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arxiv: 2607.01331 · v1 · pith:X4PISYFVnew · submitted 2026-07-01 · 🌌 astro-ph.GA

The fingerprint of primordial mass segregation on the tidal tails of star clusters

S. Mojtaba Ghasemi , Hosein Haghi , Mohammad Mansoury , Akram Hasani Zonoozi , Pouriya Miri , Pavel Kroupa This is my paper

Pith reviewed 2026-07-03 19:39 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords primordial mass segregationtidal tailsstar clustersN-body simulationsstellar mass functionGalactocentric distanceblack hole retentioncluster evolution
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The pith

Primordial mass segregation produces denser, unified, and longer tidal tails in star clusters early in their evolution.

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 with two levels of primordial mass segregation at different distances from the galactic center and with varying black hole retention. It tracks how these initial conditions change the expansion of the cluster and the structure of the tidal tails that form as stars escape. Segregated clusters develop tails that are denser and more connected, with a higher fraction of low-mass stars, and this pattern stands out more at smaller galactic distances. The distinctions in tail shape and mass distribution are clearest at early times and become harder to see as the cluster ages. Retention of black holes shows little influence on these tail features.

Core claim

N-body simulations of clusters with different degrees of primordial mass segregation at various Galactocentric distances show that primordially segregated clusters form denser, unified, and longer tidal tail structures with a bottom-heavy stellar mass function compared to non-segregated clusters. The effect is stronger at smaller R_G but weakens over time, with mean stellar mass distributions along the tails converging at later stages. Stellar remnant retention has only a weak effect on the mass distribution and tail morphology.

What carries the argument

N-body simulations that compare primordially mass-segregated and non-segregated clusters to measure tidal tail density, length, unity, and the stellar mass function along the tails.

If this is right

  • Mean stellar mass along the tails follows distinct patterns for segregated versus non-segregated clusters that converge at later times.
  • The rate of change in mean mass along the tails for segregated clusters eventually matches that of non-segregated clusters.
  • Black hole retention has only a weak effect on mean mass distribution and tail morphology.
  • Tail structure differences are more pronounced at smaller Galactocentric distances.
  • The overall influence of primordial mass segregation on tail properties fades during cluster evolution.

Where Pith is reading between the lines

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

  • Observations of mass functions in the tails of young clusters could indicate whether they began with primordial mass segregation.
  • Late-time observations of old clusters may not retain clear signatures of initial mass segregation.
  • Comparing clusters at a range of galactic distances could test how strongly the galactic potential modulates the PMS signal in tails.
  • Simulations with a wider range of initial cluster masses or orbital parameters would show whether the reported tail differences hold more generally.

Load-bearing premise

The two chosen degrees of primordial mass segregation together with the specific galactic potential and black hole retention fractions match the range present in real star clusters.

What would settle it

Finding young star clusters whose tidal tails show no measurable difference in density, length, or low-mass star fraction between clusters expected to have had high versus low primordial mass segregation.

Figures

Figures reproduced from arXiv: 2607.01331 by Akram Hasani Zonoozi, Hosein Haghi, Mohammad Mansoury, Pavel Kroupa, Pouriya Miri, S. Mojtaba Ghasemi.

Figure 1
Figure 1. Figure 1: 2-D display of the initial spatial distribution of stellar population characteristics. Top row: The logarithmic number density of stars. Bottom row: The distribution of mean stellar mass. Models with low and high PMS coefficients are shown in the left and right columns, respectively. Colour scales represent values per 2 pc2 area. tidal tails. To analyse the impact of 𝑅G and PMS on cluster dynamics and tida… view at source ↗
Figure 2
Figure 2. Figure 2: Analysis of the stellar number and mean mass distribution for models at 𝑅G = 12 kpc with the clusters having lost 40% of their initial mass ( 𝑓mass−loss = 0.4). The left column shows the results for the S0 model, and the right column displays the S1 model. The top two rows show the spatial distribution of the number of luminous stars along the tails (first row) and the corresponding spatial number distribu… view at source ↗
Figure 3
Figure 3. Figure 3: Same as [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Radial variation of <m> of luminous stars along cluster tails for both S0 and S1 models at 𝑅G = 12 kpc. Distributions are shown at 𝑓mass−loss = 0.4 and 0.75 in the top and bottom panels, respectively. The <m> is calculated in 200 pc radial bins. The blue dotted lines show the S0 model, and the orange dotted-dashes show the S1 model. At 𝑓mass−loss = 0.4, S0 clusters develop symmetric tails that reach a tota… view at source ↗
Figure 5
Figure 5. Figure 5: Evolution of the mass function slope as a function of 𝑓mass−loss for models at 𝑅G = 12 kpc. 𝛼 is calculated for luminous stars with masses 0.3 to 0.8 M⊙ (eq. 2). A colour gradient from red to blue represents radial regions from cluster core to tail edges. This visualisation demonstrates the spatial and temporal variation of 𝛼 across the cluster’s evolution. highlights contrasting behavior between S0 and S1… view at source ↗
Figure 6
Figure 6. Figure 6: Same as [PITH_FULL_IMAGE:figures/full_fig_p006_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Comparative analysis of mean stellar mass (< 𝑚 >) profiles in tidal tails of low-NKV cluster models. The horizontal axis shows distance from the cluster centre in units of tidal radius (𝑟t), plotted on a semi-logarithmic scale from 0 to 100 𝑟t. The vertical axis shows the mean stellar mass, < 𝑚 >. Columns correspond to different evolutionary stages, expressed by fractional mass loss ( 𝑓mass−loss, see [PIT… view at source ↗
Figure 8
Figure 8. Figure 8: The total length of the leading and trailing tails of star clusters evolving with time (left panel) and 𝑓mass−loss (right panel) for all 4 models placed at 𝑅G = 4 kpc until their dissolution times. 0.1 0.3 0.5 < m > [M -] fmass!loss = 0:4 RG4-S0-K RG4-S1-K -1 0 1 x [kpc] 0.1 0.3 0.5 < m > [M -] fmass!loss = 0:75 [PITH_FULL_IMAGE:figures/full_fig_p008_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Same as [PITH_FULL_IMAGE:figures/full_fig_p008_9.png] view at source ↗
read the original abstract

We investigate the effect of primordial mass segregation (PMS) in shaping the tidal tail structures of star clusters, searching for any trace of PMS on the tails at both early and late evolutionary stages. Through N-body simulations, we analyze clusters with two different degrees of PMS at various Galactocentric distances (R_G), considering two black hole retention scenarios. Our findings reveal that PMS influences early cluster expansion and the formation of tidal tails with a bottom-heavy stellar mass function, this being more pronounced at smaller R_G but diminishes over time. Primordially segregated clusters exhibit denser, unified, and longer tail structures compared to non-segregated clusters. The mean stellar mass distribution along the tails shows distinct patterns for primordially segregated and non-segregated clusters, converging at later evolutionary stages. The retention of stellar remnants has a weak impact on the mean mass distribution along the tails and on its morphology. We find that although mean mass differences persist along the tidal tails, the rate of change in primordially mass-segregated clusters eventually converges with that of non-segregated clusters, suggesting that the influence of primordial mass segregation on the tidal tails gradually diminishes over the course of cluster evolution.

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 / 0 minor

Summary. The manuscript reports N-body simulations comparing star clusters with two discrete levels of primordial mass segregation (PMS) at multiple Galactocentric distances (R_G) and two black-hole retention fractions. It finds that PMS drives earlier cluster expansion and produces tidal tails with bottom-heavy stellar mass functions (stronger at small R_G), with segregated clusters forming denser, unified, and longer tails. Mean stellar mass distributions along the tails differ initially but converge at later times; black-hole retention has only weak effects, and the overall PMS imprint diminishes over cluster evolution.

Significance. If the reported trends are robust, the work demonstrates that initial mass segregation can leave observable morphological and mass-function signatures in tidal tails, offering a potential diagnostic for the early dynamical state of clusters. The parameter survey across R_G and retention fractions is a positive feature, as is the explicit tracking of time evolution showing convergence of the PMS effect.

major comments (2)
  1. [Methods] Methods section (simulation setup and post-processing): the abstract and results describe consistent trends across runs but report no quantitative error bars, no convergence tests with respect to particle number or integration accuracy, and no explicit description of how tail membership is assigned in post-processing. These omissions are load-bearing because the central claims rest on differences in tail density, length, and mass-function gradients.
  2. [Results] Results on tail morphology and mass functions: the statements that PMS produces 'denser, unified, and longer' tails and distinct mean-mass patterns are presented without statistical significance measures or sensitivity tests to the two chosen PMS degrees. This weakens the ability to judge whether the reported differences are robust or could be altered by modest changes in the free parameters (PMS level, R_G, retention fraction).

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed report. We address each major comment point by point below, agreeing where clarifications and additions are warranted, and will revise the manuscript accordingly.

read point-by-point responses

  1. Referee: [Methods] Methods section (simulation setup and post-processing): the abstract and results describe consistent trends across runs but report no quantitative error bars, no convergence tests with respect to particle number or integration accuracy, and no explicit description of how tail membership is assigned in post-processing. These omissions are load-bearing because the central claims rest on differences in tail density, length, and mass-function gradients.

    Authors: We agree these details should be explicit. In the revised manuscript we will add: (i) a precise description of the post-processing algorithm used to assign tail membership (based on stars lying beyond a multiple of the instantaneous tidal radius with velocities exceeding the local escape speed and aligned with the orbital direction); (ii) quantitative error bars on all reported tail properties, computed as the standard deviation across the ensemble of runs at each R_G and retention fraction; and (iii) a short convergence subsection noting the adopted particle number (N = 10^5) and timestep accuracy, together with a reference to prior validation of the integrator for similar cluster problems. These additions will be placed in the Methods section. revision: yes

  2. Referee: [Results] Results on tail morphology and mass functions: the statements that PMS produces 'denser, unified, and longer' tails and distinct mean-mass patterns are presented without statistical significance measures or sensitivity tests to the two chosen PMS degrees. This weakens the ability to judge whether the reported differences are robust or could be altered by modest changes in the free parameters (PMS level, R_G, retention fraction).

    Authors: The two PMS levels were selected to represent moderate and strong segregation, and the reported trends hold uniformly across the surveyed R_G and retention values. To strengthen the presentation we will insert statistical significance measures (standard errors on mean-mass profiles and, where appropriate, two-sample KS-test p-values for mass-function differences) directly into the figures and text. We will also add a short paragraph discussing sensitivity to the precise PMS parameter values, noting that the morphological and mass-function contrasts scale monotonically with the degree of segregation. Because the existing runs already span a range of R_G and retention fractions, these additions can be made from the current data set. revision: partial

Circularity Check

0 steps flagged

No significant circularity; simulation results are independent of inputs

full rationale

The paper performs direct N-body simulations of star clusters with two discrete levels of primordial mass segregation, varying Galactocentric radius and black-hole retention, then reports morphological and mass-function differences in the resulting tidal tails. No analytic derivation, fitted parameter, or self-citation chain is invoked to obtain the reported trends; the outcomes are generated by the numerical integration itself under the stated initial conditions. The comparison between segregated and non-segregated runs is therefore not reducible to a redefinition or renaming of the input assumptions.

Axiom & Free-Parameter Ledger

3 free parameters · 2 axioms · 0 invented entities

The central claim rests on the validity of the N-body integrator, the chosen initial mass functions, the Galactic tidal field model, and the two discrete PMS degrees; these are standard inputs rather than new postulates.

free parameters (3)
  • degree of primordial mass segregation
    Two discrete levels chosen by the authors to bracket possible birth conditions.
  • Galactocentric distance R_G
    Varied across runs; values not specified in abstract but treated as input parameters.
  • black-hole retention fraction
    Two scenarios tested as input choices.
axioms (2)
  • standard math Newtonian gravity and standard stellar evolution prescriptions govern the N-body evolution
    Implicit in all N-body cluster simulations; invoked throughout the methods.
  • domain assumption The chosen initial conditions for PMS are physically plausible
    The paper tests two degrees without deriving them from first principles.

pith-pipeline@v0.9.1-grok · 5765 in / 1489 out tokens · 19740 ms · 2026-07-03T19:39:26.205612+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

82 extracted references · 77 canonical work pages

  1. [1]

    J., 1999, @doi [ ] 10.1086/316455 , https://ui.adsabs.harvard.edu/abs/1999PASP..111.1333A 111, 1333

    Aarseth S. J., 1999, @doi [ ] 10.1086/316455 , https://ui.adsabs.harvard.edu/abs/1999PASP..111.1333A 111, 1333

    work page doi:10.1086/316455 1999

  2. [2]

    J., 2003, Gravitational N-body simulations: tools and algorithms

    Aarseth S. J., 2003, Gravitational N-body simulations: tools and algorithms. Cambridge University Press

    2003

  3. [3]

    J., Goodwin S

    Allison R. J., Goodwin S. P., Parker R. J., de Grijs R., Portegies Zwart S. F., Kouwenhoven M. B. N., 2009, @doi [ ] 10.1088/0004-637X/700/2/L99 , https://ui.adsabs.harvard.edu/abs/2009ApJ...700L..99A 700, L99

    work page doi:10.1088/0004-637x/700/2/l99 2009

  4. [4]

    Baumgardt H., Makino J., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06286.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.340..227B 340, 227

    work page doi:10.1046/j.1365-8711.2003.06286.x 2003

  5. [5]

    W., Irwin M

    Belokurov V., Evans N. W., Irwin M. J., Hewett P. C., Wilkinson M. I., 2006, @doi [ ] 10.1086/500362 , https://ui.adsabs.harvard.edu/abs/2006ApJ...637L..29B 637, L29

    work page doi:10.1086/500362 2006

  6. [6]

    J., et al., 2014, @doi [ ] 10.1093/mnrasl/slu089 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443L..84B 443, L84

    Bernard E. J., et al., 2014, @doi [ ] 10.1093/mnrasl/slu089 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443L..84B 443, L84

    work page doi:10.1093/mnrasl/slu089 2014

  7. [7]

    Boffin H. M. J., Jerabkova T., Beccari G., Wang L., 2022, @doi [ ] 10.1093/mnras/stac1567 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514.3579B 514, 3579

    work page doi:10.1093/mnras/stac1567 2022

  8. [8]

    J., 1934, Harvard College Observatory Circular, https://ui.adsabs.harvard.edu/abs/1934HarCi.384....1B 384, 1

    Bok B. J., 1934, Harvard College Observatory Circular, https://ui.adsabs.harvard.edu/abs/1934HarCi.384....1B 384, 1

    1934

  9. [9]

    Bonaca A., Geha M., K \"u pper A. H. W., Diemand J., Johnston K. V., Hogg D. W., 2014, @doi [ ] 10.1088/0004-637X/795/1/94 , https://ui.adsabs.harvard.edu/abs/2014ApJ...795...94B 795, 94

    work page doi:10.1088/0004-637x/795/1/94 2014

  10. [10]

    A., Bate M

    Bonnell I. A., Bate M. R., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05794.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.336..659B 336, 659

    work page doi:10.1046/j.1365-8711.2002.05794.x 2002

  11. [11]

    A., Davies M

    Bonnell I. A., Davies M. B., 1998, @doi [ ] 10.1046/j.1365-8711.1998.01372.x , https://ui.adsabs.harvard.edu/abs/1998MNRAS.295..691B 295, 691

    work page doi:10.1046/j.1365-8711.1998.01372.x 1998

  12. [12]

    Capuzzo Dolcetta R., Di Matteo P., Miocchi P., 2005, @doi [ ] 10.1086/426006 , https://ui.adsabs.harvard.edu/abs/2005AJ....129.1906C 129, 1906

    work page doi:10.1086/426006 2005

  13. [13]

    , keywords =

    Chumak Y. O., Platais I., McLaughlin D. E., Rastorguev A. S., Chumak O. V., 2010, @doi [ ] 10.1111/j.1365-2966.2009.16021.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.402.1841C 402, 1841

    work page doi:10.1111/j.1365-2966.2009.16021.x 2010

  14. [14]

    Fischer P., Pryor C., Murray S., Mateo M., Richtler T., 1998, @doi [ ] 10.1086/300212 , https://ui.adsabs.harvard.edu/abs/1998AJ....115..592F 115, 592

    work page doi:10.1086/300212 1998

  15. [15]

    , keywords =

    Frank M. J., Hilker M., Baumgardt H., C \^o t \'e P., Grebel E. K., Haghi H., K \"u pper A. H. W., Djorgovski S. G., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21105.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.423.2917F 423, 2917

    work page doi:10.1111/j.1365-2966.2012.21105.x 2012

  16. [16]

    J., Grebel E

    Frank M. J., Grebel E. K., K \"u pper A. H. W., 2014, @doi [ ] 10.1093/mnras/stu1197 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..815F 443, 815

    work page doi:10.1093/mnras/stu1197 2014

  17. [17]

    M., Rostami-Shirazi A., Khalaj P., Zonoozi A

    Ghasemi S. M., Rostami-Shirazi A., Khalaj P., Zonoozi A. H., Haghi H., 2024, @doi [ ] 10.1093/mnras/stae2212 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.535.1475G 535, 1475

    work page doi:10.1093/mnras/stae2212 2024

  18. [18]

    Gieles M., Erkal D., Antonini F., Balbinot E., Pe \ n arrubia J., 2021, @doi [Nature Astronomy] 10.1038/s41550-021-01392-2 , https://ui.adsabs.harvard.edu/abs/2021NatAs...5..957G 5, 957

    work page doi:10.1038/s41550-021-01392-2 2021

  19. [19]

    Y., Ostriker J

    Gnedin O. Y., Ostriker J. P., 1997, @doi [ ] 10.1086/303441 , https://ui.adsabs.harvard.edu/abs/1997ApJ...474..223G 474, 223

    work page doi:10.1086/303441 1997

  20. [20]

    C., Kontizas M., Kontizas E., Bellas-Velidis I., 2004, @doi [ ] 10.1051/0004-6361:20031702 , https://ui.adsabs.harvard.edu/abs/2004A&A...416..137G 416, 137

    Gouliermis D., Keller S. C., Kontizas M., Kontizas E., Bellas-Velidis I., 2004, @doi [ ] 10.1051/0004-6361:20031702 , https://ui.adsabs.harvard.edu/abs/2004A&A...416..137G 416, 137

    work page doi:10.1051/0004-6361:20031702 2004

  21. [21]

    A., de Grijs R., Xin Y., 2009, @doi [ ] 10.1088/0004-637X/692/2/1678 , https://ui.adsabs.harvard.edu/abs/2009ApJ...692.1678G 692, 1678

    Gouliermis D. A., de Grijs R., Xin Y., 2009, @doi [ ] 10.1088/0004-637X/692/2/1678 , https://ui.adsabs.harvard.edu/abs/2009ApJ...692.1678G 692, 1678

    work page doi:10.1088/0004-637x/692/2/1678 2009

  22. [22]

    J., 2009, @doi [ ] 10.1088/0004-637X/693/2/1118 , https://ui.adsabs.harvard.edu/abs/2009ApJ...693.1118G 693, 1118

    Grillmair C. J., 2009, @doi [ ] 10.1088/0004-637X/693/2/1118 , https://ui.adsabs.harvard.edu/abs/2009ApJ...693.1118G 693, 1118

    work page doi:10.1088/0004-637x/693/2/1118 2009

  23. [23]

    J., Freeman K

    Grillmair C. J., Freeman K. C., Irwin M., Quinn P. J., 1995, @doi [ ] 10.1086/117470 , https://ui.adsabs.harvard.edu/abs/1995AJ....109.2553G 109, 2553

    work page doi:10.1086/117470 1995

  24. [24]

    J., Cutri R., Masci F

    Grillmair C. J., Cutri R., Masci F. J., Conrow T., Sesar B., Eisenhardt P. R. M., Wright E. L., 2013, @doi [ ] 10.1088/2041-8205/769/2/L23 , https://ui.adsabs.harvard.edu/abs/2013ApJ...769L..23G 769, L23

    work page doi:10.1088/2041-8205/769/2/l23 2013

  25. [25]

    M., Zonoozi A

    Haghi H., Hoseini-Rad S. M., Zonoozi A. H., K \"u pper A. H. W., 2014, @doi [ ] 10.1093/mnras/stu1714 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.3699H 444, 3699

    work page doi:10.1093/mnras/stu1714 2014

  26. [26]

    H., Kroupa P., Banerjee S., Baumgardt H., 2015, @doi [ ] 10.1093/mnras/stv2207 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.3872H 454, 3872

    Haghi H., Zonoozi A. H., Kroupa P., Banerjee S., Baumgardt H., 2015, @doi [ ] 10.1093/mnras/stv2207 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.3872H 454, 3872

    work page doi:10.1093/mnras/stv2207 2015

  27. [27]

    Heggie D., Hut P., 2003, The Gravitational Million-Body Problem: A Multidisciplinary Approach to Star Cluster Dynamics

    2003

  28. [28]

    A., 1997, @doi [ ] 10.1086/118389 , https://ui.adsabs.harvard.edu/abs/1997AJ....113.1733H 113, 1733

    Hillenbrand L. A., 1997, @doi [ ] 10.1086/118389 , https://ui.adsabs.harvard.edu/abs/1997AJ....113.1733H 113, 1733

    work page doi:10.1086/118389 1997

  29. [29]

    R., Pols O

    Hurley J. R., Pols O. R., Tout C. A., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03426.x , https://ui.adsabs.harvard.edu/abs/2000MNRAS.315..543H 315, 543

    work page doi:10.1046/j.1365-8711.2000.03426.x 2000

  30. [30]

    A., Bate M

    Hurley J. R., Tout C. A., Pols O. R., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05038.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.329..897H 329, 897

    work page doi:10.1046/j.1365-8711.2002.05038.x 2002

  31. [31]

    A., Malhan K., Martin N

    Ibata R. A., Malhan K., Martin N. F., 2019, @doi [ ] 10.3847/1538-4357/ab0080 , https://ui.adsabs.harvard.edu/abs/2019ApJ...872..152I 872, 152

    work page doi:10.3847/1538-4357/ab0080 2019

  32. [32]

    V., Risbud D., Kroupa P., Wu W., 2025, @doi [ ] 10.1051/0004-6361/202555858 , https://ui.adsabs.harvard.edu/abs/2025A&A...704A..50J 704, A50

    Jadhav V. V., Risbud D., Kroupa P., Wu W., 2025, @doi [ ] 10.1051/0004-6361/202555858 , https://ui.adsabs.harvard.edu/abs/2025A&A...704A..50J 704, A50

    work page doi:10.1051/0004-6361/202555858 2025

  33. [33]

    Jerabkova T., Boffin H. M. J., Beccari G., de Marchi G., de Bruijne J. H. J., Prusti T., 2021, @doi [ ] 10.1051/0004-6361/202039949 , https://ui.adsabs.harvard.edu/abs/2021A&A...647A.137J 647, A137

    work page doi:10.1051/0004-6361/202039949 2021

  34. [34]

    Jordi K., et al., 2009, @doi [ ] 10.1088/0004-6256/137/6/4586 , https://ui.adsabs.harvard.edu/abs/2009AJ....137.4586J 137, 4586

    work page doi:10.1088/0004-6256/137/6/4586 2009

  35. [35]

    K., ¨Ozel, F., & Psaltis, D

    Just A., Berczik P., Petrov M. I., Ernst A., 2009, @doi [ ] 10.1111/j.1365-2966.2008.14099.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.392..969J 392, 969

    work page doi:10.1111/j.1365-2966.2008.14099.x 2009

  36. [36]

    Kaderali S., Hunt J. A. S., Webb J. J., Price-Jones N., Carlberg R., 2019, @doi [ ] 10.1093/mnrasl/slz015 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484L.114K 484, L114

    work page doi:10.1093/mnrasl/slz015 2019

  37. [37]

    , keywords =

    Keller S. C., Da Costa G. S., Prior S. L., 2009, @doi [ ] 10.1111/j.1365-2966.2009.14393.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.394.1045K 394, 1045

    work page doi:10.1111/j.1365-2966.2009.14393.x 2009

  38. [38]

    E., Belokurov V., Zucker D

    Koposov S. E., Belokurov V., Zucker D. B., Lewis G. F., Ibata R. A., Olszewski E. W., L \'o pez-S \'a nchez \'A . R., Hyde E. A., 2015, @doi [ ] 10.1093/mnras/stu2263 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.446.3110K 446, 3110

    work page doi:10.1093/mnras/stu2263 2015

  39. [39]

    arXiv:2406.18767

    Kos J., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.18767 , https://ui.adsabs.harvard.edu/abs/2024arXiv240618767K p. arXiv:2406.18767

    work page doi:10.48550/arxiv.2406.18767 2024

  40. [40]

    Kroupa P., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04022.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.322..231K 322, 231

    work page doi:10.1046/j.1365-8711.2001.04022.x 2001

  41. [41]

    J., Tout C

    Kroupa P., 2008, in Aarseth S. J., Tout C. A., Mardling R. A., eds, , Vol. 760, The Cambridge N-Body Lectures. p. 181, @doi 10.1007/978-1-4020-8431-7_8

    work page doi:10.1007/978-1-4020-8431-7_8 2008

  42. [42]

    Kroupa P., et al., 2022, @doi [ ] 10.1093/mnras/stac2563 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.3613K 517, 3613

    work page doi:10.1093/mnras/stac2563 2022

  43. [43]

    Kroupa P., Pflamm-Altenburg J., Mazurenko S., Wu W., Thies I., Jadhav V., Jerabkova T., 2024, @doi [ ] 10.3847/1538-4357/ad4c66 , https://ui.adsabs.harvard.edu/abs/2024ApJ...970...94K 970, 94

    work page doi:10.3847/1538-4357/ad4c66 2024

  44. [44]

    K \"u pper A. H. W., Macleod A., Heggie D. C., 2008, @doi [Astronomische Nachrichten] 10.1002/asna.200811069 , https://ui.adsabs.harvard.edu/abs/2008AN....329.1061K 329, 1061

    work page doi:10.1002/asna.200811069 2008

  45. [45]

    K \"u pper A. H. W., Kroupa P., Baumgardt H., Heggie D. C., 2010, @doi [ ] 10.1111/j.1365-2966.2009.15690.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.401..105K 401, 105

    work page doi:10.1111/j.1365-2966.2009.15690.x 2010

  46. [46]

    K \"u pper A. H. W., Maschberger T., Kroupa P., Baumgardt H., 2011, @doi [ ] 10.1111/j.1365-2966.2011.19412.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.417.2300K 417, 2300

    work page doi:10.1111/j.1365-2966.2011.19412.x 2011

  47. [47]

    K \"u pper A. H. W., Lane R. R., Heggie D. C., 2012, @doi [ ] 10.1111/j.1365-2966.2011.20242.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.420.2700K 420, 2700

    work page doi:10.1111/j.1365-2966.2011.20242.x 2012

  48. [48]

    Kustaanheimo P., SCHINZEL A., DAVENPORT H., STIEFEL E., 1965, @doi [] doi:10.1515/crll.1965.218.204 , 1965, 204

    work page doi:10.1515/crll.1965.218.204 1965

  49. [49]

    Lee J., Wilhelm R., 2006, @doi [ ] 10.1086/509254 , https://ui.adsabs.harvard.edu/abs/2006ApJ...651L..33L 651, L33

    Lauchner A., Powell W. Lee J., Wilhelm R., 2006, @doi [ ] 10.1086/509254 , https://ui.adsabs.harvard.edu/abs/2006ApJ...651L..33L 651, L33

    work page doi:10.1086/509254 2006

  50. [50]

    A., 2018, @doi [ ] 10.1093/mnras/sty912 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.477.4063M 477, 4063

    Malhan K., Ibata R. A., 2018, @doi [ ] 10.1093/mnras/sty912 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.477.4063M 477, 4063

    work page doi:10.1093/mnras/sty912 2018

  51. [51]

    A., Martin N

    Malhan K., Ibata R. A., Martin N. F., 2018, @doi [ ] 10.1093/mnras/sty2474 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.3442M 481, 3442

    work page doi:10.1093/mnras/sty2474 2018

  52. [52]

    McMillan S. L. W., Vesperini E., Portegies Zwart S. F., 2007, @doi [ ] 10.1086/511763 , https://ui.adsabs.harvard.edu/abs/2007ApJ...655L..45M 655, L45

    work page doi:10.1086/511763 2007

  53. [53]

    Meingast S., Alves J., 2019, @doi [ ] 10.1051/0004-6361/201834622 , https://ui.adsabs.harvard.edu/abs/2019A&A...621L...3M 621, L3

    work page doi:10.1051/0004-6361/201834622 2019

  54. [54]

    J., 1993, @doi [Celestial Mechanics and Dynamical Astronomy] 10.1007/BF00695714 , https://ui.adsabs.harvard.edu/abs/1993CeMDA..57..439M 57, 439

    Mikkola S., Aarseth S. J., 1993, @doi [Celestial Mechanics and Dynamical Astronomy] 10.1007/BF00695714 , https://ui.adsabs.harvard.edu/abs/1993CeMDA..57..439M 57, 439

    work page doi:10.1007/bf00695714 1993

  55. [55]

    Mikkola S., Tanikawa K., 1999, @doi [ ] 10.1046/j.1365-8711.1999.02982.x , https://ui.adsabs.harvard.edu/abs/1999MNRAS.310..745M 310, 745

    work page doi:10.1046/j.1365-8711.1999.02982.x 1999

  56. [56]

    Montuori M., Capuzzo-Dolcetta R., Di Matteo P., Lepinette A., Miocchi P., 2007, @doi [ ] 10.1086/512114 , https://ui.adsabs.harvard.edu/abs/2007ApJ...659.1212M 659, 1212

    work page doi:10.1086/512114 2007

  57. [57]

    D., Lin D

    Murray S. D., Lin D. N. C., 1996, @doi [ ] 10.1086/177648 , https://ui.adsabs.harvard.edu/abs/1996ApJ...467..728M 467, 728

    work page doi:10.1086/177648 1996

  58. [58]

    Odenkirchen M., et al., 2001, @doi [ ] 10.1086/319095 , https://ui.adsabs.harvard.edu/abs/2001ApJ...548L.165O 548, L165

    work page doi:10.1086/319095 2001

  59. [59]

    Odenkirchen M., et al., 2003, @doi [ ] 10.1086/378601 , https://ui.adsabs.harvard.edu/abs/2003AJ....126.2385O 126, 2385

    work page doi:10.1086/378601 2003

  60. [60]

    G., Miralda-Escud \'e J., 2019, @doi [ ] 10.1093/mnras/stz1790 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.1535P 488, 1535

    Palau C. G., Miralda-Escud \'e J., 2019, @doi [ ] 10.1093/mnras/stz1790 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.1535P 488, 1535

    work page doi:10.1093/mnras/stz1790 2019

  61. [61]

    Pavl \' k V., Kroupa P., S ubr L., 2019, @doi [ ] 10.1051/0004-6361/201834265 , https://ui.adsabs.harvard.edu/abs/2019A&A...626A..79P 626, A79

    work page doi:10.1051/0004-6361/201834265 2019

  62. [62]

    Pflamm-Altenburg J., Kroupa P., Thies I., Jerabkova T., Beccari G., Prusti T., Boffin H. M. J., 2023, @doi [ ] 10.1051/0004-6361/202244243 , https://ui.adsabs.harvard.edu/abs/2023A&A...671A..88P 671, A88

    work page doi:10.1051/0004-6361/202244243 2023

  63. [63]

    C., 1911, @doi [ ] 10.1093/mnras/71.5.460 , https://ui.adsabs.harvard.edu/abs/1911MNRAS..71..460P 71, 460

    Plummer H. C., 1911, @doi [ ] 10.1093/mnras/71.5.460 , https://ui.adsabs.harvard.edu/abs/1911MNRAS..71..460P 71, 460

    work page doi:10.1093/mnras/71.5.460 1911

  64. [64]

    R \"o ser S., Schilbach E., Goldman B., 2019, @doi [ ] 10.1051/0004-6361/201834608 , https://ui.adsabs.harvard.edu/abs/2019A&A...621L...2R 621, L2

    work page doi:10.1051/0004-6361/201834608 2019

  65. [65]

    H., Farhani Asl A., Kroupa P., 2024, @doi [ ] 10.1093/mnras/stae936 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.4166R 531, 4166

    Rostami Shirazi A., Haghi H., Zonoozi A. H., Farhani Asl A., Kroupa P., 2024, @doi [ ] 10.1093/mnras/stae936 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.4166R 531, 4166

    work page doi:10.1093/mnras/stae936 2024

  66. [66]

    S., Smith L

    Sabbi E., Gallagher J. S., Smith L. J., de Mello D. F., Mountain M., 2008, @doi [ ] 10.1086/587548 , https://ui.adsabs.harvard.edu/abs/2008ApJ...676L.113S 676, L113

    work page doi:10.1086/587548 2008

  67. [67]

    Shipp N., Drlica-Wagner A., Dark Energy Survey Collaboration 2018, in APS April Meeting Abstracts. p. R15.008

    2018

  68. [68]

    Sirianni M., Nota A., De Marchi G., Leitherer C., Clampin M., 2002, @doi [ ] 10.1086/342723 , https://ui.adsabs.harvard.edu/abs/2002ApJ...579..275S 579, 275

    work page doi:10.1086/342723 2002

  69. [69]

    Spitzer Lyman J., 1940, @doi [ ] 10.1093/mnras/100.5.396 , https://ui.adsabs.harvard.edu/abs/1940MNRAS.100..396S 100, 396

    work page doi:10.1093/mnras/100.5.396 1940

  70. [70]

    S., 2014, in , Dynamical Evolution of Globular Clusters

    Spitzer L. S., 2014, in , Dynamical Evolution of Globular Clusters. Princeton University Press

    2014

  71. [71]

    Stolte A., Brandner W., Brandl B., Zinnecker H., 2006, @doi [ ] 10.1086/504589 , https://ui.adsabs.harvard.edu/abs/2006AJ....132..253S 132, 253

    work page doi:10.1086/504589 2006

  72. [72]

    Vesperini E., McMillan S. L. W., Portegies Zwart S., 2009, @doi [ ] 10.1088/0004-637X/698/1/615 , https://ui.adsabs.harvard.edu/abs/2009ApJ...698..615V 698, 615

    work page doi:10.1088/0004-637x/698/1/615 2009

  73. [73]

    Wang L., Jerabkova T., 2021, @doi [ ] 10.1051/0004-6361/202141838 , https://ui.adsabs.harvard.edu/abs/2021A&A...655A..71W 655, A71

    work page doi:10.1051/0004-6361/202141838 2021

  74. [74]

    C., K ro g lu F., Fragione G., Chatterjee S., Kremer K., Rasio F

    Weatherford N. C., K ro g lu F., Fragione G., Chatterjee S., Kremer K., Rasio F. A., 2023, @doi [ ] 10.3847/1538-4357/acbcc1 , https://ui.adsabs.harvard.edu/abs/2023ApJ...946..104W 946, 104

    work page doi:10.3847/1538-4357/acbcc1 2023

  75. [75]

    J., Bovy J., 2022, @doi [ ] 10.1093/mnras/stab3451 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510..774W 510, 774

    Webb J. J., Bovy J., 2022, @doi [ ] 10.1093/mnras/stab3451 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510..774W 510, 774

    work page doi:10.1093/mnras/stab3451 2022

  76. [76]

    Wirth H., Dinnbier F., Kroupa P., S ubr L., 2024, @doi [ ] 10.1051/0004-6361/202347839 , https://ui.adsabs.harvard.edu/abs/2024A&A...691A.143W 691, A143

    work page doi:10.1051/0004-6361/202347839 2024

  77. [77]

    T., Ray, P

    Zonoozi A. H., K \"u pper A. H. W., Baumgardt H., Haghi H., Kroupa P., Hilker M., 2011, @doi [ ] 10.1111/j.1365-2966.2010.17831.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.411.1989Z 411, 1989

    work page doi:10.1111/j.1365-2966.2010.17831.x 2011

  78. [78]

    H., Haghi H., K \"u pper A

    Zonoozi A. H., Haghi H., K \"u pper A. H. W., Baumgardt H., Frank M. J., Kroupa P., 2014, @doi [ ] 10.1093/mnras/stu526 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.440.3172Z 440, 3172

    work page doi:10.1093/mnras/stu526 2014

  79. [79]

    H., Haghi H., Kroupa P., K \"u pper A

    Zonoozi A. H., Haghi H., Kroupa P., K \"u pper A. H. W., Baumgardt H., 2017, @doi [ ] 10.1093/mnras/stx130 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.467..758Z 467, 758

    work page doi:10.1093/mnras/stx130 2017

  80. [80]

    H., Rabiee M., Haghi H., Kroupa P., 2024, @doi [ ] 10.3847/1538-4357/ad7953 , https://ui.adsabs.harvard.edu/abs/2024ApJ...975..266Z 975, 266

    Zonoozi A. H., Rabiee M., Haghi H., Kroupa P., 2024, @doi [ ] 10.3847/1538-4357/ad7953 , https://ui.adsabs.harvard.edu/abs/2024ApJ...975..266Z 975, 266

    work page doi:10.3847/1538-4357/ad7953 2024

Showing first 80 references.