Pith. sign in

REVIEW 2 major objections 5 minor 1 cited by

A 130-night PFS survey will decide if Local Group dwarfs have dark-matter cusps or cores, and will map how M31 and the outer Milky Way assembled.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

T0 review · grok-4.5

2026-07-12 23:08 UTC pith:EX74RWKP

load-bearing objection Solid, high-stakes survey design paper for PFS-GA; the cusp/core forecasts are grounded but still rest on membership+binary control of higher LOSVD moments that is necessary and only partially demonstrated. the 2 major comments →

arxiv 2604.09875 v3 pith:EX74RWKP submitted 2026-04-10 astro-ph.GA astro-ph.SR

Galactic Archaeology with the Subaru `\=Onohi`ula Prime Focus Spectrograph Strategic Program

classification astro-ph.GA astro-ph.SR
keywords galactic archaeologydwarf spheroidal galaxiesdark matter density profilescore-cusp problemM31 stellar haloMilky Way outer diskchemical abundancesPFS spectroscopy
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 lays out the three-pillar Galactic Archaeology program of the Subaru PFS Strategic Survey. With spectra of roughly 18,000 member stars in six dwarf galaxies, the team will reconstruct each galaxy’s dark-matter density profile and test whether any cores can be explained by bursty star formation recorded in the stars’ [α/Fe] ratios. Parallel observations of 30,000 red giants across M31’s halo and outer disk will compare that galaxy’s merger history with the Milky Way’s quieter past, while tens of thousands of main-sequence stars out to 30 kpc will reveal how the fragile outer Milky Way responded to ancient and ongoing accretion. The survey exploits PFS’s 2,400 fibers, 1.24 deg^{2} field, and medium-resolution red arm, pre-selected with Hyper Suprime-Cam gravity-sensitive imaging. If successful, the data will turn the Local Group into a precision laboratory for both cold-dark-matter predictions and the assembly of L* disks.

Core claim

The authors claim that the planned PFS sample sizes, velocity precision better than 3 km s^{-1}, and chemical abundances will be sufficient to distinguish a dark-matter cusp (γ_DM ≈ -1) from a core (γ_DM ≈ 0) in each of six dwarf galaxies, and simultaneously to quantify whether the observed star-formation burstiness can account for any cores via baryonic feedback.

What carries the argument

Full line-of-sight velocity distributions plus multi-element abundances, modeled with axisymmetric Jeans, higher-order moments, Schwarzschild orbit superposition, and the Walker–Peñarrubia two-population mass estimator, all applied to chemically selected subpopulations that reach beyond each galaxy’s nominal tidal radius.

Load-bearing premise

That photometric membership from HSC broadband plus NB515 imaging, combined with two spectroscopic epochs months apart, will keep non-member and binary contamination low enough that higher-order velocity moments remain unbiased.

What would settle it

If, after the full 18,000-star sample is in hand, the recovered inner density slopes for the classical dwarfs still show large mass–anisotropy degeneracies or remain consistent with both cusps and cores at the level of current data, the claim that PFS can “definitively determine” the profiles fails.

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

If this is right

  • Dark-matter density profiles of six dwarfs spanning a wide stellar-mass range will be measured to the precision needed to test cold-dark-matter predictions against fuzzy or self-interacting alternatives.
  • Star-formation histories inferred from [α/Fe]–[Fe/H] diagrams will show whether baryonic feedback is strong enough to erase cusps in the more massive systems.
  • M31’s [α/Fe] patterns across 45 deg^{2} will reveal whether its halo and disk were built by a major wet merger or by a series of minor accretions, providing a direct contrast with the Milky Way.
  • Ages, velocities and metallicities of outer-disk and halo main-sequence stars will map the Milky Way’s response to Gaia–Sausage–Enceladus and Sagittarius, including bending and breathing modes.
  • Extra-tidal stars and cold streams will constrain both the outer mass profiles of the dwarfs and the shape of the Milky Way’s dark halo.

Where Pith is reading between the lines

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

  • Success on the dwarf-galaxy pillar would supply the astrophysical J-factors needed for tighter multi-wavelength limits on dark-matter particle annihilation or decay.
  • A clear chemical dichotomy (or its absence) between M31’s thin and thick disks would become a benchmark for semi-analytic and cosmological zoom-in models of L* galaxy assembly.
  • The same PFS spectra that map the outer Milky Way will serendipitously enlarge the census of extremely metal-poor and ultracool subdwarf stars, feeding nucleosynthesis and low-mass star-formation studies.
  • If cores are found only in galaxies with clear bursty [α/Fe] signatures, the result would favor baryonic feedback over exotic dark-matter physics as the dominant solution to the core-cusp problem.

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 manuscript presents the design, science goals, and survey strategy for the Galactic Archaeology component of the Subaru PFS Strategic Program (130 nights). It has three pillars: (1) dark-matter density profiles and chemical evolution of six Local Group dwarf galaxies (plus NGC 6822), aiming for ~18,000 member stars with velocities better than 3 km/s and [α/Fe] and detailed abundances; (2) a large-scale chemodynamical survey of M31 (and M33) with ~30,000 member stars over ~45 deg² to compare assembly histories with the Milky Way; and (3) outer-disk and halo fields of the MW to map responses to past and ongoing accretion (GSE, Sgr, LMC) using velocities, metallicities, and ages for main-sequence stars out to ~30 kpc. The paper details HSC pre-imaging and membership selection, fiber allocation, binary mitigation, and spectral analysis pipelines for RVs and abundances, with forecasts based on published mocks and simulations.

Significance. If the survey delivers as forecast, it will provide the largest homogeneous samples of velocities and multi-element abundances for classical dSphs and for M31’s halo/disk, enabling a definitive cusp/core test across a range of stellar masses and SFHs, multi-zone chemical-evolution models, and a direct comparison of M31 versus MW merger histories. Strengths include explicit sample-size and S/N forecasts (Tables 1–2, Figs. 15, 18–19), published mock Jeans and abundance analyses (Hayashi et al., Wardana et al., Hirai et al., Dobos et al.), binary-orbit simulations (Ye et al. 2024), and multi-method dynamical plans (WP11, axisymmetric Jeans, higher-order moments, Schwarzschild). The paper is a prospective survey design rather than a results paper; its value is as a clear, falsifiable roadmap for a major facility program.

major comments (2)
  1. §2.1.2–2.1.3 and Fig. 2b: The central claim of a definitive cusp/core distinction (Abstract; magenta points in Fig. 1) relies on higher-order LOSVD moments (kurtosis) to break the γ–β degeneracy that persists with second moments alone even at N~thousands (citing Chang & Necib 2021). Residual non-Gaussian wings from imperfect membership or binaries can erase that leverage. The mitigation plan (HSC NB515 + broadband probabilities in §6.2; two-epoch spectroscopy + Bayesian binary model of Ye et al. 2024) is necessary but not shown end-to-end to leave residual contamination low enough that the cyan posterior in Fig. 2b still cleanly separates γ_DM = −1 from 0 for the lower-N systems (Draco, UMi, Boötes I). A quantitative residual-contamination budget or end-to-end mock that injects realistic membership and binary residuals into the higher-moment analysis would make the “definitive” claim loa
  2. Table 2 and §2.1.4: Boötes I is listed with only ~1000 stars and is noted as too sparse for full LOSVD shape work (§2.1.2). The paper should state more explicitly which dynamical methods (WP11-style subpopulations vs. full higher-moment Jeans/Schwarzschild) are expected to deliver a robust γ_DM for each galaxy, and which systems are limited to second-moment or multi-population constraints only, so that the forecast magenta points in Fig. 1 are not over-interpreted for the lowest-N targets.
minor comments (5)
  1. Table 1: The total of 91 clear nights assumes a 0.7 clear-sky fraction of 130 nights; a short note on how weather contingency or re-prioritization among the three pillars would be handled would help readers assess schedule risk.
  2. §6.2 and Fig. 13: The synthetic NB515 magnitudes for cool main-sequence stars are acknowledged to be incorrect and are excluded; a brief statement of how this affects membership purity at the bright RGB tip (where foreground contamination is highest) would strengthen the targeting section.
  3. §7.1–7.2: RV and abundance pipelines are described with useful simulations (Figs. 18–21), but the text notes that full end-to-end validation and systematic error budgets will appear in future papers. Cross-references to those forthcoming works (or a short appendix table of expected systematics) would help readers gauge readiness.
  4. Figure 1 caption and §2.1.1: The open/filled magenta points are “expected constraints under two prospective scenarios.” Clarifying whether the error bars include only Poisson/sample-size effects or also residual contamination and binary modeling would avoid over-reading the forecast.
  5. Minor presentation: Consistent use of γ_DM vs. γ_in (and of [α/Fe] vs. [α/M]) across text and figures would reduce notational friction; a few figure panels (e.g., Fig. 3 pointings) would benefit from larger labels for readability in print.

Circularity Check

0 steps flagged

No significant circularity: prospective survey design whose forecasts rest on independent mocks and published codes, not on self-defined or fitted-as-predicted results.

full rationale

This is a Subaru/PFS Strategic Program survey-design paper. It does not claim to have measured dark-matter density slopes, [α/Fe] patterns, or MW outer-disk responses; it describes planned observations, sample sizes, and analysis methods, and illustrates expected performance with mock catalogs. The magenta forecast points in Fig. 1 and the recovered profiles in Fig. 2 are generated from independent mock data (AGAMA, GravSphere, MAMPOSSt, axisymmetric Jeans, etc.) with known input cusps/cores and published dynamical codes; they are not fits to real PFS data re-labeled as predictions. Self-citations (Hayashi et al. 2020/2023, Wardana et al. 2025, Hirai et al. 2024, Dobos et al. 2024, Ye et al. 2024, Ogami et al. 2025, etc.) supply prior methodological simulations, membership techniques, or binary models; none of those works already contains the target scientific result (cusp/core determinations for the six dSphs, M31 assembly history, or MW outer-disk response), so the citations are not load-bearing circular premises. There is no self-definitional loop, no uniqueness theorem imported from the same authors to forbid alternatives, no ansatz smuggled in as a theorem, and no renaming of a known empirical pattern as a new derivation. The paper is self-contained as a prospective design document against external benchmarks (ΛCDM NFW, SIDM/FDM cores, existing DEIMOS/DART/DESI samples). Score 0 is therefore the correct, proportionate finding.

Axiom & Free-Parameter Ledger

0 free parameters · 5 axioms · 0 invented entities

As a survey-design paper the load-bearing content is instrumental capability plus standard dynamical and chemical-evolution assumptions. No free parameters are fitted to new data; the axioms are the usual domain premises of stellar dynamics and nucleosynthesis that any such survey inherits.

axioms (5)
  • domain assumption Cold-dark-matter N-body simulations produce NFW-like cusps (γ_DM ≈ −1) in the absence of baryons; cores require either alternative DM or repeated baryonic feedback.
    Stated in §2.1.1 and Fig. 1; the entire cusp/core science case rests on this standard prediction.
  • domain assumption Distinct chemodynamical subpopulations (metal-rich/cold vs metal-poor/hot) share the same gravitational potential and can therefore be used as independent tracers (Walker & Peñarrubia 2011 method).
    Invoked throughout §2.1.2 as the basis for model-independent enclosed-mass estimates.
  • domain assumption Higher-order moments of the LOSVD (kurtosis) plus non-spherical Jeans or Schwarzschild modeling break the mass-anisotropy degeneracy once samples exceed ~1000 secure members.
    Supported by cited mock analyses (Read et al. 2021; Wardana et al. 2025) and used to justify the planned sample sizes.
  • ad hoc to paper Two spectroscopic epochs separated by months, combined with a Bayesian binary model, recover center-of-mass velocities sufficiently well that binary inflation of the LOSVD wings does not bias the density-profile inference.
    Specific observing strategy and simulation results of Ye et al. 2024 (§2.1.3); not a universal literature result.
  • ad hoc to paper HSC NB515 gravity-sensitive photometry plus broadband colors yield membership probabilities accurate enough that residual MW-halo contamination can be forward-modeled in the LOSVD.
    Core of the targeting strategy (§6.2 and Figs. 13–14); success is demonstrated only on simulations and limited existing spectroscopy.

pith-pipeline@v1.1.0-grok45 · 67337 in / 2932 out tokens · 34942 ms · 2026-07-12T23:08:36.681942+00:00 · methodology

0 comments
read the original abstract

The recently commissioned Subaru `\=Onohi`ula Prime Focus Spectrograph (PFS) will obtain spectra from nearly 2,400 fibers that cover 1.24 square degrees. The 360 night Subaru Strategic Program for PFS is dedicating approximately one-third of its allocation (130 nights) to study the structure and evolution of galaxies in the Local Group. This Galactic Archaeological survey has three pillars. (1) We will determine whether the mass density profiles of dwarf galaxies are consistent with cusps, as expected for cold dark matter, or cores, as expected from alternative dark matter theories or baryonic feedback. We will deduce the density profiles as a function of radius from modeling of the full line-of-sight velocity and abundance distributions for six dwarf galaxies. Our total sample will consist of 18,000 member stars to beyond the nominal tidal radius of each system. (2) From measurements of the [alpha/Fe] abundance ratio, we will learn the difference in assembly history of the two most massive galaxies in the Local Group: M31 and the Milky Way. We will observe 30,000 member stars over 45 square degrees of M31's halo and outer disk. (3) We will uncover how the most fragile (outer) part of the Milky Way responded to accretion events both in the distant past (such as Gaia-Sausage Enceladus) and in more recent history (such as the Sagittarius dwarf spheroidal galaxy). To support this study, PFS will provide velocities and metallicities--from which, in combination with photometry, we will deduce ages--for tens of thousands of main-sequence stars out to a Galactocentric distance of ~30 kpc.

Figures

Figures reproduced from arXiv: 2604.09875 by Alexander S. Szalay, Ana L. Chies-Santos, Andrew P. Cooper, Carrie Filion, Chiaki Kobayashi, Dafa Wardana, Elisa G. M. Ferreira, Evan N. Kirby, Federico Sestito, Gang Zhao, Itsuki Ogami, Ivanna Escala, Jihye Hong, Jingkun Zhao, Judith G. Cohen, Keyi Ding, Kohei Hayashi, Kyosuke Sato, L\'aszl\'o Dobos, Lauren Henderson, Magda Arnaboldi, Masashi Chiba, Miho N. Ishigaki, Mohammad K. Mardini, Nicolas Martin, Nicole L. Klock-Miranda, Ortwin Gerhard, Pete B. Kuzma, Rin Miyazaki Sakurako Okamoto, Rohan Pattnaik, Roman Gerasimov, Rosemary F. G. Wyse, Ryo Ishikawa, Ryota Ikeda, Shunichi Horigome, Souradeep Bhattacharya, Takanobu Kirihara, Tam\'as Budav\'ari, Viska Wei, Wenbo Wu, Xiangwei Zhang, Xianhao Ye, Xiaosheng Zhao, Xinfeng Xu, Yohei Miki, Yoshihisa Suzuki, Yutaka Hirai, Yutaka Komiyama, Zhenyu Wu, Zhuohan Li.

Figure 1
Figure 1. Figure 1: (Figure after J. S. Bullock & M. Boylan-Kolchin 2017, their [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: (a) DM density profiles derived by an axisymmetric, 2nd-velocity-moment Jeans analysis. The underlying model is shown as a dashed line. The shaded bands and colored curves correspond to the recovered density profiles and uncertainties obtained using line-of-sight velocities for stars that match “Current” (N = 500, orange) and “PFS forecast” (N = 5, 000, purple) samples, distributed on the sky as shown in t… view at source ↗
Figure 3
Figure 3. Figure 3: The planned PFS pointings for the dwarf galaxies. Red hexagons indicate pointings that will be repeated to identify candidate binary systems. The blue and gray dots in each panel are member and non-member star candidates selected by HSC photometry. The solid and dashed ellipses show the core and nominal tidal radii that result from fits to King model profiles (R. R. Mu˜noz et al. 2018). S14A (PI:Chiba) & S… view at source ↗
Figure 4
Figure 4. Figure 4: The HSC color–magnitude diagrams for three dSphs in order of decreasing distance. Red points show stars that pass the narrow-band selection for giants. The approximate g magnitude limit for PFS spectroscopy is shown as a solid blue line. The approximate g magnitude at which [Fe/H] and [α/Fe] uncertainties are less than 0.15 are shown as dashed blue lines (constants in g magnitude). The limits for 3 and 5 k… view at source ↗
Figure 5
Figure 5. Figure 5: Proposed PFS pointings (gray hexagons) in M31 and M33 (inset). The color map shows the surface density of candidate member stars selected through the combination of HSC broadband (g, i) and narrowband (NB515) imaging (I. Ogami et al. 2025). We anticipate observing about 30,000 red giants in M31. Also shown are planetary nebulae (§3.2) and candidate globular clusters (§3.6). morphology of cannibalized satel… view at source ↗
Figure 6
Figure 6. Figure 6: Mean log(O/Ar) values of older (> 4.5 Gyr) low-extinction PNe (red) over the 2 − 30 kpc M31-galactocentric radial range, the younger (∼ 2.5 Gyr) high-extinction PNe (blue) within RM31 ≤ 14 kpc, and the two-infall fiducial chemical evolution model for the M31 disk(s), colored by predicted lookback time (see M. Arn￾aboldi et al. 2022 for details). quent or more massive mergers of luminous or dark satel￾lites… view at source ↗
Figure 7
Figure 7. Figure 7: N-body simulation that reproduces the morphology and kinematics of the Northwestern Stream in M31 (Miki & Kirihara, private communication): (a) The projected spatial densities of simulated stellar particles, where the main stellar disk of M31 is represented by an ellipse and the five HSC pointings for the stream (Y. Komiyama et al. 2018) are shown by the circles. These fields are included in the planned PF… view at source ↗
Figure 8
Figure 8. Figure 8: HSC color–magnitude ((g − i)0 vs. i0) and color–color ((NB515 − g)0 vs. (g − i)0) diagrams for stars in the fields of the Northwestern Stream of M31, shown in [PITH_FULL_IMAGE:figures/full_fig_p018_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Radial density profile of the HSC/NB515-selected RGB stars in the outer region of M33 (reproduced by per￾mission of the AAS from I. Ogami et al. 2024). The black dots and their error bars indicate the number density of stars in each region. The red, blue, and pink lines are the derived individual profiles for the disk, halo, and contamination com￾ponents, respectively, and the orange line shows the result … view at source ↗
Figure 10
Figure 10. Figure 10: The predicted abundance-ratio distribution of disk stars at different Galactocentric radial and height ranges, from the chemodynamical simulation model by F. Vincenzo & C. Kobayashi (2020). The color coding indicates the degree of rotation support: vrot/σ < 3 (blue), 2.5 (cyan), 2 (green), 1.5 (yellow), 1 (orange), and 0.5 (red). Merrifield & K. Kuijken 1998), as seen in N-body and cosmological numerical … view at source ↗
Figure 11
Figure 11. Figure 11: Planned PFS outer Milky Way fields for low and high latitude regions. The low-latitude fields target the outer disk and consists of 44 contiguous pointings at l = 180◦ and l = 90◦ over 15◦ < |b| < 30◦ . The high-latitude fields target the Galactic halo and include 45 pointings over 30◦ < |b| < 60◦ , including those covering the three halo streams Triangulum–Pisces, NGC5466, and Hermus. Known member stars … view at source ↗
Figure 12
Figure 12. Figure 12: Synthetic spectra of UCDs (Teff = 2700 K) with assumed elemental abundances characteristic of the thin disk, thick disk and the Galactic halo (J. T. Mackereth et al. 2019), shown in black, green and red respectively. Prominent molecular absorption bands and atomic lines are highlighted and labeled. Intensities have been offset for clarity, as indicated by dotted horizontal lines. Subsolar metallicity mode… view at source ↗
Figure 13
Figure 13. Figure 13: The two top panels of [PITH_FULL_IMAGE:figures/full_fig_p029_13.png] view at source ↗
Figure 15
Figure 15. Figure 15: Expected signal-to-noise per resolution element in the medium resolution red arm, for three different types of targets. Targets in the fields of dSphs will have an expo￾sure time of 3 hours, while M31 targets will be observed for 5 hours. The top two panels of [PITH_FULL_IMAGE:figures/full_fig_p030_15.png] view at source ↗
Figure 14
Figure 14. Figure 14: Panels a and b: Membership probability of stars observed in the field of the Ursa Minor dwarf galaxy based on HSC broadband and narrow-band photometry from stellar population simulations. Panel (a) shows the probabil￾ities based on broadband colors only while panel (b) is based on the broadband photometry plus the NB515 narrow-band filter. Panel c: “Ghost plot” of the observed CMD with stars randomly remo… view at source ↗
Figure 16
Figure 16. Figure 16: The color–magnitude (top left) and color–color (top right) diagrams, corrected for reddening and extinction, for the stars of the Ursa Minor dSph. The innermost four pointings (of the planned eight pointings) are shown. Stars with fibers assigned are shown in the right panels. Untargeted stars are shown in the middle panels. The spatial distribution of the stars is plotted in the bottom row. The bottom ri… view at source ↗
Figure 17
Figure 17. Figure 17: Panel a: Stars observed by HSC in four fields around the center of the Ursa Minor dSph. The dashed el￾lipse marks the nominal tidal radius, while the blue hexagons indicate these inner PFS pointings. Panel b: The col￾or-magnitude diagram, corrected for reddening and extinc￾tion, of stars located outside the nominal tidal radius. Even though the sample is clearly dominated by likely foreground Milky Way ha… view at source ↗
Figure 18
Figure 18. Figure 18: The uncertainty of RV measurements (random errors only) as a function of S/N per resolution element, for the medium-resolution red arm (top row) and of HSC i mag￾nitude (bottom row), for three different stellar types, similar to those that the PFS/SSP will target in dSphs (texp = 3 hr) and in M31 (texp = 5 hr). The colors indicate the spectro￾graph arms included in the simulations: blue – blue arm, black … view at source ↗
Figure 19
Figure 19. Figure 19: Expected limiting r-magnitudes for PFS mea￾surements of chemical abundances for stars with different metallicities. Limiting magnitudes are defined such that the random error in the measurement does not exceed 0.1 dex. The magnitudes were derived from simulated observations of a star with Teff = 5000 K, log(g) = 1.5, and scaled solar abundances. Nominal 3-hour exposures and the MR mode in the red arm were… view at source ↗
Figure 20
Figure 20. Figure 20: Spectral model fit to a PFS SSP observation of a r ≈ 16.8 red giant member of Draco with estimated Teff = 4270 K and [Fe/H] = −1.7. This spectrum was obtained with 3 hours of exposure. The three panels showcase small regions of the spectra obtained with the blue (left), MR-mode red (center) and infrared (right) arms, centered around La ii λλ5302, 5304, Mg i λ8807, and Si i λλ10785, 10787, respectively. Th… view at source ↗
Figure 21
Figure 21. Figure 21: MCMC posterior distributions of chemical pa￾rameters inferred from simulated PFS observations of a star with Teff = 4000 K, log(g) = 1 and [Fe/H] = −1, assuming a range of apparent magnitudes as shown. The contours show 2-sigma constraints on the best-fit parameters. 8. SUMMARY The PFS/SSP GA survey, as outlined here, will sig￾nificantly improve our understanding of the formation, evolution, and structure… view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The Merger-Driven Origin of the Vast Extended Stellar Disc Around the Andromeda Galaxy

    astro-ph.GA 2026-07 unverdicted novelty 5.0

    N-body simulation of a major merger shows M31's extended rotating stellar disc as a stretched and warped remnant of the progenitor disc extending beyond 40 kpc.

Reference graph

Works this paper leans on

294 extracted references · 13 linked inside Pith · cited by 1 Pith paper

  1. [1]

    2018, PASJ, 70, S4, doi: 10.1093/pasj/psx066

    Aihara, H., Arimoto, N., Armstrong, R., et al. 2018, PASJ, 70, S4, doi: 10.1093/pasj/psx066

  2. [2]

    2022, PASJ, 74, 247, doi: 10.1093/pasj/psab122

    Aihara, H., AlSayyad, Y., Ando, M., et al. 2022, PASJ, 74, 247, doi: 10.1093/pasj/psab122

  3. [3]

    2011, in Cool Stars 16, Vol

    Allard, F., Homeier, D., & Freytag, B. 2011, in Cool Stars 16, Vol. 448, 91, doi: 10.48550/arXiv.1011.5405

  4. [4]

    J., et al

    Alvarado, E., Gerasimov, R., Burgasser, A. J., et al. 2024, Research Notes of the American Astronomical Society, 8, 134, doi: 10.3847/2515-5172/ad4bd7

  5. [5]

    C., Agnello, A., & Evans, N

    Amorisco, N. C., Agnello, A., & Evans, N. W. 2013, MNRAS, 429, L89, doi: 10.1093/mnrasl/sls031

  6. [6]

    C., & Evans, N

    Amorisco, N. C., & Evans, N. W. 2012, MNRAS, 419, 184, doi: 10.1111/j.1365-2966.2011.19684.x

  7. [7]

    2022, arXiv e-prints, arXiv:2203.06781

    Ando, S., Baum, S., Boylan-Kolchin, M., et al. 2022, arXiv e-prints, arXiv:2203.06781. https://arxiv.org/abs/2203.06781

  8. [8]

    2018, Nature, 561, 360, doi: 10.1038/s41586-018-0510-7

    Antoja, T., Helmi, A., Romero-G´ omez, M., et al. 2018, Nature, 561, 360, doi: 10.1038/s41586-018-0510-7

  9. [9]

    D., et al

    Arentsen, A., Starkenburg, E., Shetrone, M. D., et al. 2019, A&A, 621, A108, doi: 10.1051/0004-6361/201834146

  10. [10]

    Arnaboldi, M., Aguerri, J. A. L., Napolitano, N. R., et al. 2002, AJ, 123, 760, doi: 10.1086/338313

  11. [11]

    2022, A&A, 666, A109, doi: 10.1051/0004-6361/202244258

    Arnaboldi, M., Bhattacharya, S., Gerhard, O., et al. 2022, A&A, 666, A109, doi: 10.1051/0004-6361/202244258

  12. [12]

    1995, ApJL, 451, L49, doi: 10.1086/309687

    Audouze, J., & Silk, J. 1995, ApJL, 451, L49, doi: 10.1086/309687

  13. [13]

    2008, ApJL, 681, L13, doi: 10.1086/590179

    Battaglia, G., Helmi, A., Tolstoy, E., et al. 2008, ApJL, 681, L13, doi: 10.1086/590179

  14. [14]

    A., San Roman, I., Gallart, C., Sarajedini, A., & Aparicio, A

    Beasley, M. A., San Roman, I., Gallart, C., Sarajedini, A., & Aparicio, A. 2015, MNRAS, 451, 3400, doi: 10.1093/mnras/stv943

  15. [15]

    C., & Christlieb, N

    Beers, T. C., & Christlieb, N. 2005, ARA&A, 43, 531, doi: 10.1146/annurev.astro.42.053102.134057

  16. [16]

    2020, ApJ, 903, 10, doi: 10.3847/1538-4357/abb5f4

    Belland, B., Kirby, E., Boylan-Kolchin, M., & Wheeler, C. 2020, ApJ, 903, 10, doi: 10.3847/1538-4357/abb5f4

  17. [17]

    Deason, A. J. 2018, MNRAS, 478, 611, doi: 10.1093/mnras/sty982

  18. [18]

    L., Fattahi, A., et al

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

  19. [19]

    J., et al

    Belokurov, V., Vasiliev, E., Deason, A. J., et al. 2023, MNRAS, 518, 6200, doi: 10.1093/mnras/stac3436

  20. [20]

    B., Evans, N

    Belokurov, V., Zucker, D. B., Evans, N. W., et al. 2006, ApJL, 642, L137, doi: 10.1086/504797

  21. [21]

    2003, A&A, 410, 527, doi: 10.1051/0004-6361:20031213

    Bensby, T., Feltzing, S., & Lundstr¨ om, I. 2003, A&A, 410, 527, doi: 10.1051/0004-6361:20031213

  22. [22]

    J., Ferguson, A

    Bernard, E. J., Ferguson, A. M. N., Schlafly, E. F., et al. 2016, MNRAS, 463, 1759, doi: 10.1093/mnras/stw2134

  23. [23]

    2024, A&A, 686, A92, doi: 10.1051/0004-6361/202348410

    Bernet, M., Ramos, P., Antoja, T., Monari, G., & Famaey, B. 2024, A&A, 686, A92, doi: 10.1051/0004-6361/202348410

  24. [24]

    2012, MNRAS, 421, 2109, doi: 10.1111/j.1365-2966.2012.20466.x

    Besla, G., Kallivayalil, N., Hernquist, L., et al. 2012, MNRAS, 421, 2109, doi: 10.1111/j.1365-2966.2012.20466.x

  25. [25]

    2025a, ApJL, 983, L30, doi: 10.3847/2041-8213/adc735

    Bhattacharya, S., Arnaboldi, M., Gerhard, O., Kobayashi, C., & Saha, K. 2025a, ApJL, 983, L30, doi: 10.3847/2041-8213/adc735

  26. [26]

    2021, A&A, 647, A130, doi: 10.1051/0004-6361/202038366

    Bhattacharya, S., Arnaboldi, M., Gerhard, O., et al. 2021, A&A, 647, A130, doi: 10.1051/0004-6361/202038366

  27. [27]

    2023, MNRAS, 522, 6010, doi: 10.1093/mnras/stad1378

    Bhattacharya, S., Arnaboldi, M., Hammer, F., et al. 2023, MNRAS, 522, 6010, doi: 10.1093/mnras/stad1378

  28. [28]

    2019a, A&A, 624, A132, doi: 10.1051/0004-6361/201834579

    Bhattacharya, S., Arnaboldi, M., Hartke, J., et al. 2019a, A&A, 624, A132, doi: 10.1051/0004-6361/201834579

  29. [29]

    2025b, arXiv e-prints, arXiv:2505.01896, doi: 10.48550/arXiv.2505.01896

    Bhattacharya, S., Arnaboldi, M., Kobayashi, C., Gerhard, O., & Saha, K. 2025b, arXiv e-prints, arXiv:2505.01896, doi: 10.48550/arXiv.2505.01896

  30. [30]

    2019b, A&A, 631, A56, doi: 10.1051/0004-6361/201935898

    Bhattacharya, S., Arnaboldi, M., Caldwell, N., et al. 2019b, A&A, 631, A56, doi: 10.1051/0004-6361/201935898

  31. [31]

    2022, MNRAS, 517, 2343, doi: 10.1093/mnras/stac2703

    Bhattacharya, S., Arnaboldi, M., Caldwell, N., et al. 2022, MNRAS, 517, 2343, doi: 10.1093/mnras/stac2703

  32. [32]

    C., Loebman, S

    Bird, J. C., Loebman, S. R., Weinberg, D. H., et al. 2021, MNRAS, 503, 1815, doi: 10.1093/mnras/stab289

  33. [34]

    2021b, MNRAS, 504, 3168, doi: 10.1093/mnras/stab704

    Bland-Hawthorn, J., & Tepper-Garc´ ıa, T. 2021b, MNRAS, 504, 3168, doi: 10.1093/mnras/stab704

  34. [35]

    C., M´ esz´ aros, S., Fleming, S

    Bohlin, R. C., M´ esz´ aros, S., Fleming, S. W., et al. 2017, AJ, 153, 234, doi: 10.3847/1538-3881/aa6ba9

  35. [36]

    2012, ApJL, 760, L6, doi: 10.1088/2041-8205/760/1/L6

    Bonaca, A., Geha, M., & Kallivayalil, N. 2012, ApJL, 760, L6, doi: 10.1088/2041-8205/760/1/L6

  36. [37]

    Bonaca, A., & Hogg, D. W. 2018, ApJ, 867, 101, doi: 10.3847/1538-4357/aae4da PFS-SSP GA Science39

  37. [38]

    Bonaca, A., & Price-Whelan, A. M. 2025, New Astronomy Reviews, 100, 101713, doi: https://doi.org/10.1016/j.newar.2024.101713

  38. [39]

    A., et al

    Bonaca, A., Conroy, C., Cargile, P. A., et al. 2020, ApJL, 897, L18, doi: 10.3847/2041-8213/ab9caa

  39. [40]

    2021, A&A, 651, A79, doi: 10.1051/0004-6361/202140816

    Bonifacio, P., Monaco, L., Salvadori, S., et al. 2021, A&A, 651, A79, doi: 10.1051/0004-6361/202140816

  40. [41]

    2018, PASJ, 70, S5, doi: 10.1093/pasj/psx080

    Bosch, J., Armstrong, R., Bickerton, S., et al. 2018, PASJ, 70, S5, doi: 10.1093/pasj/psx080

  41. [42]

    A., & Helmi, A

    Breddels, M. A., & Helmi, A. 2014, ApJL, 791, L3, doi: 10.1088/2041-8205/791/1/L3

  42. [43]

    Bromm, V., & Larson, R. B. 2004, ARA&A, 42, 79, doi: 10.1146/annurev.astro.42.053102.134034

  43. [44]

    2024, The BONES Archive, Zenodo, doi: 10.5281/zenodo.12668258

    Brooks, H. 2024, The BONES Archive, Zenodo, doi: 10.5281/zenodo.12668258

  44. [45]

    2021, MNRAS, 506, 150, doi: 10.1093/mnras/stab1242

    Buder, S., Sharma, S., Kos, J., et al. 2021, MNRAS, 506, 150, doi: 10.1093/mnras/stab1242

  45. [46]

    S., & Boylan-Kolchin, M

    Bullock, J. S., & Boylan-Kolchin, M. 2017, ARA&A, 55, 343, doi: 10.1146/annurev-astro-091916-055313

  46. [47]

    S., & Johnston, K

    Bullock, J. S., & Johnston, K. V. 2005, ApJ, 635, 931, doi: 10.1086/497422

  47. [48]

    J., Cruz, K

    Burgasser, A. J., Cruz, K. L., & Kirkpatrick, J. D. 2007, ApJ, 657, 494, doi: 10.1086/510148

  48. [49]

    B., Koposov, S

    Buttry, R., Pace, A. B., Koposov, S. E., et al. 2022, MNRAS, 514, 1706, doi: 10.1093/mnras/stac1441

  49. [50]

    2011, Nature, 477, 67, doi: 10.1038/nature10377

    Caffau, E., Bonifacio, P., Fran¸ cois, P., et al. 2011, Nature, 477, 67, doi: 10.1038/nature10377

  50. [51]

    Caldwell, N., & Romanowsky, A. J. 2016, ApJ, 824, 42, doi: 10.3847/0004-637X/824/1/42

  51. [52]

    2011, AJ, 141, 61, doi: 10.1088/0004-6256/141/2/61

    Harding, P. 2011, AJ, 141, 61, doi: 10.1088/0004-6256/141/2/61

  52. [53]

    M., O’Leary, E

    Cannon, J. M., O’Leary, E. M., Weisz, D. R., et al. 2012, ApJ, 747, 122, doi: 10.1088/0004-637X/747/2/122

  53. [54]

    Carlberg, R. G. 2012, ApJ, 748, 20, doi: 10.1088/0004-637X/748/1/20

  54. [55]

    G., Jenkins, A., Frenk, C

    Carlberg, R. G., Jenkins, A., Frenk, C. S., & Cooper, A. P. 2024, ApJ, 975, 135, doi: 10.3847/1538-4357/ad7b35

  55. [56]

    2003, PASP, 115, 763, doi: 10.1086/376392

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

  56. [57]

    C., Magnier, E

    Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv, arXiv:1612.05560, doi: 10.48550/arXiv.1612.05560

  57. [58]

    2022, MNRAS, 511, 943, doi: 10.1093/mnras/stac063

    Chiba, M. 2022, MNRAS, 511, 943, doi: 10.1093/mnras/stac063

  58. [59]

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

    Chandra, V., Semenov, V. A., Rix, H.-W., et al. 2024, ApJ, 972, 112, doi: 10.3847/1538-4357/ad5b60

  59. [60]

    P., Conroy, C., et al

    Chandra, V., Naidu, R. P., Conroy, C., et al. 2025, ApJ, 988, 156, doi: 10.3847/1538-4357/addab6

  60. [61]

    J., & Necib, L

    Chang, L. J., & Necib, L. 2021, MNRAS, 507, 4715, doi: 10.1093/mnras/stab2440

  61. [62]

    C., Ibata, R., Lewis, G

    Chapman, S. C., Ibata, R., Lewis, G. F., et al. 2006, ApJ, 653, 255, doi: 10.1086/508599

  62. [63]

    Q., Liu, X

    Chen, B. Q., Liu, X. W., Xiang, M. S., et al. 2015, VizieR Online Data Catalog (other), 0400, J/other/RAA/15

  63. [64]

    2015, Research in Astronomy and Astrophysics, 15, 1392, doi: 10.1088/1674-4527/15/8/020

    Chen, B.-Q., Liu, X.-W., Xiang, M.-S., et al. 2015, Research in Astronomy and Astrophysics, 15, 1392, doi: 10.1088/1674-4527/15/8/020

  64. [65]

    Q., Zhao, G., & Zhao, J

    Chen, Y. Q., Zhao, G., & Zhao, J. K. 2009, ApJ, 702, 1336, doi: 10.1088/0004-637X/702/2/1336

  65. [66]

    2001, ApJ, 554, 1044, doi: 10.1086/321427

    Chiappini, C., Matteucci, F., & Romano, D. 2001, ApJ, 554, 1044, doi: 10.1086/321427

  66. [67]

    Chiba, M., & Beers, T. C. 2000, AJ, 119, 2843, doi: 10.1086/301409

  67. [68]

    K., et al

    Chiti, A., Frebel, A., Mardini, M. K., et al. 2021, ApJS, 254, 31, doi: 10.3847/1538-4365/abf73d

  68. [69]

    2008, A&A, 484, 721, doi: 10.1051/0004-6361:20078748 Ciuc˘ a, I., Kawata, D., Miglio, A., Davies, G

    Christlieb, N., Sch¨ orck, T., Frebel, A., et al. 2008, A&A, 484, 721, doi: 10.1051/0004-6361:20078748 Ciuc˘ a, I., Kawata, D., Miglio, A., Davies, G. R., & Grand, R. J. J. 2021, MNRAS, 503, 2814, doi: 10.1093/mnras/stab639

  69. [70]

    R., McMonigal, B., Bate, N

    Conn, A. R., McMonigal, B., Bate, N. F., et al. 2016, MNRAS, 458, 3282, doi: 10.1093/mnras/stw513

  70. [71]

    H., Naidu, R

    Conroy, C., Weinberg, D. H., Naidu, R. P., et al. 2022, arXiv e-prints, arXiv:2204.02989, doi: 10.48550/arXiv.2204.02989

  71. [72]

    P., Cole, S., Frenk, C

    Cooper, A. P., Cole, S., Frenk, C. S., et al. 2010, MNRAS, 406, 744, doi: 10.1111/j.1365-2966.2010.16740.x

  72. [73]

    P., Koposov, S

    Cooper, A. P., Koposov, S. E., Allende Prieto, C., et al. 2023, ApJ, 947, 37, doi: 10.3847/1538-4357/acb3c0 Correa Magnus, L., & Vasiliev, E. 2022, MNRAS, 511, 2610, doi: 10.1093/mnras/stab3726 Da Costa, G. S., Bessell, M. S., Mackey, A. D., et al. 2019, MNRAS, 489, 5900, doi: 10.1093/mnras/stz2550 de Blok, W. J. G., McGaugh, S. S., Bosma, A., & Rubin, V....

  73. [75]

    Shen, K. J. 2020b, ApJ, 891, 85, doi: 10.3847/1538-4357/ab736f De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, 2604, doi: 10.1093/mnras/stv327 40PFS-SSP GA Working group

  74. [76]

    2014, ApJ, 794, 115, doi: 10.1088/0004-637X/794/2/115

    Deason, A., Wetzel, A., & Garrison-Kimmel, S. 2014, ApJ, 794, 115, doi: 10.1088/0004-637X/794/2/115

  75. [77]

    J., Belokurov, V., Koposov, S

    Deason, A. J., Belokurov, V., Koposov, S. E., & Lancaster, L. 2018, ApJL, 862, L1, doi: 10.3847/2041-8213/aad0ee

  76. [78]

    J., Fattahi, A., Frenk, C

    Deason, A. J., Fattahi, A., Frenk, C. S., et al. 2020, MNRAS, 496, 3929, doi: 10.1093/mnras/staa1711

  77. [79]

    R., Koposov, S

    Dey, A., Najita, J. R., Koposov, S. E., et al. 2023, ApJ, 944, 1, doi: 10.3847/1538-4357/aca5f8

  78. [80]

    D., & Bekki, K

    Diaz, J. D., & Bekki, K. 2012, ApJ, 750, 36, doi: 10.1088/0004-637X/750/1/36

  79. [81]

    S., et al

    Ding, J., Rockosi, C., Li, T. S., et al. 2025, ApJ, 994, 134, doi: 10.3847/1538-4357/ae0a37

  80. [82]

    Ding, K., Filion, C., Wyse, R. F. G., et al. 2025, AJ, 170, 327, doi: 10.3847/1538-3881/ae10a7

Showing first 80 references.