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CosmoGEMS builds globular cluster stellar streams star by star in a fully cosmological, time-evolving galactic potential, and shows that clumps, shells, and orbital-plane precession arise from episodic tidal stripping and potential evolutio

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 →

A new framework produces globular cluster stellar streams star by star using a time-evolving cosmological Milky Way potential, revealing orbital plane precession and episodic stripping effects.

T0 review reviewed 2026-08-05 challenge →

load-bearing objection A genuinely new integration of CMC escapers with a time-evolving BFE potential from the same FIRE simulation, showing plausible stream morphologies from two examples; the main soft spot is that stream-level convergence against BFE snapshot cadence is not demonstrated. the 3 major comments →

arxiv 2509.03599 v1 pith:J3KLLIAM submitted 2025-09-03 astro-ph.GA

Breaking Down the $\textsf{CosmoGEMS}$: Toward Modeling and Understanding Globular Cluster Stellar Streams in a Fully Cosmological Context

classification astro-ph.GA
keywords globular cluster streamscosmological simulationsFIRE simulationsbasis function expansiontidal strippingorbital precessionstream morphologystellar streams
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.

The reading

This paper presents a pipeline, CosmoGEMS, that produces globular cluster stellar streams one star at a time inside a fully cosmological Milky Way-like simulation, rather than in a static, hand-built galactic potential. Stars are stripped from their clusters by a collisional cluster model, and then each escaped star is integrated forward in the time-evolving potential of the same simulated galaxy. Applying the pipeline to two example clusters, the paper shows that realistic stream features—density clumps, thin-plus-shell double components, and misaligned stream tracks—emerge naturally from episodic tidal stripping and from evolution of the progenitor's orbit, including precession of the orbital plane. The authors argue this challenges common assumptions in stream-finding and stream-modeling tools, which treat stream stars as tracing a single fixed orbit. The framework is a proof of concept aimed at predicting what next-generation surveys will see.

Core claim

CosmoGEMS couples three previously separate modeling layers into one chain: cluster formation from giant molecular clouds in the FIRE m12i simulation, collisional cluster evolution with CMC, and orbit integration of every escaped star in a basis-function-expanded, time-dependent potential of the same host galaxy. The central demonstration is that two clusters on different eccentric orbits produce qualitatively different streams. GC1, on a milder orbit, yields a long cold stream with velocity dispersion below 5 km/s and a local density clump; GC2, on a more eccentric orbit, produces a thin stream segment embedded in a diffuse shell, similar to features observed in the Jhelum stream. Both stre

What carries the argument

The load-bearing piece is the time-evolving basis-function-expansion (BFE) representation of the host galaxy potential, built from each snapshot of the FIRE m12i simulation. It feeds two stages: CMC uses the tidal tensor to strip stars, and the escaped stars are integrated in the time-interpolated BFE potential plus a Plummer model of the cluster's own gravity. The BFE's limited snapshot cadence (about 20 Myr) is what forces the analysis to the last 2 Gyr of stream formation.

Load-bearing premise

The reconstructed time-evolving potential, built from snapshots spaced about 20 million years apart, faithfully reproduces the real gravitational forces over the full integration; the paper's own orbit checks show growing divergence, so any stream structure older than about 2 Gyr could be an artifact of the snapshot cadence.

What would settle it

Run the same CMC escape lists through a higher-cadence potential reconstruction, with snapshots every 2–5 Myr instead of 20 Myr, and check whether the GC1 clump, the GC2 thin-plus-shell split, and the orbital-phase-dependent track misalignment persist; if they shift or vanish, those morphological claims are artifacts of BFE cadence. On the observational side, measure the orbital-plane precession of real Milky Way globular clusters over the last few Gyr and ask whether precession of tens of degrees is typical.

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

If this is right

  • Stream-finding tools that assume a fixed great circle or a single progenitor orbit will misclassify cosmological streams, so physics-agnostic search methods may perform better.
  • Clumps and thin-plus-shell morphologies can arise from orbital phase and potential evolution alone, without requiring exotic dark subhalo encounters.
  • Velocity dispersion along a stream is not a clean proxy for progenitor mass in an evolving potential.
  • Streams are reliable probes of the Galactic potential only back to about 2 Gyr at the current snapshot cadence; older escapers are too phase-mixed or orbitally unreliable.
  • Survey-depth mass cuts do not change the apparent width or length of the GC1 stream, so shallow surveys see the same overall stream shape.

Where Pith is reading between the lines

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

  • If the 2 Gyr cutoff is typical for cosmological stream models, population-level predictions will systematically undercount old, phase-mixed stream material; higher-cadence potential reconstructions or live-force reruns would be needed to recover it.
  • Precession rates of 10–30 degrees over 2 Gyr imply that fitting observed stream tracks with fixed orbital poles may bias Milky Way halo shape constraints; marginalizing over time-varying pole directions would be a testable extension.
  • The clump in GC1, tentatively attributed to a disk interaction about 1 Gyr ago, suggests a concrete observational search: look for similar density clumps in real streams on disk-aligned, retrograde orbits near apocenter.
  • Because both example clusters ejected all their black holes more than 8 Gyr ago and their orbits have since changed, the model implies that black holes like Gaia BH3 should rarely be found near present-day stream tracks; a detection would challenge the assumption of orbit stability.
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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

3 major / 5 minor

Summary. The paper presents CosmoGEMS, a post-processing pipeline that produces globular cluster (GC) stellar streams star-by-star in a fully cosmological context. It combines (1) the FIRE m12i zoom-in cosmological simulation, (2) a cluster formation model (Grudić et al. 2023) followed by collisional evolution with CMC (Rodriguez et al. 2023), and (3) orbit integration of escaped stars in a time-dependent basis-function-expansion (BFE) potential of the host galaxy. Two example GC streams are presented: GC1, on a less eccentric orbit, forms a long, thin stream with an internal velocity dispersion below ~5 km/s, a local overdensity ('clump'), and an orbital-phase-dependent stream-track misalignment; GC2, on a more eccentric orbit, develops both a thin tail and a diffuse shell-like component. The authors argue these morphologies arise naturally from episodic tidal stripping and a time-evolving Galactic potential, and they discuss implications for stream-finding methods that assume static potentials or fixed orbital planes.

Significance. If the numerical concerns are resolved, CosmoGEMS is a significant step forward. It is the first framework to connect star-by-star GC escape with a fully cosmological, time-evolving host potential, and the stream features are emergent rather than fitted to observations. The use of published, independently tested codes (FIRE, CMC, BFE) and the explicit acknowledgment of limitations are strengths. The resulting streams could serve as a realistic testbed for stream-finding algorithms and for interpreting upcoming survey data. However, the current paper is a proof of concept with two clusters, and the central physical claims depend on the accuracy of the BFE potential reconstruction over the relevant integration time.

major comments (3)
  1. [Sections 2.3.1, 2.3.3, 4.5; Figure 3] The orbit validation shows growing phase shifts, especially for GC2, and the analysis is restricted to the last 2 Gyr because of this. However, the key features—GC1's clump at phi1≈140°, the stream-track misalignment in Figure 9, and GC2's thin tail—are built from stars that escaped 1–2 Gyr ago, exactly the population with the largest accumulated integration error. The convergence tests in §4.5 vary ell_max, timestep, and integrator, but not the temporal cadence of the BFE snapshots or the resulting stream morphology. Because the streams are cold (σ<~5 km/s) and the misalignments are degree-level, systematic BFE force errors could plausibly create or mask these features. Please provide a test of sensitivity to the BFE time sampling—e.g., using every other snapshot, or perturbing the BFE coefficients at the level of reported force errors—and show that the clump and track misalignment are
  2. [Section 3.2] The GC1 clump is presented as a key result, but its physical origin is not established. The proposed explanation (interaction with a massive subhalo plus apocentric pile-up) rests on a timing coincidence: the clump contains stars that escaped 1–2 Gyr ago, and a subhalo reached pericenter ~1 Gyr ago. The paper itself states 'Further investigation is required.' For the abstract's claim that the clump arises from the evolving potential, a direct test is needed—e.g., re-running the integration without the subhalo encounter, or in a smoothed/static potential—to check whether the clump persists. Without such a test, the causal attribution is speculative.
  3. [Sections 2.3.3 and 2.4] Escaped stars are injected at tej with isotropic angular position and velocity direction. In reality, stars escape through the Lagrange points, so the escape direction is correlated with the cluster's orbital phase and the tidal field orientation. This approximation could affect the leading/trailing arm asymmetry (GC1) and the thin-tail selection (GC2). The paper does not test the sensitivity of the final stream morphology to this injection prescription. Please either justify the isotropic assumption with a physical argument or a numerical test (e.g., comparing with injection at L1/L2), or demonstrate that the stream features are unchanged when the injection is varied.
minor comments (5)
  1. [Section 2, first paragraph] Typo: 'establing' should be 'establishing'.
  2. [Section 4.5, last paragraph] Typo: 'Cook at al.' should be 'Cook et al.'.
  3. [Section 3.1] The observer is placed at the host galaxy center rather than at a realistic Solar position. This is fine for the proof-of-concept, but consider clarifying how line-of-sight projection would change the appearance, since this may be relevant for comparing with real streams.
  4. [Section 4.1 and Figure 9] The colorbar in Figure 9 is not described in the caption; consider adding a note that red is recent and blue is old, though the text mentions this.
  5. [Section 4.2] The comparison with Balbinot & Gieles (2018) is well framed, but the wording 'only ~1.4–1.5 times their initial masses' is confusing because the initial mass here is defined at 2 Gyr ago; please clarify.

Circularity Check

0 steps flagged

No significant circularity: stream features are emergent outputs; pipeline components are independently validated despite same-group citations.

full rationale

CosmoGEMS treats the FIRE m12i galaxy, GBoF1/2 cluster initial conditions and CMC evolution, and the Arora et al. BFE potential as inputs, then integrates escaped stars forward; none of the target stream properties (GC1 clump at phi1~140 deg, orbital-phase track misalignment, GC2 thin+shell morphology) are used to define the potential, the escape criterion, or any fitted parameter. The rthreshold=100 pc and 2 Gyr integration window are explicit modeling/validation choices (Sections 2.3.3, 2.4, 4.5), not fits to the stream outputs. The heavy self-citation (GBoF1/2, Arora et al.) supplies the input pipeline, but those are published codes with external validation (CMC vs NBODY6, BFE force/orbit checks including Figure 3 in this paper), so the self-citations are real evidence rather than circular premises. The main limitation acknowledged in Section 4.5 is the BFE snapshot cadence (~20 Myr), which motivates restricting analysis to the last 2 Gyr; this is a numerical accuracy concern that could affect old stream stars, but it is not a circularity because the interpretation does not reduce to the reconstruction error by construction. Score 0-2 range: no fitted-input-called-prediction, no self-definitional equivalence, no uniqueness imported from authors.

Axiom & Free-Parameter Ledger

3 free parameters · 4 axioms · 0 invented entities

The framework relies on established simulation codes and a published potential model. The only hand-chosen parameters are the escape distance threshold and the 2 Gyr integration window, neither of which is fitted to reproduce a target stream property.

free parameters (3)
  • rthreshold = 100 pc = 100 pc
    Hand-chosen distance threshold to define the escape time tescp (Equation 5). Affects which stars are counted as escaped and the stream membership.
  • Integration window of 2 Gyr = 2 Gyr
    Chosen because orbit reconstruction in the BFE potential degrades before that; restricts the streams to stars ejected in the last 2 Gyr.
  • Mass bins for detectability analysis = 0.5 and 0.8 Msun cutoffs
    Analysis choices to mimic magnitude limits in the detectability section, not part of the central stream generation.
axioms (4)
  • domain assumption CMC's spherical symmetry and Monte Carlo treatment of two-body encounters reliably predicts cluster mass-loss rates.
    Invoked in Section 2.2 and Section 4.5; the paper notes spherical symmetry may break down during tidal debris production.
  • domain assumption The cluster formation model calibrated to higher-resolution simulations (Grudić et al. 2021) applies to m12i GMCs.
    Used in Step 1 to assign initial cluster properties; the model does not reproduce old metal-poor GCs, as acknowledged.
  • domain assumption The tracer particle in FIRE tracks the cluster's true orbit and the BFE potential accurately reproduces tidal forces.
    Needed in Sections 2.3.1 and 2.3.2; the paper shows orbit reconstruction with growing phase error over time.
  • domain assumption A Plummer sphere with evolving mass and scale radius is an adequate model for the cluster's self-gravity during escape.
    Assumed in Equation 4; the paper notes a single Plummer model may be inaccurate for core-collapsed clusters.

reviewed 2026-08-05 · how reviews work

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Cite this review

Pith. "Pith review of Breaking Down the $\textsf{CosmoGEMS}$: Toward Modeling and Understanding Globular Cluster Stellar Streams in a Fully Cosmological Context." pith.science (2026). https://pith.science/paper/J3KLLIAM

@misc{pith2026250903599,
  author       = {Pith},
  title        = {Pith review of: Breaking Down the $\textsfCosmoGEMS$: Toward Modeling and Understanding Globular Cluster Stellar Streams in a Fully Cosmological Context},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/J3KLLIAM}},
  note         = {Machine review of arXiv:2509.03599}
}
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abstract

Next-generation surveys are expected to uncover thousands of globular cluster (GC) stellar streams, motivating the need for a theoretical framework that produces realistic GC streams in a fully cosmological, Milky Way-like environment. We present $\textsf{CosmoGEMS}$, a star-by-star cosmological GC stream framework that self-consistently links small-scale cluster physics with large-scale Galactic dynamics. The initial phase-space positions of stream stars are informed by post-processed GC populations within the FIRE cosmological simulation. Escaped stars are orbit-integrated from their time of escape to the present day in a time-evolving Galactic potential extracted from the same simulation using a basis function expansion. We explore two example streams on different orbits. One forms a long, thin stream with a velocity dispersion consistent with Milky Way GC streams. However, it exhibits a clump and orbital-phase-dependent misalignments due to the evolving potential. The other stream develops both a thin component and a diffuse, shell-like structure, similar to features observed in streams like Jhelum. These results highlight the power of fully cosmological models in producing realistic stream morphologies and kinematics. Unlike idealized simulations, our models naturally incorporate time-dependent changes in the progenitor's orbit, including orbital plane evolution, which significantly affects stream structure. This challenges common assumptions in stream-finding algorithms and interpretation. $\textsf{CosmoGEMS}$ provides a key step toward connecting future stellar stream observations with the physics of globular cluster evolution and hierarchical galaxy formation in a cosmological context.

Figures

Figures reproduced from arXiv: 2509.03599 by Ana Bonaca, Arpit Arora, Brian T. Cook, Carl L. Rodriguez, Newlin C. Weatherford, Nondh Panithanpaisal, Philip F. Hopkins, Robyn E. Sanderson, Sarah Pearson, Tjitske Starkenburg.

Figure 1
Figure 1. Figure 1: A diagram describing steps in our cosmological GC stream production pipeline, CosmoGEMS. In step 1, the initial cluster properties were derived from applying struc￾ture finder and cluster formation model on the FIRE m12i simulation snapshots (Grudi´c et al. 2023). Next, these ini￾tial clusters were evolved to z = 0 using the collisional CMC model (Rodriguez et al. 2023) in step 2. Finally, in step 3, we tr… view at source ↗
Figure 2
Figure 2. Figure 2: Properties of GC1 and GC2 as a function of look-back time in blue and red, respectively. The top panel shows the the 3D galactocentric (physical) distances of the clusters, rgal. The middle panel shows the cluster masses, in log scale. The bottom panel shows the distributions of the number of stars “ejected” from the clusters, Nej , informed by CMC. Both clusters experience episodic mass-loss, where the st… view at source ↗
Figure 3
Figure 3. Figure 3: Comparisons between the true (solid) and the integrated (dashed) orbits for GC1 and GC2 in blue and red, respectively. The solid lines are identical to the cluster orbits shown in [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: GC1 and GC2 streams (44045 and 19206 stars, respectively) shown in 4 different age bins: 0.36, 0.78, 1.50, and 2.10 Gyr. GC1, on a less eccentric orbit, forms a relatively cold and long stream. GC2, on a more eccentric orbit, forms a shell-like structure. Equation 10 in Renaud et al. 2011): rtidal =  GMGC λe,1 1/3 , (6) where MGC is mass of the cluster, and λe,1 is the largest eigenvalue of the tidal ten… view at source ↗
Figure 5
Figure 5. Figure 5: Top: The GC1 stream at the present day in stream-aligned coordinates. There is an asymmetry in the lengths of the leading and trailing arms. Middle: The ϕ1 distribution of all stream stars. Bottom: The 3D velocity dispersion, σ, along the stream, binned uniformly in ϕ1 with a bin size of approximately 2◦ . The dotted line (magenta) shows the estimated 1D velocity dispersion. σ is lowest near the progenitor… view at source ↗
Figure 7
Figure 7. Figure 7: Orbits of the GC2 stream stars and its progenitor. The orbits of all the stream stars, stars that comprised the thin tail, and the progenitor are shown in gray, blue, and red, respectively. At the present day, the progenitor is located near the apocenter, while the stars belonging to the thin tail. time-dependent gravitational torque that causes the or￾bital angular momentum vector to precess chaotically. … view at source ↗
Figure 6
Figure 6. Figure 6: Subsets of the GC1 stream stars at the present day in the (ϕ1, ϕ2) coordinates grouped by their escape times, tescp. All of the stream stars are plotted in the top panel (identical to [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: The precession of GC1 and GC2’s orbital planes over time. The orbital tilt is define as the angle between the total angular momentum vector of the progenitor at time t and at the present day. focus on the interesting time-dependent stream features as well as the observational implications. 4.1. Orbital-phase dependent stream track misalignment It has been shown that stellar streams, whether on cir￾cular or… view at source ↗
Figure 9
Figure 9. Figure 9: The orbital-phase dependent misalignment of the stream track. Each panel shows the GC1 stream in the stream￾aligned coordinates in different time bins. The progenitor is located at ϕ1 = 0◦ and its velocity vector is shown by the black arrow. The color represents the time that each star escaped from the cluster, tescp. The inset plots on the right show the orbital phases of the progenitor. The stream track … view at source ↗
Figure 10
Figure 10. Figure 10: Bar charts showing the fraction of escaped high-mass (red; 0.8 < M/M⊙ < 1.0), intermediate-mass (green; 0.5 < M/M⊙ < 0.8), and low-mass (blue; M < 0.5M⊙) stars in each episode. The left panel displays the data for GC1 (10 stripping episodes), while the right panel shows the data for GC2 (7 stripping episodes). The x-axis labels indicate the average time of each stripping episode [PITH_FULL_IMAGE:figures/… view at source ↗
Figure 11
Figure 11. Figure 11: The detectability of the GC1 stream as viewed in different stellar mass bins. The top three panels show stream stars with mass 0 < M/M⊙ < 1, 0.5 < M/M⊙ < 1, and 0.8 < M/M⊙ < 1, respectively. The bottom panel shows the normalized histograms of the stream stars in both ϕ1 and ϕ2. of the CMC. However, a single Plummer model may not accurately capture the progenitor’s density profile at all evolutionary stage… view at source ↗

discussion (0)

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Forward citations

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Reference graph

Works this paper leans on

92 extracted references · 7 canonical work pages · cited by 2 Pith papers

  1. [1]

    2024, ApJ, 962, 151, doi: 10.3847/1538-4357/ad159c

    Aganze, C., Pearson, S., Starkenburg, T., et al. 2024, ApJ, 962, 151, doi: 10.3847/1538-4357/ad159c

  2. [2]

    2014, MNRAS, 442, 1265, doi: 10.1093/mnras/stu899

    Baumgardt, H. 2014, MNRAS, 442, 1265, doi: 10.1093/mnras/stu899

  3. [3]

    Amorisco, N. C. 2015, MNRAS, 450, 575, doi: 10.1093/mnras/stv648

  4. [4]

    C., G´ omez, F

    Amorisco, N. C., G´ omez, F. A., Vegetti, S., & White, S. D. M. 2016, MNRAS, 463, L17, doi: 10.1093/mnrasl/slw148

  5. [5]

    E., Panithanpaisal, N., et al

    Arora, A., Sanderson, R. E., Panithanpaisal, N., et al. 2022, ApJ, 939, 2, doi: 10.3847/1538-4357/ac93fb

  6. [6]

    2024, ApJ, 977, 23, doi: 10.3847/1538-4357/ad88f0

    Arora, A., Sanderson, R., Regan, C., et al. 2024, ApJ, 977, 23, doi: 10.3847/1538-4357/ad88f0

  7. [7]

    E., et al

    Arora, A., Garavito-Camargo, N., Sanderson, R. E., et al. 2025, ApJ, 988, 190, doi: 10.3847/1538-4357/ade30d

  8. [8]

    2018, MNRAS, 474, 2479, doi: 10.1093/mnras/stx2708

    Balbinot, E., & Gieles, M. 2018, MNRAS, 474, 2479, doi: 10.1093/mnras/stx2708

  9. [9]

    2023, A&A, 678, A115, doi: 10.1051/0004-6361/202347076

    Balbinot, E., Helmi, A., Callingham, T., et al. 2023, A&A, 678, A115, doi: 10.1051/0004-6361/202347076

  10. [10]

    2024, A&A, 687, L3, doi: 10.1051/0004-6361/202450425

    Balbinot, E., Dodd, E., Matsuno, T., et al. 2024, A&A, 687, L3, doi: 10.1051/0004-6361/202450425

  11. [11]

    Banik, N., Bovy, J., Bertone, G., Erkal, D., & de Boer, T. J. L. 2021, JCAP, 2021, 043, doi: 10.1088/1475-7516/2021/10/043

  12. [13]

    2003, MNRAS, 340, 227, doi: 10.1046/j.1365-8711.2003.06286.x

    Baumgardt, H., & Makino, J. 2003, MNRAS, 340, 227, doi: 10.1046/j.1365-8711.2003.06286.x

  13. [14]

    2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441

    Bland-Hawthorn, J., & Gerhard, O. 2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441

  14. [15]

    M., & Hogg, D

    Bonaca, A., Conroy, C., Price-Whelan, A. M., & Hogg, D. W. 2019, ApJL, 881, L37, doi: 10.3847/2041-8213/ab36ba

  15. [16]

    Bonaca, A., Geha, M., K¨ upper, A. H. W., et al. 2014, ApJ, 795, 94, doi: 10.1088/0004-637X/795/1/94

  16. [17]

    Bonaca, A., & Price-Whelan, A. M. 2025, NewAR, 100, 101713, doi: 10.1016/j.newar.2024.101713

  17. [18]

    W., et al

    Bonaca, A., Conroy, C., Hogg, D. W., et al. 2020, ApJL, 892, L37, doi: 10.3847/2041-8213/ab800c

  18. [19]

    A., & Davies, M

    Bonnell, I. A., & Davies, M. B. 1998, Monthly Notices of the Royal Astronomical Society, 295, 691, doi: 10.1046/j.1365-8711.1998.01372.x 18

  19. [20]

    2015, ApJS, 216, 29, doi: 10.1088/0067-0049/216/2/29

    Bovy, J. 2015, ApJS, 216, 29, doi: 10.1088/0067-0049/216/2/29

  20. [21]

    K., & Kallivayalil, N

    Bovy, J., Bahmanyar, A., Fritz, T. K., & Kallivayalil, N. 2016, ApJ, 833, 31, doi: 10.3847/1538-4357/833/1/31

  21. [22]

    2020, ApJ, 898, 71, doi: 10.3847/1538-4357/ab9d85

    Breivik, K., Coughlin, S., Zevin, M., et al. 2020, ApJ, 898, 71, doi: 10.3847/1538-4357/ab9d85

  22. [23]

    Cabrera, T., & Rodriguez, C. L. 2023, ApJ, 953, 19, doi: 10.3847/1538-4357/acdc22

  23. [24]

    Carlberg, R. G. 2012, ApJ, 748, 20, doi: 10.1088/0004-637X/748/1/20 —. 2013, ApJ, 775, 90, doi: 10.1088/0004-637X/775/2/90 —. 2020, ApJ, 889, 107, doi: 10.3847/1538-4357/ab61f0

  24. [25]

    Chen, Y., & Gnedin, O. Y. 2022, MNRAS, 514, 4736, doi: 10.1093/mnras/stac1651 —. 2023, MNRAS, 522, 5638, doi: 10.1093/mnras/stad1328 —. 2024, MNRAS, 527, 3692, doi: 10.1093/mnras/stad3345

  25. [26]

    Y., & Ash, N

    Chen, Y., Valluri, M., Gnedin, O. Y., & Ash, N. 2025, ApJS, 276, 32, doi: 10.3847/1538-4365/ad9904

  26. [27]

    2018, MNRAS, 479, 4720, doi: 10.1093/mnras/sty1726

    Dehnen, W., & Hasanuddin. 2018, MNRAS, 479, 4720, doi: 10.1093/mnras/sty1726

  27. [28]

    K., & Rix, H.-W

    Dehnen, W., Odenkirchen, M., Grebel, E. K., & Rix, H.-W. 2004, AJ, 127, 2753, doi: 10.1086/383214

  28. [29]

    E., & Belokurov, V

    Erkal, D., Koposov, S. E., & Belokurov, V. 2017, MNRAS, 470, 60, doi: 10.1093/mnras/stx1208

  29. [30]

    L., & Belokurov, V

    Erkal, D., Sanders, J. L., & Belokurov, V. 2016, MNRAS, 461, 1590, doi: 10.1093/mnras/stw1400

  30. [32]

    A., Huang, S., & Weinberg, M

    Fardal, M. A., Huang, S., & Weinberg, M. D. 2015, MNRAS, 452, 301, doi: 10.1093/mnras/stv1198

  31. [33]

    Fukushige, T., & Heggie, D. C. 2000, MNRAS, 318, 753, doi: 10.1046/j.1365-8711.2000.03811.x Gaia Collaboration, Panuzzo, P., Mazeh, T., et al. 2024, A&A, 686, L2, doi: 10.1051/0004-6361/202449763

  32. [34]

    T., Naidu, R

    Gialluca, M. T., Naidu, R. P., & Bonaca, A. 2021, ApJL, 911, L32, doi: 10.3847/2041-8213/abf491

  33. [35]

    Gibbons, S. L. J., Belokurov, V., & Evans, N. W. 2014, MNRAS, 445, 3788, doi: 10.1093/mnras/stu1986

  34. [36]

    2014, MNRAS, 437, 916, doi: 10.1093/mnras/stt1980

    Baumgardt, H. 2014, MNRAS, 437, 916, doi: 10.1093/mnras/stt1980

  35. [37]

    Y., & Ostriker, J

    Gnedin, O. Y., & Ostriker, J. P. 1997, ApJ, 474, 223, doi: 10.1086/303441 Grudi´ c, M. Y., Hafen, Z., Rodriguez, C. L., et al. 2023, MNRAS, 519, 1366, doi: 10.1093/mnras/stac3573 Grudi´ c, M. Y., Kruijssen, J. M. D., Faucher-Gigu` ere, C.-A., et al. 2021, MNRAS, 506, 3239, doi: 10.1093/mnras/stab1894

  36. [38]

    Y., Hopkins, P

    Guszejnov, D., Grudi´ c, M. Y., Hopkins, P. F., Offner, S. S. R., & Faucher-Gigu` ere, C.-A. 2020, MNRAS, 496, 5072, doi: 10.1093/mnras/staa1883

  37. [39]

    Hattori, K., Erkal, D., & Sanders, J. L. 2016, MNRAS, 460, 497, doi: 10.1093/mnras/stw1006

  38. [40]

    Hendel, D., & Johnston, K. V. 2015, MNRAS, 454, 2472, doi: 10.1093/mnras/stv2035 H´ enon, M. 1971, Ap&SS, 13, 284, doi: 10.1007/BF00649159

  39. [41]

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

  40. [42]

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

    Hopkins, P. F., Wetzel, A., Kereˇ s, D., et al. 2018, MNRAS, 480, 800, doi: 10.1093/mnras/sty1690

  41. [43]

    2024, ApJ, 967, 89, doi: 10.3847/1538-4357/ad382d

    Ibata, R., Malhan, K., Tenachi, W., et al. 2024, ApJ, 967, 89, doi: 10.3847/1538-4357/ad382d

  42. [44]

    A., Lewis, G

    Ibata, R. A., Lewis, G. F., Irwin, M. J., & Quinn, T. 2002, MNRAS, 332, 915, doi: 10.1046/j.1365-8711.2002.05358.x

  43. [45]

    2017, ApJ, 842, 120, doi: 10.3847/1538-4357/aa7514 Ivezi´ c,ˇZ., Kahn, S

    Chapman, S. 2017, ApJ, 842, 120, doi: 10.3847/1538-4357/aa7514 Ivezi´ c,ˇZ., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111, doi: 10.3847/1538-4357/ab042c

  44. [46]

    V., Spergel, D

    Johnston, K. V., Spergel, D. N., & Haydn, C. 2002, ApJ, 570, 656, doi: 10.1086/339791

  45. [47]

    J., Rasio, F

    Joshi, K. J., Rasio, F. A., & Portegies Zwart, S. 2000, ApJ, 540, 969, doi: 10.1086/309350

  46. [48]

    I., & Ernst, A

    Just, A., Berczik, P., Petrov, M. I., & Ernst, A. 2009, MNRAS, 392, 969, doi: 10.1111/j.1365-2966.2008.14099.x

  47. [49]

    Rasio, F. A. 2019, ApJ, 871, 38, doi: 10.3847/1538-4357/aaf646

  48. [50]

    Rasio, F. A. 2018, ApJL, 855, L15, doi: 10.3847/2041-8213/aab26c

  49. [51]

    2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x K¨ upper, A

    Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x K¨ upper, A. H. W., Balbinot, E., Bonaca, A., et al. 2015, ApJ, 803, 80, doi: 10.1088/0004-637X/803/2/80 K¨ upper, A. H. W., Lane, R. R., & Heggie, D. C. 2012, MNRAS, 420, 2700, doi: 10.1111/j.1365-2966.2011.20242.x K¨ upper, A. H. W., MacLeod, A., & Heggie, D. C. 2008, MNRAS, 387, 12...

  50. [52]

    B., Ferguson, A

    Kuzma, P. B., Ferguson, A. M. N., Varri, A. L., et al. 2022, MNRAS, 512, 315, doi: 10.1093/mnras/stac381

  51. [53]

    R., K¨ upper, A

    Lane, R. R., K¨ upper, A. H. W., & Heggie, D. C. 2012, MNRAS, 423, 2845, doi: 10.1111/j.1365-2966.2012.21093.x

  52. [54]

    2011, arXiv e-prints, arXiv:1110.3193, doi: 10.48550/arXiv.1110.3193 19

    Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, arXiv e-prints, arXiv:1110.3193, doi: 10.48550/arXiv.1110.3193 19

  53. [55]

    S., Ji, A

    Li, T. S., Ji, A. P., Pace, A. B., et al. 2022, ApJ, 928, 30, doi: 10.3847/1538-4357/ac46d3

  54. [56]

    Malhan, K., & Ibata, R. A. 2018, MNRAS, 477, 4063, doi: 10.1093/mnras/sty912

  55. [57]

    2023, MNRAS, 520, 5225, doi: 10.1093/mnras/stad321

    Mateu, C. 2023, MNRAS, 520, 5225, doi: 10.1093/mnras/stad321

  56. [58]

    P., Font, A

    Mateu, C., Cooper, A. P., Font, A. S., et al. 2017, Monthly Notices of the Royal Astronomical Society, 469, 721, doi: 10.1093/mnras/stx872

  57. [59]

    McMillan, P. J. 2017, MNRAS, 465, 76, doi: 10.1093/mnras/stw2759

  58. [60]

    C., Evans, N

    Myeong, G. C., Evans, N. W., Belokurov, V., Koposov, S. E., & Sanders, J. L. 2017, MNRAS, 469, L78, doi: 10.1093/mnrasl/slx051

  59. [61]

    2025, arXiv e-prints, arXiv:2504.07187, doi: 10.48550/arXiv.2504.07187

    Nibauer, J., & Bonaca, A. 2025, arXiv e-prints, arXiv:2504.07187, doi: 10.48550/arXiv.2504.07187

  60. [62]

    N., et al

    Nibauer, J., Bonaca, A., Spergel, D. N., et al. 2025, ApJ, 983, 68, doi: 10.3847/1538-4357/adb8e8

  61. [63]

    G., & Miralda-Escud´ e, J

    Palau, C. G., & Miralda-Escud´ e, J. 2023, MNRAS, 524, 2124, doi: 10.1093/mnras/stad1930

  62. [64]

    2013, ApJS, 204, 15, doi: 10.1088/0067-0049/204/2/15

    Pattabiraman, B., Umbreit, S., Liao, W.-k., et al. 2013, ApJS, 204, 15, doi: 10.1088/0067-0049/204/2/15

  63. [65]

    Pearson, S., Bonaca, A., Chen, Y., & Gnedin, O. Y. 2024, ApJ, 976, 54, doi: 10.3847/1538-4357/ad8348

  64. [66]

    E., Demirjian, A

    Pearson, S., Clark, S. E., Demirjian, A. J., et al. 2022, ApJ, 926, 166, doi: 10.3847/1538-4357/ac4496

  65. [67]

    Price-Whelan, A. M. 2015, ApJ, 799, 28, doi: 10.1088/0004-637X/799/1/28

  66. [68]

    M., & Johnston, K

    Pearson, S., Price-Whelan, A. M., & Johnston, K. V. 2017, Nature Astronomy, 1, 633, doi: 10.1038/s41550-017-0220-3

  67. [69]

    K., Johnston, K

    Pearson, S., Starkenburg, T. K., Johnston, K. V., et al. 2019, ApJ, 883, 87, doi: 10.3847/1538-4357/ab3e06

  68. [70]

    Price-Whelan, A. M. 2017, The Journal of Open Source Software, 2, 388, doi: 10.21105/joss.00388

  69. [71]

    M., & Bonaca, A

    Price-Whelan, A. M., & Bonaca, A. 2018, ApJL, 863, L20, doi: 10.3847/2041-8213/aad7b5

  70. [72]

    M., Mateu, C., Iorio, G., et al

    Price-Whelan, A. M., Mateu, C., Iorio, G., et al. 2019, AJ, 158, 223, doi: 10.3847/1538-3881/ab4cef

  71. [73]

    M., Sanderson, R

    Reino, S., Rossi, E. M., Sanderson, R. E., et al. 2021, MNRAS, 502, 4170, doi: 10.1093/mnras/stab304

  72. [75]

    Roberts, D., Gieles, M., Erkal, D., & Sanders, J. L. 2025, MNRAS, 538, 454, doi: 10.1093/mnras/staf321

  73. [76]

    L., Hafen, Z., Grudi´ c, M

    Rodriguez, C. L., Hafen, Z., Grudi´ c, M. Y., et al. 2023, MNRAS, 521, 124, doi: 10.1093/mnras/stad578

  74. [77]

    L., Weatherford, N

    Rodriguez, C. L., Weatherford, N. C., Coughlin, S. C., et al. 2022, ApJS, 258, 22, doi: 10.3847/1538-4365/ac2edf

  75. [78]

    L., & Binney, J

    Sanders, J. L., & Binney, J. 2013a, MNRAS, 433, 1813, doi: 10.1093/mnras/stt806 —. 2013b, MNRAS, 433, 1826, doi: 10.1093/mnras/stt816

  76. [79]

    R., & Necib, L

    Shih, D., Buckley, M. R., & Necib, L. 2024, MNRAS, 529, 4745, doi: 10.1093/mnras/stae446

  77. [80]

    R., Necib, L., & Tamanas, J

    Shih, D., Buckley, M. R., Necib, L., & Tamanas, J. 2022, MNRAS, 509, 5992, doi: 10.1093/mnras/stab3372

  78. [81]

    2020, MNRAS, 495, 2222, doi: 10.1093/mnras/staa1209

    Sollima, A. 2020, MNRAS, 495, 2222, doi: 10.1093/mnras/staa1209

  79. [82]

    2015, arXiv e-prints, arXiv:1503.03757, doi: 10.48550/arXiv.1503.03757

    Spergel, D., Gehrels, N., Baltay, C., et al. 2015, arXiv e-prints, arXiv:1503.03757, doi: 10.48550/arXiv.1503.03757

  80. [83]

    1987, Dynamical evolution of globular clusters

    Spitzer, L. 1987, Dynamical evolution of globular clusters

Showing first 80 references.

This paper was first reviewed by deepseek-v4-flash on August 5, 2026.