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Adding young open clusters to the Milky Way's abundance map leaves the radial iron gradient essentially flat, at about -0.08 dex/kpc, across all cluster ages.

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2026-08-03 15:05 UTC pith:L5GDEWC7

load-bearing objection Useful, honest catalog paper, but the no-evolution claim rests on cluster ages the paper itself suggests are unreliable. the 2 major comments →

arxiv 2607.29023 v1 pith:L5GDEWC7 submitted 2026-07-31 astro-ph.GA astro-ph.SR

The Open Cluster Chemical Abundances and Mapping Survey XI. First Gradients from SDSS/MWM BOSS Determined Clusters

Jonah M. Otto , Peter M. Frinchaboy , John Donor , Ilija Medan , Natalie R. Myers , Audrey Hauck , Katia Cunha , Gail Zasowski
show 8 more authors
Madeleine McKenzie Jingkun Zhao Jose Eduardo Mendez-Delgado Amaya Sinha Zachary Way Dmitry Bizyaev Andrew R. Casey Jose G. Fernandez-Trincado
This is my paper
classification astro-ph.GA astro-ph.SR
keywords open clustersmetallicity gradientMilky Way diskBOSS spectroscopymono-age populationschemical abundancesGalactic archaeologyradial migration
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

This paper attempts to establish that the Milky Way's radial iron gradient is the same for open clusters of every age, not steeper or shallower for young or old clusters. It does so by adding 95 open clusters observed in low-resolution optical spectroscopy to the existing infrared-based cluster sample, giving 253 clusters from 6 to 16 kpc. The combined sample yields a linear gradient of -0.079 to -0.082 dex/kpc depending on the radial coordinate, and the five mono-age bins have gradients consistent with that global value in four out of five bins. The one exception, the 150-400 Myr bin, is treated as a fluctuation rather than evidence of evolution. The reason to care: if the gradient is truly static, the disk's interstellar medium must reach chemical equilibrium at each radius on timescales shorter than the cluster age spread, and radial migration is not strongly reshaping the gradient.

Core claim

The paper builds a new catalog of open-cluster members from low-resolution optical spectra (BOSS) and combines it with the previous infrared-based (APOGEE) sample to measure the Milky Way's radial iron gradient. Across 253 clusters spanning 6–16 kpc, it finds a linear gradient of -0.079±0.005 dex/kpc in guiding-center radius (and -0.082±0.006 dex/kpc in Galactocentric radius), and when the sample is split into five mono-age populations, the gradients are consistent with this global value in four of five bins. The single exception, the 150–400 Myr bin, is shallower, but the paper argues the overall pattern favors a scenario in which the interstellar medium reaches local chemical equilibrium q

What carries the argument

Open clusters are used as coeval, chemically homogeneous tracers: each cluster's bulk [Fe/H] is the average of ≥3 member stars, membership being established by a combination of Gaia astrometric probabilities, radial velocity, and metallicity. Ages and distances come from an adopted isochrone catalog; orbital radii are computed with a Galactic dynamics code, and guiding-center radius (the radius of a circular orbit with the same angular momentum as the cluster's real orbit) is the primary radial coordinate because it partially corrects for radial migration. The [Fe/H]-versus-radius fits are performed with a Markov Chain Monte Carlo linear regression.

Load-bearing premise

The mono-age analysis assumes the adopted isochrone ages and distances are accurate; the paper itself notes that 124 of 158 APOGEE clusters have isochrone [Fe/H] differing from spectroscopic values by more than 0.1 dex, so an age error will reassign clusters between bins and break the age-gradient test.

What would settle it

Recompute the five age-binned gradients after replacing the adopted cluster ages with independent ages from Gaia parallax main-sequence fitting, and restrict the youngest bin to stars without chromospheric activity flags; if the spread across bins widens beyond the current uncertainties, the static-gradient claim fails.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • If the gradient is age-independent, the interstellar medium at a given Galactic radius reaches a quasi-equilibrium abundance quickly, so chemical evolution models should not require the gradient to steepen with time.
  • The new young clusters reproduce the APOGEE-only gradient, meaning the young and old cluster populations trace the same present-day radial abundance pattern; the 150–400 Myr bin is the only divergence.
  • Young open clusters yield a steeper gradient than classical cepheids and H II regions; if the flat-gradient result is right, this discrepancy points to age or distance errors in the cluster sample rather than real evolution.
  • The public catalog of 1883 member stars with chemistry and membership probabilities provides a new benchmark for calibrating low-resolution abundance pipelines.

Where Pith is reading between the lines

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

  • A decisive test would re-derive the mono-age gradients using independent ages (e.g., from Gaia parallax turn-off fitting) for the 95 new clusters; if the age bins reshuffle, the static-gradient conclusion may not survive.
  • The shallow 150–400 Myr bin could be a selection artifact: those clusters may be biased toward wide, low-mass systems that migrated from different radii; comparing their orbital eccentricities to other bins would check this.
  • If the equilibrium scenario is correct, high-resolution spectroscopy of the youngest clusters (10–150 Myr) should show the same slope even after excluding chromospherically active stars; a steeper slope there would falsify the scenario.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 5 minor

Summary. This OCCAM survey paper presents the first open cluster catalog based on SDSS-V/MWM DR20 BOSS optical spectroscopy, comprising 1883 member stars in 111 clusters, 95 of which are new relative to the APOGEE-based DR19 OCCAM sample. The authors combine the BOSS sample with the APOGEE OCCAM sample (253 clusters total) to measure the radial [Fe/H] gradient: -0.079±0.005 dex/kpc in R_Guide and -0.082±0.006 dex/kpc in R_GC, consistent with previous APOGEE-only results. They also split the sample into five mono-age bins and report that the gradient is 'mostly constant' across age, favoring the equilibrium scenario of Johnson et al. (2025). The paper includes comparisons to Cepheid and H II region gradients and releases the catalogs as a DR20 Value Added Catalog.

Significance. If the mono-age gradient conclusion is robust, this is an important result: it substantially extends the age baseline of open-cluster gradient studies and provides the first BOSS-based OCCAM catalog, filling a young-cluster gap. The paper is transparent about its methods, releases machine-readable catalogs and a VAC, and the global gradient agrees well with independent high-resolution work (Spina et al. 2021). However, the central mono-age claim rests on external cluster ages whose reliability the paper itself calls into question, so the significance of the evolutionary conclusion is currently conditional. The catalog itself is a valuable community resource regardless of the interpretation.

major comments (2)
  1. [§6.4, §6.3.2, §7] The central claim of a constant gradient across mono-age populations depends entirely on assigning clusters to the five age bins using L. Cavallo et al. (2024) ages. The paper itself reports in §6.4 that for the 158 APOGEE OCCAM clusters, 124 have isochrone [Fe/H] values differing from spectroscopic values by >0.1 dex and 80 by >0.25 dex, and states that 'such a large discrepancy between the metallicity of the cluster can alter the isochrone-derived ages.' The 95 new BOSS clusters, which dominate the young age bins, are never subjected to a similar validation. The paper's own comparison in §6.3.2 shows that young open clusters give a steeper gradient than Cepheids and H II regions, and the text admits this 'could be the case if the cluster ages are incorrect.' These caveats directly undermine the age binning used in Figure 5 and Table 4. To support the equilibrium-scenario conclusion, th
  2. [§5.3.1, Table 4] The claim of 'no significant evolution' is supported only by a per-bin inspection: four of five age bins are consistent with the overall gradient, while the 150–400 Myr bin gives -0.052±0.012 dex/kpc in R_Guide, about 2σ away from the overall -0.079±0.005. No formal consistency test (e.g., chi-square of the five slopes or a fit with a time-dependent slope) is reported. Given that the age bins have quite different sample sizes and radius coverage, a quantitative test is needed to distinguish a genuinely static gradient from a dataset that simply lacks statistical power. Please add such a test or explicitly quantify the evidence against gradient evolution.
minor comments (5)
  1. [Appendix A] The sentence 'shown in Figures )' is incomplete; the figure numbers are missing.
  2. [Table 4] The age-bin column headers (e.g., '0.01<Age≤0.15') should explicitly state the units (Gyr) in the table caption, since the text switches between Myr and Gyr.
  3. [§3] The membership threshold of 14% in all three criteria is stated without justification. A brief justification or reference to the Donor et al. (2018) routine would help readers assess the robustness of the cluster parameters.
  4. [§6.2.1] The phrase 'median offset of 0.04±0.08 dex kpc−1' for the 13 common clusters likely should be 'dex', since it is an abundance offset, not a gradient. Please clarify.
  5. [Figure 1] The histograms above the scatter plots are not axis-labeled; adding 'Count' and '[Fe/H]' would improve readability.

Circularity Check

0 steps flagged

No significant circularity: the gradients are empirical fits to independent data, and the mono-age caveats concern age accuracy, not a derivation that reduces to its own inputs.

full rationale

The central result—a radial [Fe/H] gradient of about −0.079 to −0.082 dex/kpc and its constancy across mono-age bins—is obtained by direct linear fits (emcee/MLE) of cluster [Fe/H] against R_guide and R_gc. No fitted parameter is renamed as a prediction: the overall gradient, the five mono-age gradients, and the cepheid/H II region comparisons are separate fits to separate data subsets. The BOSS-CLAM abundances are validated against APOGEE overlap clusters and an Appendix correction is tested, but these are consistency checks; the gradient conclusion does not assume the gradient result. The mono-age conclusion does depend on the Cavallo et al. (2024) ages, and the paper itself flags the risk: '124 have differences larger than 0.1 dex' between isochrone and spectroscopic [Fe/H] and 'could be the case if the cluster ages are incorrect.' That is a validity/robustness caveat, not circularity, because age misassignment would undermine the interpretation rather than tautologically confirm it. Self-citations to J. M. Otto et al. (2026) are used for comparison and for the choice of a linear over bilinear fit; that modeling choice is a mild same-group prior but is not load-bearing, and the gradient agrees with the external L. Spina et al. (2021) result. No uniqueness theorem, ansatz, or definitional equivalence is invoked to force the conclusion. Score 1 reflects one minor non-load-bearing self-citation for the linear-fit choice, not substantive circularity.

Axiom & Free-Parameter Ledger

3 free parameters · 6 axioms · 0 invented entities

The central gradient measurement rests on standard assumptions about the fidelity of the BOSS-CLAM abundance pipeline and the Gaia-based membership catalog. The most fragile input is the Cavallo et al. (2024) cluster ages/distances, which the paper itself shows are inconsistent with spectroscopic metallicities for a large fraction of APOGEE clusters. The analysis also includes a hand-fit correction that was tested and set aside, and a hand-chosen membership threshold; neither is a derived entity, but both affect the results.

free parameters (3)
  • Post-hoc [Fe/H] quadratic correction coefficients = a=-0.87, b=0.32, c=-0.03
    Fitted to the 16 BOSS-APOGEE overlap clusters in Appendix A to correct the metallicity-dependent offset; not used in the final gradients, but represents a fitted systematic model for the BOSS abundances.
  • Mono-age bin boundaries = 0.01-0.15, 0.15-0.4, 0.4-0.8, 0.8-2.0, >2.0 Gyr
    The division into five age groups is chosen by hand; the no-evolution conclusion depends on this binning. Splitting the youngest population differently could change the derived age-group gradients.
  • Membership probability threshold = >14% in each of three criteria
    Chosen to balance sample size and contamination; the paper notes low-resolution data make membership harder, so this threshold is an analysis choice that affects which stars enter the bulk cluster parameters.
axioms (6)
  • domain assumption BOSS-CLAM v1.0.0 stellar parameters are accurate for open cluster members, including the [Fe/H] and [α/M] labels.
    Used throughout; the BOSS-CLAM method is described in a submitted companion paper (Medan et al.), and the authors rely on its validation.
  • domain assumption The Hunt & Reffert (2024) Gaia-based cluster membership catalog correctly identifies member stars.
    Membership probabilities and cluster radii are adopted from this catalog (Section 2.2); if membership is wrong, the cluster abundance and the gradients change.
  • domain assumption Cluster ages and distances from Cavallo et al. (2024) are reliable enough to split the sample into mono-age populations.
    Used for the age bins and for R_guide/R_gc; the paper shows large discrepancies between isochrone and spectroscopic [Fe/H] for many APOGEE clusters, which could bias the ages.
  • domain assumption BOSS and APOGEE abundance scales can be combined without applying an offset correction.
    Section 2.3 reports a median offset of -0.045 dex in [Fe/H] and a metallicity-dependent trend; the authors choose not to correct for it, which affects the combined sample fit.
  • domain assumption The gala Milky Way potential model is accurate enough to compute guiding-center radii.
    Orbital parameters and R_guide are computed with gala (Section 3); the gradient in R_guide depends on this potential.
  • domain assumption The linear model (single-slope fit) is the correct description of the radial metallicity gradient over 6-18 kpc.
    The paper follows Otto et al. (2026) in preferring linear over bilinear; if there is a break beyond 10 kpc, the comparison with cepheids in Section 6.3.1 could be affected.

pith-pipeline@v1.3.0-daily-deepseek · 21807 in / 13439 out tokens · 118853 ms · 2026-08-03T15:05:58.792130+00:00 · methodology

0 comments
read the original abstract

The Milky Way Mapper program in the fifth generation of the Sloan Digital Sky Survey (SDSS-V/MWM) has observed millions of stars, thousands of them in open clusters. The Open Cluster Chemical Abundances and Mapping (OCCAM) survey continues to create comprehensive datasets of open clusters and their members in order to constrain Galactic parameters. This eleventh contribution from the OCCAM survey is the first to use stellar parameters from stars observed with the optical Baryon Oscillation Spectroscopic Survey (BOSS) spectrograph to determine cluster membership. We use data from SDSS-V/MWM's 20th Data Release (DR20) and curate a sample of 1883 stars in 111 open clusters, including 95 not in previous OCCAM samples based on infrared data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectrograph. The sample includes 16 clusters with stars observed using both the BOSS and APOGEE spectrographs, and we find consistent agreement in measurements of both [Fe/H] and [$\alpha/M$]. The BOSS sample includes the majority of the clusters at young ages (Age $< 150$ Myr) that complement the APOGEE sample of primarily older clusters. We use the combined BOSS+APOGEE OCCAM sample to constrain the radial metallicity gradient with respect to $R_{guide}$ ($-0.079 \pm 0.005 \text{ dex kpc}^{-1}$) and $R_{gc}$ ($-0.082 \pm 0.006 \text{ dex kpc}^{-1}$), which agree well with results from previous OCCAM papers using only APOGEE data. Finally, the inclusion of the primarily young BOSS clusters has not changed that the OCCAM open cluster sample indicates no significant evolution of this gradient in different mono-age populations.

Figures

Figures reproduced from arXiv: 2607.29023 by Amaya Sinha, Andrew R. Casey, Audrey Hauck, Dmitry Bizyaev, Gail Zasowski, Ilija Medan, Jingkun Zhao, John Donor, Jonah M. Otto, Jose Eduardo Mendez-Delgado, Jose G. Fernandez-Trincado, Katia Cunha, Madeleine McKenzie, Natalie R. Myers, Peter M. Frinchaboy, Zachary Way.

Figure 1
Figure 1. Figure 1: The DR20 BOSS minus DR19 APOGEE delta plot for [Fe/H] (top scatter plot) and ([α/M] (bottom scatter plot) using the 16 clusters that are in both catalogs. Points are colored by the number of stars in the cluster in the DR20 OCCAM catalog. The grey dashed line shows the zero point and the solid blue line shows the median offset. The [Fe/H] distribution of the entire DR20 OCCAM sample is shown above the scat… view at source ↗
Figure 2
Figure 2. Figure 2: The BOSS OCCAM DR20 Solar neighborhood clusters plotted in the Galactic plane with the dust map from G. Edenhofer et al. (2024). Clusters are colored by log(age(yr)) and the dust map color bar saturates at a value of 1.75. The Sun is depicted as a yellow star at (0,0) [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: The radial iron gradient with respect to both Galactocentric radius (top) and guiding center radius (bottom), using the combined cluster catalog, is represented by the pink dot-dashed line. Clusters with APOGEE DR19 measurements are shown as orange pentagons, and clusters with BOSS DR20 measurements are depicted as blue triangles. Representative error bars for each data set in the top right. (2026). We fou… view at source ↗
Figure 4
Figure 4. Figure 4: The [α/M] vs RGuide radial gradient shown in the pink dot-dashed line. As in 3, blue triangles are clusters with BOSS data and orange pentagons are clusters with APOGEE data [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: The radial Galactic [Fe/H] gradient for 5 age groups, (a) 0.01 ≤ age ≤ 0.15 Gyr, (b) 0.15 ≤ age ≤ 0.4 Gyr, (c) 0.4 ≤ age ≤ 0.8 Gyr, (d) 0.8 ≤ age ≤ 2.0 Gyr, and (e) age > 2 Gyr. Blue triangles are clusters with BOSS data, orange pentagons are clusters with APOGEE data and the overall gradient is shown with the pink dot-dashed line. with ages less than 500 Myr, does not significantly alter the radial metall… view at source ↗
Figure 7
Figure 7. Figure 7: The CCs (black stars) from A. Nunnari et al. (2026) and young open clusters (blue triangles and orange pentagons) over-plotted with their respective radial gradi￾ents. The pink dot-dashed line shows the gradient from the young open-clusters, while the green dotted line is the gra￾dient calculated from the CCs. 6.3.2. H II Regions H II regions are an excellent probe of the current abun￾dance gradient of the… view at source ↗
Figure 8
Figure 8. Figure 8: The DR20 BOSS minus DR19 APOGEE delta plot for [Fe/H] using the corrected DR20 [Fe/H] abundances for the 16 overlap clusters. Points are colored by the number of stars in the cluster in the DR20 OCCAM catalog. The grey dashed line shows the zero point and the solid blue line shows the median offset. The [Fe/H] distribution of the entire corrected DR20 OCCAM sample is shown above the scatter plot. Deng, L.-… view at source ↗
Figure 9
Figure 9. Figure 9: Same as [PITH_FULL_IMAGE:figures/full_fig_p017_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Same as [PITH_FULL_IMAGE:figures/full_fig_p018_10.png] view at source ↗

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Works this paper leans on

62 extracted references · 6 canonical work pages · 1 internal anchor

  1. [1]

    M., et al

    Afflerbach, A., Churchwell, E., Acord, J. M., et al. 1996, ApJS, 106, 423, doi: 10.1086/192343 Allende Prieto, C., Beers, T. C., Wilhelm, R., et al. 2006, ApJ, 636, 804, doi: 10.1086/498131

    work page doi:10.1086/192343 1996

  2. [2]

    F., Argudo-Fern´ andez, M., et al

    Almeida, A., Anderson, S. F., Argudo-Fern´ andez, M., et al. 2023, ApJS, 267, 44, doi: 10.3847/1538-4365/acda98 Arellano-C´ ordova, K. Z., Esteban, C., Garc ´ ıa-Rojas, J., & M´ endez-Delgado, J. E. 2020, MNRAS, 496, 1051, doi: 10.1093/mnras/staa1523 Arellano-C´ ordova, K. Z., Esteban, C., Garc ´ ıa-Rojas, J., & M´ endez-Delgado, J. E. 2021, MNRAS, 502, 2...

    doi:10.3847/1538-4365/acda98 2023

  3. [3]

    R., Ness, M

    Bhattarai, B., Loebman, S. R., Ness, M. K., et al. 2024, ApJ, 977, 70, doi: 10.3847/1538-4357/ad8bac

    doi:10.3847/1538-4357/ad8bac 2024

  4. [4]

    S., Schlegel, D

    Bolton, A. S., Schlegel, D. J., Aubourg, ´E., et al. 2012, AJ, 144, 144, doi: 10.1088/0004-6256/144/5/144

    doi:10.1088/0004-6256/144/5/144 2012

  5. [5]

    F., & Pietrinferni, A

    Bono, G., Braga, V. F., & Pietrinferni, A. 2024, A&A Rv, 32, 4, doi: 10.1007/s00159-024-00153-0

    doi:10.1007/s00159-024-00153-0 2024

  6. [6]

    2016, ApJ, 817, 49, doi: 10.3847/0004-637X/817/1/49

    Bovy, J. 2016, ApJ, 817, 49, doi: 10.3847/0004-637X/817/1/49

    doi:10.3847/0004-637x/817/1/49 2016

  7. [7]

    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

  8. [8]

    2018, A&A, 618, A93, doi: 10.1051/0004-6361/201833476

    Cantat-Gaudin, T., Jordi, C., Vallenari, A., et al. 2018, A&A, 618, A93, doi: 10.1051/0004-6361/201833476

    doi:10.1051/0004-6361/201833476 2018

  9. [9]

    2020, A&A, 640, A1, doi: 10.1051/0004-6361/202038192

    Cantat-Gaudin, T., Anders, F., Castro-Ginard, A., et al. 2020, A&A, 640, A1, doi: 10.1051/0004-6361/202038192

    doi:10.1051/0004-6361/202038192 2020

  10. [10]

    2024, A&A, 687, A239, doi: 10.1051/0004-6361/202347648

    Carbajo-Hijarrubia, J., Casamiquela, L., Carrera, R., et al. 2024, A&A, 687, A239, doi: 10.1051/0004-6361/202347648

    doi:10.1051/0004-6361/202347648 2024

  11. [11]

    R., Wheeler, A., Bedell, M., et al

    Casey, A. R., Wheeler, A., Bedell, M., et al. 2026, ApJ, 998, 192, doi: 10.3847/1538-4357/ae3bd6

    doi:10.3847/1538-4357/ae3bd6 2026

  12. [12]

    2024, AJ, 167, 12, doi: 10.3847/1538-3881/ad07e5

    Cavallo, L., Spina, L., Carraro, G., et al. 2024, AJ, 167, 12, doi: 10.3847/1538-3881/ad07e5

    doi:10.3847/1538-3881/ad07e5 2024

  13. [13]

    A., Ji, A

    Chandra, V., Cargile, P. A., Ji, A. P., et al. 2026, The Astrophysical Journal, 1000, 283, doi: 10.3847/1538-4357/ae448a

    doi:10.3847/1538-4357/ae448a 2026

  14. [14]

    M., Souto, D., et al

    Cunha, K., Frinchaboy, P. M., Souto, D., et al. 2016, Astronomische Nachrichten, 337, 922, doi: 10.1002/asna.201612398

    doi:10.1002/asna.201612398 2016

  15. [15]

    S., Schlegel, D

    Dawson, K. S., Schlegel, D. J., Ahn, C. P., et al. 2013, AJ, 145, 10, doi: 10.1088/0004-6256/145/1/10 De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, 2604, doi: 10.1093/mnras/stv327 16 0 10 20 30 40Count 0.2 0.1 0.0 0.1 0.2 0.3 BOSS [Fe/H] 0.15 0.10 0.05 0.00 0.05 0.10 0.15 (BOSS - APOGEE) (dex) median offset: +0.003 ± 0.053[...

    doi:10.1088/0004-6256/145/1/10 2013

  16. [16]

    J., Liu, C., et al

    Deng, L.-C., Newberg, H. J., Liu, C., et al. 2012, Research in Astronomy and Astrophysics, 12, 735, doi: 10.1088/1674-4527/12/7/003

    doi:10.1088/1674-4527/12/7/003 2012

  17. [17]

    M., Cunha, K., et al

    Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2018, AJ, 156, 142, doi: 10.3847/1538-3881/aad635

    doi:10.3847/1538-3881/aad635 2018

  18. [18]

    M., Cunha, K., et al

    Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2020, AJ, 159, 199, doi: 10.3847/1538-3881/ab77bc

    doi:10.3847/1538-3881/ab77bc 2020

  19. [19]

    2024, A&A, 685, A82, doi: 10.1051/0004-6361/202347628

    Edenhofer, G., Zucker, C., Frank, P., et al. 2024, A&A, 685, A82, doi: 10.1051/0004-6361/202347628

    doi:10.1051/0004-6361/202347628 2024

  20. [20]

    El-Badry, K., Rix, H.-W., & Heintz, T. M. 2021, MNRAS, 506, 2269, doi: 10.1093/mnras/stab323 Fern´ andez-Mart ´ ın, A., P´ erez-Montero, E., V ´ ılchez, J. M., &

    doi:10.1093/mnras/stab323 2021

  21. [21]

    2017, A&A, 597, A84, doi: 10.1051/0004-6361/201628423

    Mampaso, A. 2017, A&A, 597, A84, doi: 10.1051/0004-6361/201628423

    doi:10.1051/0004-6361/201628423 2017

  22. [22]

    W., Lang, D., & Goodman, J

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067

    doi:10.1086/670067 2013

  23. [23]

    Friel, E. D. 1995, ARA&A, 33, 381, doi: 10.1146/annurev.aa.33.090195.002121

    arXiv 1995

  24. [24]

    M., Thompson, B., Jackson, K

    Frinchaboy, P. M., Thompson, B., Jackson, K. M., et al. 2013, ApJL, 777, L1, doi: 10.1088/2041-8205/777/1/L1 Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1, doi: 10.1051/0004-6361/202243940 Garc ´ ıa P´ erez, A. ...

    doi:10.1088/2041-8205/777/1/l1 2013

  25. [25]

    2012, The Messenger, 147, 25

    Gilmore, G., Randich, S., Asplund, M., et al. 2012, The Messenger, 147, 25

    2012

  26. [26]

    Open cluster members in APOGEE DR17 I. Dynamics and star members

    Green, G. 2018, The Journal of Open Source Software, 3, 695, doi: 10.21105/joss.00695 Guer¸ co, R., Souto, D., Fern´ andez-Trincado, J. G., et al. 2025, arXiv e-prints, arXiv:2506.19936, doi: 10.48550/arXiv.2506.19936

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2506.19936 2018

  27. [27]

    2009, A&A, 504, 829, doi: 10.1051/0004-6361/200811313

    Guillout, P., Klutsch, A., Frasca, A., et al. 2009, A&A, 504, 829, doi: 10.1051/0004-6361/200811313

    work page doi:10.1051/0004-6361/200811313 2009

  28. [28]

    E., Siegmund, W

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

    doi:10.1086/500975 2006

  29. [29]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    doi:10.1038/s41586-020-2649-2 2020

  30. [30]

    L., & Reffert, S

    Hunt, E. L., & Reffert, S. 2023, A&A, 673, A114, doi: 10.1051/0004-6361/202346285

    doi:10.1051/0004-6361/202346285 2023

  31. [31]

    L., & Reffert, S

    Hunt, E. L., & Reffert, S. 2024, Astronomy and Astrophysics, 686, doi: 10.1051/0004-6361/202348662

    doi:10.1051/0004-6361/202348662 2024

  32. [32]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    doi:10.1109/mcse.2007.55 2007

  33. [33]

    Janes, K. A. 1979, ApJS, 39, 135, doi: 10.1086/190568

    doi:10.1086/190568 1979

  34. [34]

    W., Weinberg, D

    Johnson, J. W., Weinberg, D. H., Blanc, G. A., et al. 2025, ApJ, 988, 8, doi: 10.3847/1538-4357/addbe5 17 0.4 0.2 0.0 0.2 0.4 [Fe/H] (a) BOSS DR20 APOGEE DR19 Cav RGC -0.085±0.006 dex/kpc N=253 6 8 10 12 14 16 18 R (kpc) 0.4 0.2 0.0 0.2 0.4 [Fe/H] (b) RGuide -0.080±0.005 dex/kpc N=253 Figure 9.Same as Figure 3 but with the calibrated DR20 [Fe/H] abundances

    doi:10.3847/1538-4357/addbe5 2025

  35. [35]

    A., Rix, H.-W., Aerts, C., et al

    Kollmeier, J. A., Rix, H.-W., Aerts, C., et al. 2026, AJ, 171, 52, doi: 10.3847/1538-3881/ae0576

    doi:10.3847/1538-3881/ae0576 2026

  36. [36]

    A., Andrievsky, S

    Korotin, S. A., Andrievsky, S. M., Luck, R. E., et al. 2014, MNRAS, 444, 3301, doi: 10.1093/mnras/stu1643

    work page doi:10.1093/mnras/stu1643 2014

  37. [37]

    L., et al

    Kos, J., Buder, S., Beeson, K. L., et al. 2025, A&A, 703, A104, doi: 10.1051/0004-6361/202554112

    doi:10.1051/0004-6361/202554112 2025

  38. [38]

    G., Bouma, L

    Kounkel, M., Stassun, K. G., Bouma, L. G., et al. 2022, AJ, 164, 137, doi: 10.3847/1538-3881/ac866d

    doi:10.3847/1538-3881/ac866d 2022

  39. [39]

    J., & Lada, E

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

    Pith/arXiv arXiv 2003

  40. [40]

    2017, A&A, 603, A2, doi: 10.1051/0004-6361/201630294

    Magrini, L., Randich, S., Kordopatis, G., et al. 2017, A&A, 603, A2, doi: 10.1051/0004-6361/201630294

    doi:10.1051/0004-6361/201630294 2017

  41. [41]

    2023, A&A, 669, A119, doi: 10.1051/0004-6361/202244957

    Magrini, L., Viscasillas V´ azquez, C., Spina, L., et al. 2023, A&A, 669, A119, doi: 10.1051/0004-6361/202244957

    doi:10.1051/0004-6361/202244957 2023

  42. [42]

    R., Schiavon, R

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

    doi:10.3847/1538-3881/aa784d 2017

  43. [43]

    R., et al

    Medan, I., Dwelly, T., Covey, K. R., et al. 2025, AJ, 170, 267, doi: 10.3847/1538-3881/ae03b2 M´ endez-Delgado, J. E., Amayo, A., Arellano-C´ ordova, K. Z., et al. 2022, MNRAS, 510, 4436, doi: 10.1093/mnras/stab3782 M´ endez-Delgado, J. E., Esteban, C., Garc ´ ıa-Rojas, J., Arellano-C´ ordova, K. Z., & Valerdi, M. 2020, MNRAS, 496, 2726, doi: 10.1093/mnra...

    work page doi:10.3847/1538-3881/ae03b2 2025

  44. [44]

    2022, AJ, 164, 85, doi: 10.3847/1538-3881/ac7ce5

    Myers, N., Donor, J., Spoo, T., et al. 2022, AJ, 164, 85, doi: 10.3847/1538-3881/ac7ce5

    doi:10.3847/1538-3881/ac7ce5 2022

  45. [45]

    A., C ¸ akmak, H., Michel, R., & Karata¸ s, Y

    Netopil, M., Oralhan, ˙I. A., C ¸ akmak, H., Michel, R., & Karata¸ s, Y. 2021, MNRAS, doi: 10.1093/mnras/stab2961

    doi:10.1093/mnras/stab2961 2021

  46. [46]

    2026, A&A, 708, A17, doi: 10.1051/0004-6361/202558288

    Nunnari, A., D’Orazi, V., Fiorentino, G., et al. 2026, A&A, 708, A17, doi: 10.1051/0004-6361/202558288

    doi:10.1051/0004-6361/202558288 2026

  47. [47]

    M., Frinchaboy, P

    Otto, J. M., Frinchaboy, P. M., Myers, N. R., et al. 2026, AJ, 171, 91, doi: 10.3847/1538-3881/ae28d8 pandas development team, T. 2025, pandas-dev/pandas: Pandas, v2.3.3 Zenodo, doi: 10.5281/zenodo.17229934 18 0.5 0.0 0.5 [Fe/H] (a) BOSS DR20 APOGEE DR19 0.01 < a 0.15 Gyr -0.083±0.015 dex/kpc N=63 0.5 0.0 0.5 [Fe/H] (b) 0.15 < a 0.4 Gyr -0.054±0.012 dex/k...

    doi:10.3847/1538-3881/ae28d8 2026

  48. [48]

    W., Derwent, M

    Pogge, R. W., Derwent, M. A., O’Brien, T. P., et al. 2020, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 11447, Ground-based and Airborne Instrumentation for Astronomy VIII, ed. C. J

    2020

  49. [49]

    Evans, J. J. Bryant, & K. Motohara, 1144781, doi: 10.1117/12.2561113

    doi:10.1117/12.2561113

  50. [50]

    2024, adrn/gala: v1.9.1, v1.9.1 Zenodo, doi: 10.5281/zenodo.13377376

    Price-Whelan, A., Souchereau, H., Wagg, T., et al. 2024, adrn/gala: v1.9.1, v1.9.1 Zenodo, doi: 10.5281/zenodo.13377376

    doi:10.5281/zenodo.13377376 2024

  51. [51]

    Price-Whelan, A. M. 2017, The Journal of Open Source Software, 2, doi: 10.21105/joss.00388 SDSS Collaboration, Aghakhanloo, M., Aird, J., et al. 2026, ApJS, 285, 9, doi: 10.3847/1538-4365/ae4697

    doi:10.21105/joss.00388 2017

  52. [52]

    A., & Binney, J

    Sellwood, J. A., & Binney, J. J. 2002, MNRAS, 336, 785, doi: 10.1046/j.1365-8711.2002.05806.x

    arXiv 2002

  53. [53]

    2024, ApJ, 975, 89, doi: 10.3847/1538-4357/ad78e1

    Sinha, A., Zasowski, G., Frinchaboy, P., et al. 2024, ApJ, 975, 89, doi: 10.3847/1538-4357/ad78e1

    doi:10.3847/1538-4357/ad78e1 2024

  54. [54]

    A., Gunn, J

    Smee, S. A., Gunn, J. E., Uomoto, A., et al. 2013, AJ, 146, 32, doi: 10.1088/0004-6256/146/2/32

    doi:10.1088/0004-6256/146/2/32 2013

  55. [55]

    S., De Silva, G

    Spina, L., Ting, Y. S., De Silva, G. M., et al. 2021, MNRAS, 503, 3279, doi: 10.1093/mnras/stab471

    doi:10.1093/mnras/stab471 2021

  56. [56]

    2019, The Astrophysical Journal, 879, 69, doi: 10.3847/1538-4357/ab2331

    Ting, Y.-S., Conroy, C., Rix, H.-W., & Cargile, P. 2019, The Astrophysical Journal, 879, 69, doi: 10.3847/1538-4357/ab2331

    doi:10.3847/1538-4357/ab2331 2019

  57. [57]

    2023, MNRAS, 519, 2331, doi: 10.1093/mnras/stac2459

    Trentin, E., Ripepi, V., Catanzaro, G., et al. 2023, MNRAS, 519, 2331, doi: 10.1093/mnras/stac2459

    doi:10.1093/mnras/stac2459 2023

  58. [58]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2 Viscasillas V´ azquez, C., Magrini, L., Spina, L., et al. 2023, A&A, 679, A122, doi: 10.1051/0004-6361/202346963

    doi:10.1038/s41592-019-0686-2 2020

  59. [59]

    W., Swiler, L

    Vugrin, K. W., Swiler, L. P., Roberts, R. M., Stucky-Mack, N. J., & Sullivan, S. P. 2007, Water Resources Research, 43, doi: https://doi.org/10.1029/2005WR004804 Wes McKinney. 2010, in Proceedings of the 9th Python in Science Conference, ed. St´ efan van der Walt & Jarrod Millman, 56 – 61, doi: 10.25080/Majora-92bf1922-00a

    doi:10.1029/2005wr004804 2007

  60. [60]

    I., Quinn, J

    Wiggins, A. I., Quinn, J. R., Oeur, M., et al. 2025, ApJL, 995, L25, doi: 10.3847/2041-8213/ae21bf

    doi:10.3847/2041-8213/ae21bf 2025

  61. [61]

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

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

    doi:10.3847/1538-3881/adba45 2025

  62. [62]

    2021, ApJ, 919, 52, doi: 10.3847/1538-4357/ac0e92

    Zhang, H., Chen, Y., & Zhao, G. 2021, ApJ, 919, 52, doi: 10.3847/1538-4357/ac0e92

    work page doi:10.3847/1538-4357/ac0e92 2021