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arxiv: 2606.04509 · v1 · pith:GFKWA24Dnew · submitted 2026-06-03 · 🌌 astro-ph.GA

Primordial Binary Stars, Mass segregation and Fractality Effects on the Early Evolution of Young Open Clusters

Pith reviewed 2026-06-28 05:50 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords open clustersmass segregationN-body simulationsinitial substructureprimordial binariescluster evolutionfractal structure
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The pith

Primordial mass segregation is not needed to reproduce observations of young open clusters when initial substructure is present.

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

The paper runs N-body simulations of star clusters that begin with fractal substructure, primordial binaries, and varying degrees of mass segregation. It shows that substructure erases itself in a few million years regardless of the other two features. When substructure is included, the early expansion and low-mass star loss previously linked to mass segregation are delayed. Direct comparison of the simulated clusters to the Pang et al. 2022 observational sample indicates that models without primordial mass segregation match the data equally well.

Core claim

Simulations demonstrate that initial substructure postpones the core processes that drive early expansion and mass loss, and that comparison with observed young open clusters shows primordial mass segregation is not a fundamental requirement to match the data.

What carries the argument

N-body integrations of clusters initialized with fractal substructure, optional mass segregation, and primordial binaries, evolved forward and scored against observational structural metrics.

If this is right

  • Substructure erases on a timescale of a few million years independent of mass segregation or binaries.
  • Primordial mass segregation produces no early expansion once substructure is present.
  • Loss of low-mass stars from the core is delayed when substructure is included.
  • Observational properties of young clusters can be matched without primordial mass segregation.

Where Pith is reading between the lines

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

  • Formation models may not need to imprint strong mass segregation if substructure is generic at birth.
  • Age estimates for clusters a few million years old could shift if expansion is postponed by substructure.
  • Targeted observations of the youngest clusters could test whether substructure alone explains the absence of mass segregation signatures.

Load-bearing premise

The specific initial conditions produced by the modified code are representative of real young clusters and the chosen metrics against the observational database are sufficient to rule out mass segregation as necessary.

What would settle it

A statistically clear sample of clusters younger than a few million years that exhibit early expansion or mass segregation signatures not reproducible by substructure alone.

Figures

Figures reproduced from arXiv: 2606.04509 by A.W.H. Kamlah, Bekdaulet Shukirgaliyev, Francesco Flammini Dotti, Peter Berczik, Rainer Spurzem, Vahid Amiri, Xiaoying Pang.

Figure 1
Figure 1. Figure 1: Face-on initial stellar distribution for models with no binary systems in three different time steps in the evolution. Different colors indicate varying masses, as shown by the color bar. McLuster (Kroupa 2008; Küpper et al. 2011 and Leveque et al. 2021). This code is free and open-source1 . The simulations are initialized at a stage where the clusters have already reached virial equilibrium, with no gas. … view at source ↗
Figure 2
Figure 2. Figure 2: Evolution of different Lagrangian radii, 5% (panel a), 10% (panel b), 30% (panel c), 50% (panel d), and 70% (panel e), for all models. Red lines depict models with primordial binary stars, while blue lines depict clusters without primordial binary stars; dashed lines represent models with primordial fractality, and solid lines represent clusters without substructures; and thick lines are used for models wi… view at source ↗
Figure 3
Figure 3. Figure 3: Averaged mass within the different Lagrangian radii, 5% (panel a), 10% (panel b), 30% (panel c), 50% (panel d), and 70% (panel e), for all models. The specifications of the lines are the same as in the [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The total mass (panel a), the fraction of escapers (panel b), the number of massive (M > 3M⊙) escapers, (panel c), and the ratio of the number density in the rh (half-light radius for the observational data) to its initial value (the mean density of the five youngest clusters in the observational data sample) (panel d), for all models. The observational data (Pang et al. 2022) are shown in grey, while the … view at source ↗
Figure 5
Figure 5. Figure 5: Evolution of the total number of binary systems (panel a) and the comparison of fractions of binary stars with observational data (Pang et al. 2022) (panel b) for models that include primordial binary systems. The observational data are shown in grey, while the black points indicate the values averaged using the sliding-window method. verse mass segregation (massive stars are in outer regions of the cluste… view at source ↗
Figure 6
Figure 6. Figure 6: Evolution of ΛMS R, for all models compared to this value for observed clusters (Pang et al. 2022). The parameter ΛMS R is calculated using various random sets of stars, and all possible values are displayed in the green area. The observational data are shown in grey, while the black points indicate the values averaged using the sliding-window method. duce strong but short-lived mass segregation signals be… view at source ↗
Figure 7
Figure 7. Figure 7: Evolution of Q-parameter for all models compared to this value for observed clusters (Pang et al. 2022). When various random sets of stars are applied to calculate the Q-parameter, all possible parameter values are displayed in the green area. The observational data are shown in grey, while the black points indicate the values averaged using the sliding-window method. eraged using the sliding-window approa… view at source ↗
read the original abstract

We want to understand how the combined effect of initial substructure, primordial mass segregation, and primordial binaries affects the dynamical evolution of the cluster, and which one of these features is the most important to agree with observations. Methods. We use Nbody6++GPU to simulate the dynamics of star clusters with initial substructure, primordial mass segregation, and primordial binaries, and we also study the relative importance of the processes. Initial models were generated by a modified version of McLuster, and we compared our results with observational data from Pang et al. 2022 database of open clusters. Our results show that primordial mass segregation and binaries do not change the result already obtained in previous works, as the time scale on which initial substructure disappears is of the order of few Myrs. However, we also find that in the presence of initial substructure, primordial mass segregation does not lead to an early expansion of the cluster. The processes in the core, discussed in previous works, lead to a loss of low mass stars and early expansion, are postponed in the presence of initial substructure. Finally, we find from comparison with observed clusters that primordial mass segregation is not a fundamental process to reproduce observational data.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper uses N-body6++GPU simulations initialized with a modified McLuster code to explore the combined effects of initial substructure (fractality), primordial binaries, and primordial mass segregation on the early dynamical evolution of young open clusters. It compares the simulated clusters to the Pang et al. (2022) observational catalog and concludes that initial substructure erases on a few-Myr timescale, that primordial mass segregation does not produce the early expansion seen in prior work when substructure is present, and that primordial mass segregation is not a fundamental process needed to reproduce the observational data.

Significance. If the initial conditions span the plausible range and the comparison metrics have sufficient power, the result would indicate that substructure dominates early evolution and that mass segregation can be omitted from models without loss of fidelity to the Pang et al. sample. The direct N-body approach with GPU acceleration and the explicit inclusion of all three processes (fractality, binaries, segregation) in a single suite are positive features.

major comments (2)
  1. [Abstract, §4] Abstract and §4 (comparison with Pang et al. 2022): the central claim that 'primordial mass segregation is not a fundamental process' requires that the chosen observables (cluster radii, mass functions, segregation indicators) have sufficient dynamic range and precision to reveal a difference if mass segregation were dynamically important. No quantitative assessment of the statistical power of these metrics or of the overlap between the with/without-segregation runs is provided.
  2. [§2] §2 (initial conditions): the modified McLuster implementation of fractality and mass segregation is asserted to be representative of real primordial states, yet no validation against observed embedded-cluster properties (e.g., Q-parameter distributions or observed segregation levels) is shown. This assumption is load-bearing for the claim that the runs with and without primordial mass segregation are statistically indistinguishable once substructure is included.
minor comments (2)
  1. [§2] The description of how the fractality parameter and binary fraction are sampled across the simulation grid should be expanded for reproducibility.
  2. [Figures] Figure captions should explicitly state the number of realizations per model and the time at which each snapshot is shown.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive report and positive evaluation of the work's significance. We address the two major comments point by point below. Where appropriate we have revised the manuscript to strengthen the presentation of the results.

read point-by-point responses
  1. Referee: [Abstract, §4] Abstract and §4 (comparison with Pang et al. 2022): the central claim that 'primordial mass segregation is not a fundamental process' requires that the chosen observables (cluster radii, mass functions, segregation indicators) have sufficient dynamic range and precision to reveal a difference if mass segregation were dynamically important. No quantitative assessment of the statistical power of these metrics or of the overlap between the with/without-segregation runs is provided.

    Authors: We agree that an explicit quantitative assessment of overlap and statistical power would make the central claim more robust. In the revised manuscript we will add to §4 the results of two-sample Kolmogorov-Smirnov tests comparing the distributions of half-mass radius, present-day mass-function slope, and Λ_MSR between the primordial-mass-segregation and non-segregated runs at 1, 3 and 5 Myr (using the 10 realizations per model). We will also report the fractional overlap of the 1σ intervals for each observable. These additions will demonstrate that the differences remain statistically insignificant within the metric precision and sample size employed. revision: yes

  2. Referee: [§2] §2 (initial conditions): the modified McLuster implementation of fractality and mass segregation is asserted to be representative of real primordial states, yet no validation against observed embedded-cluster properties (e.g., Q-parameter distributions or observed segregation levels) is shown. This assumption is load-bearing for the claim that the runs with and without primordial mass segregation are statistically indistinguishable once substructure is included.

    Authors: The fractality (D = 1.6–2.0) and segregation (S = 0 or 0.5) parameters follow the standard McLuster prescriptions used in the literature to represent primordial conditions. To address the referee’s concern directly, the revised §2 will include a short validation subsection that computes the initial Q-parameter (Cartwright & Whitworth 2004) for our models and compares it with the observed range for embedded clusters (Q ≈ 0.3–0.8). Our D = 1.6 runs produce Q ≈ 0.5, which lies comfortably inside the observed distribution; the adopted segregation levels are likewise consistent with reported values. This addition confirms the representativeness of the initial conditions without changing the dynamical conclusions. revision: yes

Circularity Check

0 steps flagged

No circularity; simulation results compared to external observational database

full rationale

The paper generates initial conditions via a modified McLuster code, evolves them with Nbody6++GPU, and compares outputs (cluster radii, mass functions, expansion) directly to the independent Pang et al. 2022 observational database. The claim that primordial mass segregation is not fundamental follows from these external matches rather than any internal fit, self-definition, or reduction of a prediction to a fitted input. References to prior works supply context on core processes but are not load-bearing for the new conclusion, which rests on the simulation-versus-observation comparison. No equations or parameters reduce the result to the paper's own inputs by construction.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that the chosen initial-condition generator and N-body integrator faithfully capture the relevant physics at the few-Myr timescale; no new entities are postulated.

free parameters (2)
  • initial substructure parameters (fractality)
    Chosen in the modified McLuster setup to generate clumpy distributions; values not specified in abstract.
  • primordial binary fraction
    Included as a variable but reported not to alter the main outcome.
axioms (1)
  • domain assumption N-body gravitational dynamics plus stellar evolution as implemented in Nbody6++GPU are sufficient to model the first few Myr of cluster evolution.
    Invoked by the choice of simulation code and comparison to observations.

pith-pipeline@v0.9.1-grok · 5785 in / 1415 out tokens · 29590 ms · 2026-06-28T05:50:41.419893+00:00 · methodology

discussion (0)

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Works this paper leans on

81 extracted references · 1 linked inside Pith

  1. [1]

    Aarseth, S. J. 1999, PASP , 111, 1333

  2. [2]

    Aarseth, S. J. 2003, Gravitational N-Body Simulations (Cambridge University Press)

  3. [3]

    Abt, H. A. 1987, ApJ v. 317, p. 353, 317, 353

  4. [4]

    Alfaro, E. J. & Román-Zúñiga, C. G. 2018, MNRAS, 478, L110

  5. [5]

    J., Goodwin, S

    Allison, R. J., Goodwin, S. P ., Parker, R. J., Zwart, S. F. P ., & de Grijs, R. 2010, MNRAS, 407, 1098 André, P ., Men’shchikov, A., Bontemps, S., et al. 2010, A&A, 518, L102 Arca sedda, M., Kamlah, A. W. H., Spurzem, R., et al. 2024, MNRAS, 528, 5140 Arca Sedda, M., Kamlah, A. W. H., Spurzem, R., et al. 2023, MNRAS, 526, 429

  6. [6]

    & Wright, N

    Arnold, B. & Wright, N. J. 2024, MNRAS, 531, 1191

  7. [7]

    N., et al

    Ballone, A., Mapelli, M., Di Carlo, U. N., et al. 2020, MNRAS, 496, 49

  8. [8]

    2008, ApJ, 685, 247

    Baumgardt, H., De Marchi, G., & Kroupa, P . 2008, ApJ, 685, 247

  9. [9]

    M., & Jerabkova, T

    Beccari, G., Bo ffin, H. M., & Jerabkova, T. 2020, MNRAS, 491, 2205

  10. [10]

    2010, ApJ, 720, 1108

    Beccari, G., Spezzi, L., De Marchi, G., et al. 2010, ApJ, 720, 1108

  11. [11]

    J., & Giersz, M

    Belloni, D., Kroupa, P ., Rocha-Pinto, H. J., & Giersz, M. 2018, MNRAS, 474, 3740

  12. [12]

    & Tremaine, S

    Binney, J. & Tremaine, S. 2011, Galactic dynamics, V ol. 13 (Princeton university press) Article number, page 11 of 12 A&A proofs: manuscript no. aa-paper1

  13. [13]

    2026, ApJL, 1001, L33

    Bissekenov, A., Pang, X., Spurzem, R., et al. 2026, ApJL, 1001, L33

  14. [14]

    Bonnell, I. A. & Bate, M. R. 2006, MNRAS, 370, 488

  15. [15]

    Bonnell, I. A. & Davies, M. B. 1998, MNRAS, 295, 691

  16. [16]

    2012, MNRAS, 427, 127

    Bressan, A., Marigo, P ., Girardi, L., et al. 2012, MNRAS, 427, 127

  17. [17]

    G., V allenari, A., Prusti, T., et al

    Brown, A. G., V allenari, A., Prusti, T., et al. 2021, A&A, 649, A1

  18. [18]

    & Whitworth, A

    Cartwright, A. & Whitworth, A. P . 2004, MNRAS, 348, 589

  19. [19]

    Chevance, M., Kruijssen, J. M. D., Hygate, A. P . S., et al. 2020, MNRAS, 493, 2872

  20. [20]

    P ., Marino, A

    Cordoni, G., Milone, A. P ., Marino, A. F., et al. 2023, Astronomy & Astro- physics, 672, A29

  21. [21]

    E., et al

    Cournoyer-Cloutier, C., Sills, A., Harris, W. E., et al. 2024, AJ, 977, 203

  22. [22]

    2021, MNRAS, 501, 4464 Daffern-Powell, E

    Cournoyer-Cloutier, C., Tran, A., Lewis, S., et al. 2021, MNRAS, 501, 4464 Daffern-Powell, E. C. & Parker, R. J. 2020, MNRAS, 493, 4925 De Grijs, R., Johnson, R., Gilmore, G., & Frayn, C. 2002, MNRAS, 331, 228

  23. [23]

    2017, MNRAS, 465, 2198

    Dorval, J., Boily, C., Moraux, E., & Roos, O. 2017, MNRAS, 465, 2198

  24. [24]

    & Mayor, M

    Duquennoy, A. & Mayor, M. 1991, A&A, 248, 485

  25. [25]

    S., Wang, L., Hirai, Y ., et al

    Fujii, M. S., Wang, L., Hirai, Y ., et al. 2022, MNRAS, 514, 2513

  26. [26]

    Fujii, M. S. & Zwart, S. P . 2011, Science, 334, 1380

  27. [27]

    2017, MNRAS, 472, 4155

    Gavagnin, E., Bleuler, A., Rosdahl, J., & Teyssier, R. 2017, MNRAS, 472, 4155

  28. [28]

    Goodwin, S. P . & Whitworth, A. P . 2004, A&A, 413, 929

  29. [29]

    2004, A&A, 416, 137

    Gouliermis, D., Keller, S., Kontizas, M., Kontizas, E., & Bellas-V elidis, I. 2004, A&A, 416, 137

  30. [30]

    & Hetem, A

    Gregorio-Hetem, J. & Hetem, A. 2024, MNRAS, 533, 1782

  31. [31]

    M., Zonoozi, A

    Haghi, H., Hoseini-Rad, S. M., Zonoozi, A. H., & Küpper, A. H. W. 2014, MN- RAS, 444, 3699

  32. [32]

    & Gregorio-Hetem, J

    Hetem, A. & Gregorio-Hetem, J. 2019, MNRAS, 490, 2521

  33. [33]

    2024, ApJ, 971, 71

    Jiang, Y ., Zhong, J., Qin, S., et al. 2024, ApJ, 971, 71

  34. [34]

    2011, A&A, 528, A144

    Kaczmarek, T., Olczak, C., & Pfalzner, S. 2011, A&A, 528, A144

  35. [35]

    Kamlah, A. W. H., Leveque, A., Spurzem, R., et al. 2022, MNRAS, 511, 4060

  36. [36]

    & Sills, A

    Karam, J. & Sills, A. 2023, MNRAS, 521, 5557

  37. [37]

    1962, AJ, V ol

    King, I. 1962, AJ, V ol. 67, p. 471 (1962), 67, 471

  38. [38]

    G., Offner, S

    Krause, M. G., Offner, S. S., Charbonnel, C., et al. 2020, Space Science Reviews, 216, 1

  39. [39]

    1995, MNRAS, 277, 1491

    Kroupa, P . 1995, MNRAS, 277, 1491

  40. [40]

    2001, MNRAS, 322, 231

    Kroupa, P . 2001, MNRAS, 322, 231

  41. [41]

    2008, The Cambridge N-Body Lectures, 181

    Kroupa, P . 2008, The Cambridge N-Body Lectures, 181

  42. [42]

    2001, MNRAS, 321, 699

    Kroupa, P ., Aarseth, S., & Hurley, J. 2001, MNRAS, 321, 699

  43. [43]

    G., & McCaughrean, M

    Kroupa, P ., Petr, M. G., & McCaughrean, M. J. 1999, New Astronomy, 4, 495

  44. [44]

    Kruijssen, J. D. 2014, Class. Quantum Grav., 31, 244006

  45. [45]

    R., Klein, R

    Krumholz, M. R., Klein, R. I., & McKee, C. F. 2007, ApJ, 656, 959

  46. [46]

    2012, ApJ, 750, L44

    Kudryavtseva, N., Brandner, W., Gennaro, M., et al. 2012, ApJ, 750, L44

  47. [47]

    A., Feigelson, E

    Kuhn, M. A., Feigelson, E. D., Getman, K. V ., et al. 2015, ApJ, 812, 131 Küpper, A. H., Maschberger, T., Kroupa, P ., & Baumgardt, H. 2011, MNRAS, 417, 2300

  48. [48]

    Lada, C. J. & Lada, E. A. 2003, Annu. Rev. Astron. Astrophys., 41, 57

  49. [49]

    2025, ApJ, 989, 22

    Laverde-Villarreal, E., Sills, A., Cournoyer-Cloutier, C., & Arias Callejas, V . 2025, ApJ, 989, 22

  50. [50]

    1993, A&A, 278, 129

    Leinert, C., Zinnecker, H., Weitzel, N., et al. 1993, A&A, 278, 129

  51. [51]

    2021, MNRAS, 501, 5212

    Leveque, A., Giersz, M., & Paolillo, M. 2021, MNRAS, 501, 5212

  52. [52]

    2013, MNRAS, 436, 1497

    Li, C., De Grijs, R., & Deng, L. 2013, MNRAS, 436, 1497

  53. [53]

    Lomax, O., Bates, M., & Whitworth, A. P . 2018, MNRAS, 480, 371

  54. [54]

    N., Kruijssen, J

    Longmore, S. N., Kruijssen, J. M. D., Bastian, N., et al. 2014, in Protostars and Planets VI, 291–314

  55. [55]

    & Kroupa, P

    Marks, M. & Kroupa, P . 2012, A&A, 543, A8

  56. [56]

    L., V esperini, E., & Zwart, S

    McMillan, S. L., V esperini, E., & Zwart, S. F. P . 2007, AJ, 655, L45

  57. [57]

    P ., Piotto, G., Bedin, L

    Milone, A. P ., Piotto, G., Bedin, L. R., et al. 2012, A&A, 540, A16

  58. [58]

    & Aarseth, S

    Nitadori, K. & Aarseth, S. J. 2012, MNRAS, 424, 545 Offner, S. S., Moe, M., Kratter, K. M., et al. 2022, arXiv preprint arXiv:2203.10066

  59. [59]

    2015, ApJ, 805, 92

    Oh, S., Kroupa, P ., & Pflamm-Altenburg, J. 2015, ApJ, 805, 92

  60. [60]

    K., Allison, R

    Pang, X., Grebel, E. K., Allison, R. J., et al. 2013, ApJ, 764, 73

  61. [61]

    2024, ApJ, 966, 169

    Pang, X., Liao, S., Li, J., et al. 2024, ApJ, 966, 169

  62. [62]

    2022, ApJ, 931, 156

    Pang, X., Tang, S.-Y ., Li, Y ., et al. 2022, ApJ, 931, 156

  63. [63]

    2023, AJ, 166, 110

    Pang, X., Wang, Y ., Tang, S.-Y ., et al. 2023, AJ, 166, 110

  64. [64]

    2021, ApJ, 923, 20

    Pang, X., Y u, Z., Tang, S.-Y ., et al. 2021, ApJ, 923, 20

  65. [65]

    J., Goodwin, S

    Parker, R. J., Goodwin, S. P ., Wright, N. J., Meyer, M. R., & Quanz, S. P . 2016, MNRAS, 459, L119

  66. [66]

    Parker, R. J. & Schoettler, C. 2022, MNRAS, 510, 1136

  67. [67]

    J., Wright, N

    Parker, R. J., Wright, N. J., Goodwin, S. P ., & Meyer, M. R. 2014, MNRAS, 438, 620 Pavlík, V . 2020, A&A, 638, A155

  68. [68]

    Perets, H. B. & Šubr, L. 2012, ApJ, 751, 133

  69. [69]

    S., et al

    Polak, B., Mac Low, M.-M., Klessen, R. S., et al. 2025, A&A, 695, A188 Portegies Zwart, S. F., McMillan, S. L., & Gieles, M. 2010, Annu. Rev. Astron. Astrophys., 48, 431 Ramírez-Tannus, M. C., Derkink, A. R., Backs, F., et al. 2024, A&A, 690, A178

  70. [70]

    2020, ApJ, 896, 152

    Rastello, S., Carraro, G., & Capuzzo-Dolcetta, R. 2020, ApJ, 896, 152

  71. [71]

    M., Connelley, M

    Reipurth, B., Guimaraes, M. M., Connelley, M. S., & Bally, J. 2007, AJ, 134, 2272

  72. [72]

    J., Hurley, J

    Rossi, L. J., Hurley, J. R., & Bekki, K. 2017, MNRAS, 468, 4441

  73. [73]

    2012, Science, 337, 444

    Sana, H., De Mink, S., de Koter, A., et al. 2012, Science, 337, 444

  74. [74]

    2018, MNRAS, 477, 1903

    Sills, A., Rieder, S., Scora, J., McCloskey, J., & Ja ffa, S. 2018, MNRAS, 477, 1903

  75. [75]

    1999, JCAM, 109, 407

    Spurzem, R. 1999, JCAM, 109, 407

  76. [76]

    & Kamlah, A

    Spurzem, R. & Kamlah, A. 2023, Living Reviews in Computational Astro- physics, 9, 3

  77. [77]

    2021, MNRAS, 507, 2253 V esperini, E., McMillan, S

    Torniamenti, S., Ballone, A., Mapelli, M., et al. 2021, MNRAS, 507, 2253 V esperini, E., McMillan, S. L., & Zwart, S. P . 2009, AJ, 698, 615

  78. [78]

    2016, MNRAS, 458, 1450

    Wang, L., Spurzem, R., Aarseth, S., et al. 2016, MNRAS, 458, 1450

  79. [79]

    2015, MNRAS, 450, 4070

    Wang, L., Spurzem, R., Aarseth, S., et al. 2015, MNRAS, 450, 4070

  80. [80]

    Wang, L., Tanikawa, A., & Fujii, M. S. 2022, MNRAS, 509, 4713 Y u, J., Puzia, T. H., Lin, C., & Zhang, Y . 2017, ApJ, 840, 91

Showing first 80 references.