Pith. sign in

REVIEW 4 major objections 4 minor 43 references

Revealing the Origins of Galactic Globular Clusters via Their Mg-Al Abundances

T0 review · 4 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

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

Pith's one-line read A globular cluster's least aluminum-rich stars carry the chemical signature of the galaxy where the cluster formed, and that signature separates native Milky Way clusters from accreted ones.

desk verdict A promising but circular method: the lowest-third [Al/Fe] tracer is tuned to the MKH labels, but the Terzan 9 result warrants a careful look. read the letter →

arxiv 2508.00526 v2 pith:BF6YIAGL submitted 2025-08-01 astro-ph.GA astro-ph.SR

Shihui Lin , Baitian Tang , Genghao Liu , JosÉ G. Fernández-Trincado , Douglas Geisler , Guy Worthey , Dante Minnitit This is my paper · ORCID
classification astro-ph.GAastro-ph.SR
keywords globularclustersmultiplepopulationsMg-AlabundanceschemicaltagginggalacticarchaeologyaccretedprimordialpopulationMilkyWayassembly
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

Many of the Milky Way's globular clusters were born in dwarf galaxies that later merged into our own, but telling those accreted clusters from native ones is hard because orbits change over time and the light-element abundance variations that clusters manufacture internally mask the chemistry of the host galaxy. This paper claims the mask can be lifted. If only the least aluminum-enhanced stars in a cluster are isolated, their $[\mathrm{Mg/Fe}]$ and $[\mathrm{Al/Fe}]$ values track the birth environment rather than internal pollution. At $[\mathrm{Fe/H}] > -1.5$, those primordial populations split cleanly into two chemical groups, with native Milky Way clusters showing higher $[\mathrm{Al/Fe}]$ than accreted ones. The scheme reclassifies NGC 288 and M4 as in-situ and Terzan 9 as accreted, turning globular clusters into readable fossils of the Galaxy's assembly history.

What carries the argument

The load-bearing object is the 'primordial population' of a cluster: the stars with the lowest $N/3$ values of $[\mathrm{Al/Fe}]$, where $N$ is the number of cluster members observed. The argument assumes that internal enrichment by polluter stars always raises aluminum, so the lower tail of the $[\mathrm{Al/Fe}]$ distribution is the only part still carrying the birth galaxy's chemical signature. The classification itself lives in the $[\mathrm{Mg/Fe}]$-$[\mathrm{Al/Fe}]$ plane: the mean values of these two ratios for the primordial population define separate empirical evolutionary tracks for in-situ and accreted clusters at $[\mathrm{Fe/H}] > -1.5$, with the separation strongest for the one-third percentile definition.

What would settle it

Measure nitrogen and oxygen abundances, or use independent photometric first-generation labels, for member stars of a cluster classified as in-situ such as M4: if the stars in the lowest-$[\mathrm{Al/Fe}]$ third also show the nitrogen-enhanced, oxygen-depleted pattern characteristic of internally enriched populations, then the 'primordial' mean $[\mathrm{Al/Fe}]$ is not primordial and the in-situ/accreted split in the $[\mathrm{Mg/Fe}]$-$[\mathrm{Al/Fe}]$ plane would be an artifact of the percentile cutoff rather than a birth-environment signature.

Watch

Extended reading notes

Core claim

The paper's central claim is that the primordial population of a globular cluster, operationally defined as the least $[\mathrm{Al/Fe}]$-enhanced one-third of its observed member stars, preserves the chemical evolution of the galaxy in which the cluster formed. Using a homogeneous sample of 2,142 red giants in 27 globular clusters, the authors find that at $[\mathrm{Fe/H}] > -1.5$ the primordial populations of in-situ and accreted clusters occupy distinct regions in the $[\mathrm{Mg/Fe}]$-$[\mathrm{Al/Fe}]$ plane, with in-situ systems showing $[\mathrm{Al/Fe}]$ above about 0.04 dex and accreted systems below. They interpret the divergence as a difference in enrichment history: the Milky Way's deep potential sustained rapid star formation and a top-heavy chemical enrichment that produced more magnesium and aluminum, while accreted dwarf galaxies were overtaken by Type Ia supernova iron at lower metallicity. On this basis NGC 288 and M4 are reclassified as in-situ, despite their dynamical classification as accreted, and Terzan 9 is reclassified as accreted despite sitting in the bulge. The paper concludes that the chemistry of the least-polluted stars is a more robust origin tracer than orbital dynamics.

Load-bearing premise

The whole classification rests on the assumption that the least aluminum-rich one-third of a cluster's observed stars are completely free of the cluster's internal aluminum pollution.

Editorial extensions

If this is right

  • Globular clusters with $[\mathrm{Fe/H}] > -1.5$ can be assigned to in-situ or accreted origin using only stellar abundances, with no orbital information needed.
  • The empirical tracks in the $[\mathrm{Mg/Fe}]$-$[\mathrm{Al/Fe}]$ plane describe how the proto-Milky Way and its dwarf companions enriched differently above $[\mathrm{Fe/H}] \sim -1.5$.
  • Clusters previously classified as accreted may actually be native stars dynamically heated during mergers, implying that the inventory of 'Splash' clusters is larger than currently recognized.
  • Terzan 9's accreted signature implies that some bulge globular clusters were born in dwarf galaxies and later deposited into the bulge, complicating bulge-formation studies.
  • Applying the same percentile method to larger, more metal-rich bulge samples should refine or test the in-situ evolutionary track at high metallicity.

Reading between the lines

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

  • If the percentile definition is right, the same low-$[\mathrm{Al/Fe}]$ tail could be used to chemically tag individual field stars as well as whole clusters, since the $[\mathrm{Mg/Fe}]$-$[\mathrm{Al/Fe}]$ dichotomy should still mark their birth galaxy.
  • The method's dependence on the one-third cutoff could be tested against independent first-generation tracers: in clusters where photometric nitrogen or oxygen indicators independently identify truly unenriched stars, the lowest-$[\mathrm{Al/Fe}]$ third should match them, and a mismatch would suggest the cutoff needs to vary with cluster mass.
  • The reclassification of NGC 288 and M4 as in-situ predicts that their member-star populations should show first-to-second generation ratios and iron spreads consistent with native Milky Way clusters, which deeper spectra could measure directly.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 4 minor

Summary. The paper proposes a chemically driven classification of Galactic globular clusters (GCs) into in-situ and accreted origins based on the abundances of their 'primordial' populations, defined as the lowest N/3 stars in [Al/Fe] per cluster. Using BACCHUS abundances for 27 GCs, the authors report a clear dichotomy at [Fe/H] > -1.5 with a separation at [Al/Fe] ~ 0.04, and they extend the analysis to 28 GCs from the ASPCAP pipeline. They reclassify NGC 288 and M4 as in-situ and Terzan 9 as accreted, contrasting with several dynamical classifications. The central claim is that the least Al-enhanced stars preserve the chemical fingerprint of the cluster's birth galaxy, enabling a robust, dynamics-free origin determination.

Significance. If the claimed dichotomy is real, the method offers a valuable new probe for Galactic archaeology, allowing GC birth environments to be inferred from abundances alone and bypassing uncertainties in orbital evolution. The paper's core idea—isolating the primordial population to recover the parent galaxy's chemical evolution—is timely and well motivated by the multiple-population problem. The manuscript also makes a useful comparison with existing dynamical classifications and identifies specific discrepant clusters. However, the current evidence is weakened by the circular selection of the classification boundary and by the untested definition of the primordial population, so the significance of the result depends on whether these issues can be resolved with independent validation.

major comments (4)
  1. [Section 3, Figure 1, Section 4.1] The classification boundary at [Al/Fe] = 0.04 is introduced in Figure 1 after the MKH in-situ/accreted labels are displayed, and Section 4.1 states that n = 3 was chosen because it made the [Al/Fe] difference 'most pronounced.' The subsequent 'validation' against MKH therefore risks circularity: the split appears to be tuned to reproduce the labels it is then compared with. Please provide an a priori definition of the boundary, for example from theoretical chemical evolution tracks (e.g., Horta et al. 2021) or from a blind clustering algorithm that does not use the MKH labels, and re-derive the classification and its uncertainties.
  2. [Section 3, Section 4.1] The definition of the primordial population as the lowest N/3 stars in [Al/Fe] assumes (i) that every cluster has a first-generation fraction of at least 1/3 and (ii) that the least Al-enhanced third contains only first-generation stars. Published HST-based studies report first-generation fractions as low as ~0.2–0.3 for some massive clusters; if the true fraction is lower, the 'primordial' mean is biased upward by second-generation stars. The robustness test varying n only shows that n = 3 maximizes the separation, which is a tuning diagnostic, not an independent validation. Please validate the definition against independent first-generation identifications (e.g., the Milone & Marino 2022 catalog) for the overlapping clusters, or demonstrate that the classification is stable under a physically motivated range of n and under alternative definitions of the uncontaminated population.
  3. [Section 4.4, Tables 1–2] The [Al/Fe] = 0.04 threshold from the BACCHUS analysis is applied to the ASPCAP sample without cross-calibration, but the same clusters show systematic offsets between the two abundance scales of roughly 0.15–0.3 dex (e.g., NGC 6752: +0.11 vs -0.11; M4: +0.58 vs +0.29; 47 Tuc: +0.44 vs +0.22). The 'accreted' region on the ASPCAP scale is therefore not the same physical region as on the BACCHUS scale, so the classification and the reclassification of Terzan 9—which relies on 3 primordial stars with an ASPCAP [Al/Fe] of -0.31—are not established. Please derive a separate threshold for the ASPCAP scale using common clusters or propagate the zero-point uncertainty into the classification and state how many clusters change class under this uncertainty.
  4. [Section 4.1 (last paragraph)] The probability argument that all observed stars are enriched uses (1/2)^N, which assumes a primordial fraction of 1/2, while the adopted n = 3 corresponds to a fraction of 1/3. Using (2/3)^N, the probability for the minimum sample size N = 6 is 0.088 rather than 0.0156. The conclusion that the risk is small still holds, but the calculation should be corrected to match the adopted n and should also consider clusters with N between 6 and 10.
minor comments (4)
  1. [Figure 3 caption] The caption appears to mislabel clusters: NGC 6397 is listed as an in-situ GC (blue dotted line), but in Table 1 it falls in the 'cannot identify origin' group with [Fe/H] = -1.88, and 'M86' is not in the sample (likely a typo for M68). Please correct the caption to match the actual classifications and sample.
  2. [Section 2 and Table 2] Several clusters in Table 2 have very large [Fe/H] dispersions (e.g., NGC 6642 sigma = 0.69, NGC 6569 sigma = 0.67, Terzan 5 sigma = 0.47); the paper excludes omega Cen for iron spread but retains these. Please justify their inclusion or discuss the impact of possible iron spreads on the primordial-population means.
  3. [Throughout] The phrase 'bona f ide' in the introduction contains a stray space; it should read 'bona fide'.
  4. [Section 4.2] The term 'hex ratios' is used without a clear definition in the text; please define it explicitly at first use or refer the reader to the exact equation in Horta & Ness (2025).

Circularity Check

3 steps flagged · score 6.0 of 10

The chemical dichotomy is partly constructed: n = 3 and the [Al/Fe] = 0.04 boundary are tuned to the MKH dynamical labels that are then used to 'validate' the classification.

  1. fitted input called prediction [Section 3 (primordial population definition) and Section 4.1 (choice of n)]
    "The primordial population is defined as the first N/n stars... We adopt n = 3 for subsequent analysis and further discuss this choice in Section 4.1. ... Testing values of n = 3, 4, 6, 8 revealed that the [Al/Fe] distinction between in-situ and accreted GCs at [Fe/H] > -1.5 is most pronounced when n = 3 (Figure 1)."

    The very quantity used for classification - the mean primordial [Al/Fe] - depends on n, and n was chosen to maximize the [Al/Fe] separation between the MKH in-situ and accreted samples shown in Figure 1. The reported 'clear dichotomy' is therefore a supervised optimization of the classifier against the dynamical labels, not an independent chemical prediction. Varying n in a robustness test does not validate the choice; it only shows the tuning criterion.

  2. fitted input called prediction [Section 3 (threshold and Figure 1)]
    "At [Fe/H] > -1.5, a clear separation emerges (at [Al/Fe] ~ 0) between in-situ ([Al/Fe] > 0.04 dex) and accreted GCs ([Al/Fe] < 0.04 dex) in the [Al/Fe]-[Fe/H] plane (Figure 1)."

    The boundary [Al/Fe] = 0.04 dex is not derived from a theoretical model or from an independent calibration; it is placed at the gap between the two MKH groups displayed in Figure 1 (in-situ purple, accreted red). The chemical classification is therefore a re-drawing of the MKH dynamical split in abundance space, and the claimed separation is partly an artifact of where the line was drawn.

1 more flagged steps
  1. fitted input called prediction [Section 3 (validation paragraph)]
    "To validate our classification, we compare it with the dynamically driven MKH classification. The agreement is generally good, except for NGC 288 and M4."

    The 'validation' uses the same MKH labels that were used to select n = 3 and to set the 0.04 dex threshold. Agreement with MKH is thus partly by construction, so it cannot serve as independent evidence for the chemical dichotomy. The independent content is limited to the three discrepant clusters and the ASPCAP extension, which are residuals of the tuned classifier rather than out-of-sample predictions.

full rationale

The paper's central claim is a chemical dichotomy between in-situ and accreted GCs at [Fe/H] > -1.5 in primordial [Al/Fe] and [Mg/Fe]. The derivation chain is: define the primordial population as the lowest N/n stars in [Al/Fe]; adopt n = 3 because it makes the MKH-based in-situ/accreted [Al/Fe] separation 'most pronounced'; draw a boundary at [Al/Fe] = 0.04 on a figure showing MKH labels; then state the chemical classification agrees with MKH. The first two steps use the dynamical labels to fix the chemical observable and the cut, so the subsequent agreement is a fitted result rather than a prediction. This is genuine but partial circularity: the three reclassifications (NGC 288, M4, Terzan 9), the Si-based consistency check, and the ASPCAP sample provide some independent content, so the paper does not reduce entirely to its inputs. Concerns about the assumed first-generation fraction and abundance zero-point offsets are correctness risks rather than circularity and are not scored here.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central claim rests on the operational identification of primordial populations, on the comparability of two abundance pipelines, and on the use of MKH dynamical labels to choose the free parameters. These are assumptions inherited from the data or from the construction of the classifier.

free parameters (3)
  • n (number of subpopulations) = 3
    Section 4.1 reports tests of n = 3, 4, 6, 8 and adopts n = 3 because it makes the [Al/Fe] distinction between MKH-defined in-situ and accreted clusters most pronounced.
  • [Al/Fe] classification boundary = 0.04 dex
    Section 3 states a separation at [Al/Fe] about 0, with in-situ > 0.04 and accreted < 0.04; the boundary is drawn by eye from Figure 1, which overlays MKH labels.
  • [Fe/H] metallicity cut = -1.5 dex
    Section 3 restricts classification to [Fe/H] > -1.5 because below this the in-situ and accreted populations overlap; the cut is adopted after inspecting the data.
assumptions (4)
  • domain assumption The lowest N/3 stars in [Al/Fe] within each GC form the primordial population and trace the birth cloud chemistry.
    Section 3 defines the primordial population as the first N/n stars sorted by [Al/Fe]; Section 4.1 explicitly equates this with 'stars not strongly enriched in Al by the polluters responsible for GC MP'. No external validation, such as photometric first-generation selection, is used.
  • domain assumption The abundances from BACCHUS (Meszaros 2020) and ASPCAP (Schiavon 2024) are on a consistent scale so the same [Al/Fe] separation applies to both samples.
    Section 4.4 applies the classification to ASPCAP data with no reported offset calibration; Table 2 shows many in-situ clusters with [Al/Fe] below 0.04, suggesting a scale difference.
  • domain assumption APOGEE target selection is insensitive to multiple populations, so the observed member sample is representative of the GC's primordial/enriched mix.
    Section 4.1 uses this to argue the probability of missing all primordial stars is (1/2)^N; it relies on Zasowski et al. 2017.
  • domain assumption MKH dynamical classification is correct enough to serve as the reference for choosing n and drawing the boundary.
    Section 4.1 tests n to make the [Al/Fe] distinction between MKH-defined in-situ and accreted GCs 'most pronounced'; Section 3 validates against MKH. This makes the dynamical classification an input to the chemical classifier.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Revealing the Origins of Galactic Globular Clusters via Their Mg-Al Abundances." pith.science (2026). https://pith.science/paper/BF6YIAGL

@misc{pith2026250800526,
  author       = {Pith},
  title        = {Pith review of: Revealing the Origins of Galactic Globular Clusters via Their Mg-Al Abundances},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BF6YIAGL}},
  note         = {Machine review of arXiv:2508.00526}
}
read the original abstract

Many Galactic globular clusters (GCs) originated in diverse host galaxies before being subsequently incorporated into the Milky Way through hierarchical galaxy assembly. Identifying their origins is crucial for revealing galaxy properties at early times. Traditional classification methods relying on dynamical properties face inherent uncertainties stemming from the evolving Galactic potential and complex merger histories. Chemically driven classification confronts a distinct obstacle: multiple populations - abundance variations in light elements of GC members. In this Letter, we identify primordial populations exhibiting lower [Al/Fe] as reliable tracers of their birth environments' chemical evolution. A clear chemical dichotomy emerges between in-situ and accreted GC populations at [Fe/H] > -1.5, particularly in the [Mg/Fe]-[Al/Fe] plane, indicating that their progenitor galaxies have experienced fundamentally different enrichment histories. While our chemically driven classification demonstrates general consistency with dynamically driven classifications, notable discrepancies emerge: NGC 288 and M4 are reclassified as in-situ, and Terzan 9 as accreted. This chemically driven GC classification provides promising application for Galactic archaeology.

Figures

Figures reproduced from arXiv: 2508.00526 by the authors.

Figure 1
Figure 1. Mean [Al/Fe] versus mean [Fe/H] of primordial populations in Galactic GCs. Their associated standard deviations are shown as error bars. The black dotted line indicates the metallicity of [Fe/H] = −1.5. GCs with [Fe/H] < −1.5 are not suitable for our chemically based classification (grey region). The black dashed line separates chemically classified in-situ and accreted clusters. In comparison, MKH classification is… view at source ↗
Figure 2
Figure 2. Mean [Mg/Fe] versus mean [Al/Fe] of primor￾dial populations in Galactic GCs. Their associated standard deviations are shown as error bars. Small purple (red) dots represent the in-situ (accreted) GCs based on our classifica￾tion. Filled purple (red) squares mark the in-situ (accreted) GCs based on MKH classification. Two GCs (NGC 288 and M4) with inconsistent classification between the two works are properly labeled… view at source ↗
Figure 3
Figure 3. Our conceptual diagram showing mean [Mg/Fe] versus mean [Al/Fe] of primordial populations in Galactic GCs. The Blue (red) star symbols mark the in-situ (accreted) GCs classified by MKH. The blue (red) arrowed line shows the empirical evolutionary path of in-situ (accreted) GC primordial populations, with increasing metallicity. The Mg-Al (anti-)correlations of in-situ GCs are shown as: blue dotted line - NGC 6397 ([… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Mean [Mg/Fe] versus mean [Al/Fe] of primordial populations in APOGEE GCs. Their associated standard deviations are shown as error bars. Small purple (red) dots represent the in-situ (accreted) GCs based on our classifica￾tion. Filled purple (red) squares mark the in-si…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

43 extracted references · 11 canonical work pages

  1. [1]

    A., Baugh, C

    Beasley, M. A., Baugh, C. M., Forbes, D. A., Sharples, R. M., & Frenk, C. S. 2002, Monthly Notices of the Royal Astronomical Society, 333, 383, doi: 10.1046/j.1365-8711.2002.05402.x

    arXiv 2002

  2. [2]

    2024, MNRAS, 528, 3198, doi: 10.1093/mnras/stad3920

    Belokurov, V., & Kravtsov, A. 2024, MNRAS, 528, 3198, doi: 10.1093/mnras/stad3920

    doi:10.1093/mnras/stad3920 2024

  3. [3]

    L., Fattahi, A., et al

    Belokurov, V., Sanders, J. L., Fattahi, A., et al. 2020, MNRAS, 494, 3880, doi: 10.1093/mnras/staa876

    doi:10.1093/mnras/staa876 2020

  4. [4]

    S., & Vaughan, A

    Bowen, I. S., & Vaughan, A. H., J. 1973, ApOpt, 12, 1430, doi: 10.1364/AO.12.001430

    doi:10.1364/ao.12.001430 1973

  5. [5]

    P., & Strader, J

    Brodie, J. P., & Strader, J. 2006, Annual Review of Astronomy and Astrophysics, 44, 193, doi: 10.1146/annurev.astro.44.051905.092441

    arXiv 2006

  6. [6]

    M., Cautun, M., Deason, A

    Callingham, T. M., Cautun, M., Deason, A. J., et al. 2022, MNRAS, 513, 4107, doi: 10.1093/mnras/stac1145

    doi:10.1093/mnras/stac1145 2022

  7. [7]

    L., Sheffield, A

    Carlin, J. L., Sheffield, A. A., Cunha, K., & Smith, V. V. 2018, ApJL, 859, L10, doi: 10.3847/2041-8213/aac3d8

    doi:10.3847/2041-8213/aac3d8 2018

  8. [8]

    G., et al

    Carretta, E., Bragaglia, A., Gratton, R. G., et al. 2009, A&A, 505, 117, doi: 10.1051/0004-6361/200912096

    doi:10.1051/0004-6361/200912096 2009

Show all 43 references
  1. [9]

    2025, arXiv, doi: 10.48550/arXiv.2503.02939

    Ceccarelli, E., Massari, D., Aguado-Agelet, F., et al. 2025, arXiv, doi: 10.48550/arXiv.2503.02939

    2025 doi arXiv

  2. [10]

    Chen, Y., & Gnedin, O. Y. 2024, The Open Journal of Astrophysics, 7, doi: 10.33232/001c.116169

    2024 doi

  3. [11]

    2020, MNRAS, 493, 5195, doi: 10.1093/mnras/stz3537 Fern´ andez-Trincado, J

    Das, P., Hawkins, K., & Jofr´ e, P. 2020, MNRAS, 493, 5195, doi: 10.1093/mnras/stz3537 Fern´ andez-Trincado, J. G., Minniti, D., Souza, S. O., et al. 2021, ApJL, 908, L42, doi: 10.3847/2041-8213/abdf47

    2020 doi

  4. [12]

    A., & Bridges, T

    Forbes, D. A., & Bridges, T. 2010, MNRAS, 404, 1203, doi: 10.1111/j.1365-2966.2010.16373.x

    2010

  5. [13]

    R., Minniti, D., G´ omez, M., et al

    Garro, E. R., Minniti, D., G´ omez, M., et al. 2022, A&A, 658, A120, doi: 10.1051/0004-6361/202141819 8 T able 1.Globular Clusters selected from S. M´ esz´ aros et al. (2020) GC name sample size a [Fe/H]b prim σc F e [Al/Fe]b prim σc Al [Mg/Fe]b prim σc Mg MKH classification G...

    2020 doi

  6. [14]

    E., et al

    Geisler, D., Villanova, S., O’Connell, J. E., et al. 2021, Astronomy & Astrophysics, 652, A157, doi: 10.1051/0004-6361/202140436

    2021 doi

  7. [15]

    E., Siegmund, W

    Gunn, J. E., Siegmund, W. A., Mannery, E. J., et al. 2006, AJ, 131, 2332, doi: 10.1086/500975

    2006 doi

  8. [16]

    2015, Mon

    Hawkins, K., Jofr´ e, P., Masseron, T., & Gilmore, G. 2015, Mon. Not. R. Astron. Soc., 453, 758, doi: 10.1093/mnras/stv1586

    2015 doi

  9. [17]

    Horta, D., & Ness, M. K. 2025, arXiv e-prints, arXiv:2506.08079, doi: 10.48550/arXiv.2506.08079

    2025 doi arXiv

  10. [18]

    P., Mackereth, J

    Horta, D., Schiavon, R. P., Mackereth, J. T., et al. 2020, MNRAS, 493, 3363, doi: 10.1093/mnras/staa478

    2020 doi

  11. [19]

    P., Mackereth, J

    Horta, D., Schiavon, R. P., Mackereth, J. T., et al. 2021, MNRAS, 500, 1385, doi: 10.1093/mnras/staa2987

    2021 doi

  12. [20]

    2024, Science China

    Huang, R., Tang, B., Li, C., et al. 2024, Science China

    2024

  13. [21]

    Physics, Mechanics, and Astronomy, 67, 259513, doi: 10.1007/s11433-023-2332-5

    doi

  14. [22]

    A., Gilmore, G., & Irwin, M

    Ibata, R. A., Gilmore, G., & Irwin, M. J. 1994, Nature, 370, 194, doi: 10.1038/370194a0 9 T able 2.GCs selected from ASPCAP GC name sample size a [Fe/H]b prim σc F e [Al/Fe]b prim σc Al [Mg/Fe]b prim σc Mg MKH classification accreted GCs M3 261(87) -1.48 0.11 -0.32 0.04 0.16 0...

    1994 doi arXiv

  15. [23]

    2006, ApJ, 653, 1145, doi: 10.1086/508914

    Ohkubo, T. 2006, ApJ, 653, 1145, doi: 10.1086/508914

    2006 doi

  16. [24]

    Krause, M. G. H., Charbonnel, C., Bastian, N., & Diehl, R. 2016, A&A, 587, A53, doi: 10.1051/0004-6361/201526685

    2016 doi

  17. [25]

    R., & Majewski, S

    Law, D. R., & Majewski, S. R. 2010, ApJ, 718, 1128, doi: 10.1088/0004-637X/718/2/1128

    2010 doi

  18. [26]

    R., Schiavon, R

    Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94, doi: 10.3847/1538-3881/aa784d

    2017 doi

  19. [27]

    C., Schiavon, R

    Mason, A. C., Schiavon, R. P., Kamann, S., et al. 2025, arXiv e-prints, arXiv:2504.06341, doi: 10.48550/arXiv.2504.06341

    2025 doi

  20. [28]

    H., & Helmi, A

    Massari, D., Koppelman, H. H., & Helmi, A. 2019, A&A, 630, L4, doi: 10.1051/0004-6361/201936135 10

    2019 doi

  21. [29]

    2016, http://ascl.net/1605.004

    Masseron, T., Merle, T., & Hawkins, K. 2016, http://ascl.net/1605.004

    2016

  22. [30]

    2013, ApJ, 778, 149, doi: 10.1088/0004-637X/778/2/149

    McWilliam, A., Wallerstein, G., & Mottini, M. 2013, ApJ, 778, 149, doi: 10.1088/0004-637X/778/2/149

    2013 doi

  23. [31]

    P., & Marino, A

    Milone, A. P., & Marino, A. F. 2022, Universe, 8, 359, doi: 10.3390/universe8070359

    2022 doi

  24. [32]

    2017, ApJL, 849, L24, doi: 10.3847/2041-8213/aa95b8 M´ esz´ aros, S., Masseron, T., Garc ´ ıa-Hern´ andez, D

    Minniti, D., Geisler, D., Alonso-Garc ´ ıa, J., et al. 2017, ApJL, 849, L24, doi: 10.3847/2041-8213/aa95b8 M´ esz´ aros, S., Masseron, T., Garc ´ ıa-Hern´ andez, D. A., et al. 2020, MNRAS, 492, 1641, doi: 10.1093/mnras/stz3496

    2017 doi

  25. [33]

    L., Holtzman, J

    Nidever, D. L., Holtzman, J. A., Allende Prieto, C., et al. 2015, AJ, 150, 173, doi: 10.1088/0004-6256/150/6/173

    2015 doi

  26. [34]

    1999, Astronomy and Astrophysics Supplement Series, 138, 267, doi: 10.1051/aas:1999275

    Ortolani, S., Bica, E., & Barbuy, B. 1999, Astronomy and Astrophysics Supplement Series, 138, 267, doi: 10.1051/aas:1999275

    1999 doi

  27. [35]

    2023, A&A, 673, A86, doi: 10.1051/0004-6361/202245128

    Pagnini, G., Di Matteo, P., Khoperskov, S., et al. 2023, A&A, 673, A86, doi: 10.1051/0004-6361/202245128

    2023 doi

  28. [36]

    2017, A&A, 601, A112, doi: 10.1051/0004-6361/201730474

    Pancino, E., Romano, D., Tang, B., et al. 2017, A&A, 601, A112, doi: 10.1051/0004-6361/201730474

    2017 doi

  29. [37]

    P., Phillips, S

    Schiavon, R. P., Phillips, S. G., Myers, N., et al. 2024, MNRAS, 528, 1393, doi: 10.1093/mnras/stad3020

    2024 doi

  30. [38]

    2023, A&A, 669, A125, doi: 10.1051/0004-6361/202244052

    Tang, B., Zhang, J., Yan, Z., et al. 2023, A&A, 669, A125, doi: 10.1051/0004-6361/202244052

    2023 doi

  31. [39]

    E., Geisler, D., et al

    Tang, B., Cohen, R. E., Geisler, D., et al. 2017, MNRAS, 465, 19, doi: 10.1093/mnras/stw2739

    2017 doi

  32. [40]

    G., Geisler, D., et al

    Tang, B., Fern´ andez-Trincado, J. G., Geisler, D., et al. 2018, ApJ, 855, 38, doi: 10.3847/1538-4357/aaaaea

    2018 doi

  33. [41]

    Unavane, M., Wyse, R. F. G., & Gilmore, G. 1996, MNRAS, 278, 727, doi: 10.1093/mnras/278.3.727

    1996 doi

  34. [42]

    2022, Nature, 603, 599, doi: 10.1038/s41586-022-04496-5

    Xiang, M., & Rix, H.-W. 2022, Nature, 603, 599, doi: 10.1038/s41586-022-04496-5

    2022 doi

  35. [43]

    E., Chojnowski, S

    Zasowski, G., Cohen, R. E., Chojnowski, S. D., et al. 2017, AJ, 154, 198, doi: 10.3847/1538-3881/aa8df9

    2017 doi

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.