigo P., 2001, @doi [ ] 10.1051/0004-6361:20000247 , https://ui.adsabs.harvard.edu/abs/2001A&A...370..194M 370, 194

    2001 doi

  62. [70]

    C., Crain R

    Mason A. C., Crain R. A., Schiavon R. P., Weinberg D. H., Pfeffer J., Schaye J., Schaller M., Theuns T., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2311.00041 , https://ui.adsabs.harvard.edu/abs/2023arXiv231100041M p. arXiv:2311.00041

    2023 doi arXiv

  63. [71]

    R., Moreno J., Faucher-Gigu \`e re C.-A., Hopkins P

    McCluskey F., Wetzel A., Loebman S. R., Moreno J., Faucher-Gigu \`e re C.-A., Hopkins P. F., 2024, @doi [ ] 10.1093/mnras/stad3547 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.6926M 527, 6926

    2024 doi

  64. [72]

    L., Kere s D., Faucher-Gigu \`e re C.-A., Hopkins P

    Muratov A. L., Kere s D., Faucher-Gigu \`e re C.-A., Hopkins P. F., Quataert E., Murray N., 2015, @doi [ ] 10.1093/mnras/stv2126 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.2691M 454, 2691

    2015 doi

  65. [73]

    Ness M., et al., 2018, @doi [ ] 10.3847/1538-4357/aa9d8e , https://ui.adsabs.harvard.edu/abs/2018ApJ...853..198N 853, 198

    2018 doi

  66. [74]

    L., et al., 2014, @doi [ ] 10.1088/0004-637X/796/1/38 , https://ui.adsabs.harvard.edu/abs/2014ApJ...796...38N 796, 38

    Nidever D. L., et al., 2014, @doi [ ] 10.1088/0004-637X/796/1/38 , https://ui.adsabs.harvard.edu/abs/2014ApJ...796...38N 796, 38

    2014 doi

  67. [75]

    L., et al., 2020, @doi [ ] 10.3847/1538-4357/ab7305 , https://ui.adsabs.harvard.edu/abs/2020ApJ...895...88N 895, 88

    Nidever D. L., et al., 2020, @doi [ ] 10.3847/1538-4357/ab7305 , https://ui.adsabs.harvard.edu/abs/2020ApJ...895...88N 895, 88

    2020 doi

  68. [76]

    L., et al., 2024, in Tabatabaei F., Barbuy B., Ting Y.-S., eds, IAU Symposium Vol

    Nidever D. L., et al., 2024, in Tabatabaei F., Barbuy B., Ting Y.-S., eds, IAU Symposium Vol. 377, Early Disk-Galaxy Formation from JWST to the Milky Way. pp 115--122 ( @eprint arXiv 2306.04688 ), @doi 10.1017/S1743921323002016

    2024 arXiv

  69. [77]

    Nomoto K., Tominaga N., Umeda H., Kobayashi C., Maeda K., 2006, @doi [ ] 10.1016/j.nuclphysa.2006.05.008 , https://ui.adsabs.harvard.edu/abs/2006NuPhA.777..424N 777, 424

    2006 doi

  70. [78]

    Pandya V., et al., 2021, @doi [ ] 10.1093/mnras/stab2714 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.2979P 508, 2979

    2021 doi

  71. [79]

    B., Faucher-Gigu \`e re C.-A., Hafen Z., Stern J., Snaith O., 2023, @doi [ ] 10.1093/mnras/stad206 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.1672P 520, 1672

    Parul H., Bailin J., Wetzel A., Gurvich A. B., Faucher-Gigu \`e re C.-A., Hafen Z., Stern J., Snaith O., 2023, @doi [ ] 10.1093/mnras/stad206 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.1672P 520, 1672

    2023 doi

  72. [80]

    B., Loebman S

    Patel P. B., Loebman S. R., Wetzel A., Faucher-Gigu \`e re C.-A., El-Badry K., Bailin J., 2022, @doi [ ] 10.1093/mnras/stac834 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.5671P 512, 5671

    2022 doi

  73. [81]

    Prantzos N., et al., 2023, @doi [ ] 10.1093/mnras/stad1551 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.2126P 523, 2126

    2023 doi

  74. [82]

    Queiroz A. B. A., et al., 2020, @doi [ ] 10.1051/0004-6361/201937364 , https://ui.adsabs.harvard.edu/abs/2020A&A...638A..76Q 638, A76

    2020 doi

  75. [83]

    Queiroz A. B. A., et al., 2023, @doi [ ] 10.1051/0004-6361/202245399 , https://ui.adsabs.harvard.edu/abs/2023A&A...673A.155Q 673, A155

    2023 doi

  76. [84]

    P., Read J

    Renaud F., Agertz O., Andersson E. P., Read J. I., Ryde N., Bensby T., Rey M. P., Feuillet D. K., 2021, @doi [ ] 10.1093/mnras/stab543 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.503.5868R 503, 5868

    2021 doi

  77. [85]

    Santistevan I. B., Wetzel A., El-Badry K., Bland-Hawthorn J., Boylan-Kolchin M., Bailin J., Faucher-Gigu \`e re C.-A., Benincasa S., 2020, @doi [ ] 10.1093/mnras/staa1923 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497..747S 497, 747

    2020 doi

  78. [87]

    R., Bland-Hawthorn J., 2021, @doi [ ] 10.1093/mnras/stab2015 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.5882S 507, 5882

    Sharma S., Hayden M. R., Bland-Hawthorn J., 2021, @doi [ ] 10.1093/mnras/stab2015 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.5882S 507, 5882

    2021 doi

  79. [88]

    Shen S., Wadsley J., Stinson G., 2010, @doi [ ] 10.1111/j.1365-2966.2010.17047.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.407.1581S 407, 1581

    2010

  80. [89]

    Silva Aguirre V., et al., 2018, @doi [ ] 10.1093/mnras/sty150 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.5487S 475, 5487

    2018 doi

  81. [90]

    Soubiran C., Bienaym \'e O., Siebert A., 2003, @doi [ ] 10.1051/0004-6361:20021615 , https://ui.adsabs.harvard.edu/abs/2003A&A...398..141S 398, 141

    2003 doi

  82. [91]

    Spitoni E., Silva Aguirre V., Matteucci F., Calura F., Grisoni V., 2019, @doi [ ] 10.1051/0004-6361/201834188 , https://ui.adsabs.harvard.edu/abs/2019A&A...623A..60S 623, A60

    2019 doi

  83. [92]

    Spitoni E., Verma K., Silva Aguirre V., Calura F., 2020, @doi [ ] 10.1051/0004-6361/201937275 , https://ui.adsabs.harvard.edu/abs/2020A&A...635A..58S 635, A58

    2020 doi

  84. [93]

    Spitoni E., Aguirre B rsen-Koch V., Verma K., Stokholm A., 2022, @doi [ ] 10.1051/0004-6361/202142469 , https://ui.adsabs.harvard.edu/abs/2022A&A...663A.174S 663, A174

    2022 doi

  85. [94]

    arXiv:2405.11025

    Spitoni E., Matteucci F., Gratton R., Ratcliffe B., Minchev I., Cescutti G., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2405.11025 , https://ui.adsabs.harvard.edu/abs/2024arXiv240511025S p. arXiv:2405.11025

    2024 doi arXiv

  86. [95]

    F., Hayward C

    Su K.-Y., Hopkins P. F., Hayward C. C., Faucher-Gigu \`e re C.-A., Kere s D., Ma X., Robles V. H., 2017, @doi [ ] 10.1093/mnras/stx1463 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471..144S 471, 144

    2017 doi

  87. [96]

    Tepper-Garc \' a T., Bland-Hawthorn J., 2018, @doi [ ] 10.1093/mnras/sty1359 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.5263T 478, 5263

    2018 doi

  88. [97]

    M., 1979, @doi [ ] 10.1086/157039 , https://ui.adsabs.harvard.edu/abs/1979ApJ...229.1046T 229, 1046

    Tinsley B. M., 1979, @doi [ ] 10.1086/157039 , https://ui.adsabs.harvard.edu/abs/1979ApJ...229.1046T 229, 1046

    1979 doi

  89. [98]

    W., et al., 2022, @doi [ ] 10.1093/mnras/stab3251 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4149T 509, 4149

    Trapp C. W., et al., 2022, @doi [ ] 10.1093/mnras/stab3251 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4149T 509, 4149

    2022 doi

  90. [99]

    H., Miglio A., Lane R

    Vincenzo F., Weinberg D. H., Miglio A., Lane R. R., Roman-Lopes A., 2021, @doi [ ] 10.1093/mnras/stab2899 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.5903V 508, 5903

    2021 doi

  91. [100]

    H., Andrews B

    Weinberg D. H., Andrews B. H., Freudenburg J., 2017, @doi [ ] 10.3847/1538-4357/837/2/183 , https://ui.adsabs.harvard.edu/abs/2017ApJ...837..183W 837, 183

    2017 doi

  92. [101]

    R., Hopkins P

    Wetzel A. R., Hopkins P. F., Kim J.-h., Faucher-Gigu \`e re C.-A., Kere s D., Quataert E., 2016, @doi [ ] 10.3847/2041-8205/827/2/L23 , https://ui.adsabs.harvard.edu/abs/2016ApJ...827L..23W 827, L23

    2016 doi

  93. [102]

    arXiv:2202.06969

    Wetzel A., et al., 2022, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2022arXiv220206969W p. arXiv:2202.06969

    2022 arXiv

  94. [103]

    Wiersma R. P. C., Schaye J., Theuns T., Dalla Vecchia C., Tornatore L., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15331.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.399..574W 399, 574

    2009

  95. [104]

    Xiang M., Rix H.-W., 2022, @doi [ ] 10.1038/s41586-022-04496-5 , https://ui.adsabs.harvard.edu/abs/2022Natur.603..599X 603, 599

    2022 doi

  96. [105]

    Yu S., et al., 2021, @doi [ ] 10.1093/mnras/stab1339 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505..889Y 505, 889

    2021 doi

  97. [106]

    B., Martig M., Hayden M

    van de Sande J., Fraser-McKelvie A., Fisher D. B., Martig M., Hayden M. R., Geckos Survey Collaboration 2024, in Tabatabaei F., Barbuy B., Ting Y.-S., eds, IAU Symposium Vol. 377, Early Disk-Galaxy Formation from JWST to the Milky Way. pp 27--33 ( @eprint arXiv 2306.00059 ), @...

    2024 arXiv

  98. [107]

    B., Groenewegen M

    van den Hoek L. B., Groenewegen M. A. T., 1997, @doi [ ] 10.1051/aas:1997162 , https://ui.adsabs.harvard.edu/abs/1997A&AS..123..305V 123, 305

    1997 doi

  99. [108]

    write newline

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

Pith tools

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