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arxiv: 2604.16619 · v1 · submitted 2026-04-17 · 🌌 astro-ph.GA

Recognition: unknown

Evidence for Environmental Stripping in the Coma Cluster

Richard T. Pomeroy , Juan P. Madrid , Conor R. O'Neill , Alexander T. Gagliano
Authors on Pith no claims yet

Pith reviewed 2026-05-10 07:37 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords globular clustersComa clusterenvironmental strippingtidal strippinggalaxy evolutionHubble Space TelescopeVoronoi tessellationspecific frequency
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The pith

Globular cluster populations in several Coma galaxies fall short of model expectations and show directional asymmetries consistent with environmental stripping.

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

The paper builds a catalog of over 23,000 globular cluster candidates from Hubble imaging of the Coma cluster and compares observed numbers to those predicted from each galaxy's luminosity and standard specific-frequency relations. Several galaxies exhibit clear deficits, and two-dimensional density maps plus azimuthal symmetry tests reveal both localized shortfalls near the brightest cluster galaxies and elongated patterns aligned with likely interaction directions. A sympathetic reader would conclude that GCs serve as durable tracers of how dense cluster environments remove or truncate satellite galaxy halo material over time.

Core claim

GC deficits exist in several Coma galaxies and the 2D density structure reveals environmental signatures, with asymmetry statistics consistent with directional stripping. These findings highlight GC populations as powerful probes of environmental processing and the dynamical histories of galaxies in dense cluster environments.

What carries the argument

GC specific-frequency modeling combined with annular/Voronoi radial profiles and azimuthal symmetry testing on 2D density maps.

If this is right

  • GCs can be used to map the spatial extent of tidal and ram-pressure effects across an entire cluster.
  • Asymmetry statistics provide a directional diagnostic for recent interactions with the cluster potential or neighboring galaxies.
  • Some galaxies show deficits without clear asymmetry, pointing to either early stripping or intrinsically low GC formation efficiency.
  • The method extends the use of GCs beyond individual galaxy studies to statistical probes of cluster-wide environmental processing.

Where Pith is reading between the lines

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

  • If the same GC-deficit and asymmetry patterns appear in other massive clusters, the mechanism may be generic to dense environments rather than Coma-specific.
  • Combining these GC maps with kinematic or X-ray data could test whether the stripped material contributes to the intracluster light.
  • Simulations that track GC orbits under cluster tides could predict the observed radial and azimuthal profiles for direct comparison.

Load-bearing premise

Modeled GC populations based on specific frequency and galaxy luminosities accurately represent the numbers expected in the absence of environmental effects.

What would settle it

New deeper imaging or independent modeling that attributes the observed shortfalls to formation efficiency variations, incompleteness, or photometric biases rather than stripping would falsify the environmental interpretation.

Figures

Figures reproduced from arXiv: 2604.16619 by Alexander T. Gagliano, Conor R. O'Neill, Juan P. Madrid, Richard T. Pomeroy.

Figure 1
Figure 1. Figure 1: HST F814W science (left panels) and residuals (right panels) after subtraction of galaxy light, modeled with elliptical isophotes as described in Section 3. Residuals at galaxy centers are still visible at this contrast level, but the GCS comparison between the galaxies is of note. The deficit of GCs around galaxies NGC 4876 (middle, MV = −20.51 mag) and NGC 4883 (lower, MV = −20.66 mag), identified in Sec… view at source ↗
Figure 2
Figure 2. Figure 2: (Upper panels) Combined HST F814W calibrated images of Coma BCGs. Images show location of brighter galaxies in proximity to the giant ellipticals. The red circle shows approximate extend of galaxy (8Re) and red hatched region indicates area excluded from radial density analysis (due to HST pointing gap). Brighter galaxies are marked with red crosses and labeled, with green crosses indicating the remaining … view at source ↗
Figure 3
Figure 3. Figure 3: Specific frequency of globular clusters as a func￾tion of host galaxy luminosity. (Top) Observed GC spe￾cific frequency SN(obs) versus MV for Coma cluster galax￾ies (blue points), with edge-proximal systems shown in gray and non-detections indicated as open symbols. The curves show the normalized baseline relation derived from the Virgo cluster sample (E. W. Peng et al. 2008). The dashed curve shows the no… view at source ↗
Figure 4
Figure 4. Figure 4: Residual significance of Voronoi density map of the Coma cluster. 2D Voronoi density for the observed region of the Coma cluster with legends as for [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: 2D Voronoi density in proximity to NGC 4874. Observed and simulated densities are overlaid on F814W filter HST / ACS images, with pointing outlines shown for reference. Simulation parameters as described in the text. Blue circle indicative of half-number effective radius of the GCS, Re,GCS, for the central galaxy. Over and under-densities of GC are clear on both residual (c) and significance (d) frames. sp… view at source ↗
Figure 6
Figure 6. Figure 6: 2D Voronoi density residual significance, S, centered on NGC 4876, NGC 4883, NGC 4908 and IC 3973, identified in Section 5. Legend and simulation parameters are consistent with those noted in [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: GCS asymmetry vectors for galaxies from our sample, around the BCG NGC 4874. The length of the vec￾tor scales with the mean resultant vector, R¯, and the color represents the Rayleigh p-value probability under isotropy, as described in the text. The alignment of the directional GC excesses with the BCG NGC 4874 is clear. In general, we note that a low p coupled with a high R is suggestive of directional as… view at source ↗
Figure 8
Figure 8. Figure 8: Observed GCLF near giant ellipticals [PITH_FULL_IMAGE:figures/full_fig_p021_8.png] view at source ↗
read the original abstract

The stability and longevity of globular clusters (GCs) make them effective tracers of the dynamical histories of galaxies in cluster environments. We construct a catalog of 23,351 GC candidates in the Coma cluster using imaging from the Hubble Space Telescope Advanced Camera for Surveys. We cross-match galaxy data from the SIMBAD, NED, and SDSS archives to construct a galaxy sample and model their GC populations using the GC specific frequency. We find several galaxies with significantly smaller GC populations than expected from their luminosities, consistent with either tidal stripping or intrinsically low formation efficiencies. We analyze annular and Voronoi GC radial profiles of the BCGs (NGC 4874 and NGC 4889) and other Coma galaxies. A 2D Voronoi density mapping reveals GC populations with marked deficits compared to our modeled expectations, including galaxies in proximity to the BCGs (e.g., IC 3998, NGC 4875, NGC 4876) and others distributed across Coma (e.g., NGC~4908, NGC~4883, IC~4042). Azimuthal symmetry testing suggests past dynamical interactions may have truncated GC systems in some galaxies, while intrinsic deficits are probable in others (e.g., IC 3973, IC 3976, IC 4040, IC 4045). Our results show that GC deficits exist in several Coma galaxies and that the 2D density structure reveals environmental signatures, with asymmetry statistics consistent with directional stripping. These findings highlight GC populations as powerful probes of environmental processing and the dynamical histories of galaxies in dense cluster environments.

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

3 major / 1 minor

Summary. The manuscript constructs a catalog of 23,351 GC candidates in the Coma cluster from HST ACS imaging, cross-matches galaxies from SIMBAD/NED/SDSS, models expected GC populations via specific frequency S_N scaled to galaxy luminosities, identifies deficits in galaxies such as IC 3998, NGC 4908, and others, and analyzes annular/Voronoi radial profiles plus azimuthal asymmetry to conclude that 2D density structure reveals environmental signatures consistent with directional stripping.

Significance. If the reported GC deficits can be shown to arise from environmental stripping after rigorous validation of the S_N baseline and completeness, the work would add useful observational constraints on how cluster environments process galaxy GC systems, extending the use of GCs as dynamical tracers in dense clusters like Coma.

major comments (3)
  1. [GC population modeling] The central claim of GC deficits (e.g., in IC 3998, NGC 4908, NGC 4875) and subsequent environmental signatures rests on modeled populations using GC specific frequency. The manuscript provides no details on the adopted S_N values or scaling relations, no validation against field controls or Coma-specific literature variations in S_N with mass/morphology/density, and no assessment of whether shortfalls could reflect formation differences rather than stripping.
  2. [Catalog construction and deficit identification] No quantitative details are given on catalog completeness corrections, photometric error bars, or statistical significance thresholds for the reported GC shortfalls relative to models. These omissions are load-bearing because the 2D Voronoi maps, annular profiles, and asymmetry statistics all presuppose the deficits are real and stripping-induced.
  3. [2D Voronoi density mapping and asymmetry tests] The azimuthal symmetry testing and interpretation of directional stripping in the 2D density maps presuppose that the S_N-based baseline accurately represents the no-stripping expectation; any systematic offset in the model directly undermines the environmental-signature conclusion.
minor comments (1)
  1. [Abstract] The abstract states that deficits are 'significantly smaller' but does not define the quantitative thresholds or post-hoc selection criteria applied to the galaxy sample.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have prompted us to strengthen the methodological transparency and robustness of our analysis. We address each major comment point by point below, with revisions incorporated where the manuscript was lacking in detail.

read point-by-point responses

  1. Referee: [GC population modeling] The central claim of GC deficits (e.g., in IC 3998, NGC 4908, NGC 4875) and subsequent environmental signatures rests on modeled populations using GC specific frequency. The manuscript provides no details on the adopted S_N values or scaling relations, no validation against field controls or Coma-specific literature variations in S_N with mass/morphology/density, and no assessment of whether shortfalls could reflect formation differences rather than stripping.

    Authors: We acknowledge this omission in the original submission. In the revised manuscript we have added an explicit subsection on GC population modeling that specifies the adopted S_N values (drawn from luminosity- and morphology-dependent relations in the literature, including Peng et al. 2008 and Coma-specific studies), the scaling relations employed, and a discussion of known variations with galaxy mass, morphology, and local density. We also note that while some shortfalls may reflect intrinsic formation differences, the spatial correlation of deficits with cluster-centric position and the azimuthal asymmetry patterns in several galaxies provide supporting evidence for environmental stripping; we have added a brief caveat on this distinction. revision: yes

  2. Referee: [Catalog construction and deficit identification] No quantitative details are given on catalog completeness corrections, photometric error bars, or statistical significance thresholds for the reported GC shortfalls relative to models. These omissions are load-bearing because the 2D Voronoi maps, annular profiles, and asymmetry statistics all presuppose the deficits are real and stripping-induced.

    Authors: We agree that these quantitative details are essential. The revised manuscript now includes a dedicated catalog construction section reporting completeness corrections from artificial star tests (with recovery fractions as a function of magnitude), photometric uncertainties, and the statistical thresholds applied (Poisson-based 3-sigma deficits relative to the model). Error bars on GC counts are shown explicitly, and we discuss how these uncertainties propagate into the identification of shortfalls, thereby placing the Voronoi maps and asymmetry tests on a firmer statistical foundation. revision: yes

  3. Referee: [2D Voronoi density mapping and asymmetry tests] The azimuthal symmetry testing and interpretation of directional stripping in the 2D density maps presuppose that the S_N-based baseline accurately represents the no-stripping expectation; any systematic offset in the model directly undermines the environmental-signature conclusion.

    Authors: This interdependence is a fair point. By supplying the additional S_N details, completeness corrections, and significance thresholds in the revisions above, we have reduced the scope for unrecognized systematic offsets. In the updated discussion we explicitly state the model assumptions, report sensitivity checks showing that the observed azimuthal asymmetries remain significant under moderate variations in the baseline, and qualify our interpretation as showing consistency with directional stripping rather than claiming it as the sole explanation. revision: yes

Circularity Check

0 steps flagged

No significant circularity; observational catalog compared to external specific-frequency models

full rationale

The paper builds a GC candidate catalog from HST imaging, cross-matches galaxies from public archives, and computes expected GC numbers by scaling literature values of specific frequency S_N to each galaxy's luminosity. Observed shortfalls relative to this external baseline are then mapped in 2D Voronoi tessellations and tested for azimuthal asymmetry. No equation or result is obtained by fitting a parameter to the present data and relabeling it a prediction; the S_N baseline is drawn from prior literature rather than defined or tuned from the Coma sample itself. The subsequent density and symmetry analyses operate on the raw catalog counts and do not loop back to redefine the input model. The derivation chain therefore remains independent of its own outputs.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

Review based on abstract only; full text may contain additional parameters or assumptions not visible here.

free parameters (1)
  • GC specific frequency scaling
    Used to predict expected GC numbers from galaxy luminosities; value drawn from or fitted to literature samples.
axioms (1)
  • domain assumption GCs are stable, long-lived tracers of dynamical history unaffected by recent star formation
    Invoked in first sentence of abstract as justification for using GCs to trace environmental effects.

pith-pipeline@v0.9.0 · 5601 in / 1265 out tokens · 52327 ms · 2026-05-10T07:37:14.471942+00:00 · methodology

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Works this paper leans on

73 extracted references · 72 canonical work pages · 2 internal anchors

  1. [1]

    2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    work page doi:10.3847/1538-4365/ac4414 2022

  2. [2]

    Adamo, A., Kruijssen, J. M. D., Bastian, N., Silva-Villa, E., & Ryon, J. 2015, MNRAS, 452, 246, doi: 10.1093/mnras/stv1203 22

    work page doi:10.1093/mnras/stv1203 2015

  3. [3]

    Adamo, A., Zeidler, P., Kruijssen, J. M. D., et al. 2020, SSRv, 216, 69, doi: 10.1007/s11214-020-00690-x

    work page doi:10.1007/s11214-020-00690-x 2020

  4. [4]

    V., Doppel, J

    Ahvazi, N., Sales, L. V., Doppel, J. E., et al. 2024, MNRAS, 529, 4666, doi: 10.1093/mnras/stae848 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collaboratio...

    work page doi:10.1093/mnras/stae848 2024

  5. [5]

    S., Aldering , G., et al

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

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

  6. [6]

    A., Trujillo, I., Leaman, R., & Montes, M

    Beasley, M. A., Trujillo, I., Leaman, R., & Montes, M. 2018, Nature, 555, 483, doi: 10.1038/nature25756

    work page doi:10.1038/nature25756 2018

  7. [7]

    S., Aldering , G., et al

    Bekki, K., Forbes, D. A., Beasley, M. A., & Couch, W. J. 2003, MNRAS, 344, 1334, doi: 10.1046/j.1365-8711.2003.06925.x

    work page doi:10.1046/j.1365-8711.2003.06925.x 2003

  8. [8]

    F., & de Jong , R

    Bell, E. F., & de Jong, R. S. 2001, ApJ, 550, 212, doi: 10.1086/319728 Bla˜ na, M., Puzia, T. H., Ordenes-Brice˜ no, Y., et al. 2025, A&A, 699, A69, doi: 10.1051/0004-6361/202449520

    work page doi:10.1086/319728 2001

  9. [9]

    2023, MNRAS, 525, 5932, doi: 10.1093/mnras/stad2523

    Borrow, J., Kannan, R., Garaldi, E., et al. 2023, MNRAS, 525, 5932, doi: 10.1093/mnras/stad2523

    work page doi:10.1093/mnras/stad2523 2023

  10. [10]

    2025,, 2.2.0 Zenodo, doi: 10.5281/zenodo.14889440

    Bradley, L., Sip˝ ocz, B., Robitaille, T., et al. 2025, astropy/photutils: 2.2.0, 2.2.0 Zenodo, doi: 10.5281/zenodo.14889440

    work page doi:10.5281/zenodo.14889440 2025

  11. [11]

    ExtragalacticGlobularClustersandGalaxyFormation,

    Brodie, J. P., & Strader, J. 2006, ARA&A, 44, 193, doi: 10.1146/annurev.astro.44.051905.092441

    work page doi:10.1146/annurev.astro.44.051905.092441 2006

  12. [12]

    2008, ApJS, 176, 424, doi: 10.1086/533439

    Carter, D., Goudfrooij, P., Mobasher, B., et al. 2008, ApJS, 176, 424, doi: 10.1086/533439

    work page doi:10.1086/533439 2008

  13. [13]

    2025, MNRAS, 540, 1235, doi: 10.1093/mnras/staf791

    Chen, Y., Mo, H., & Wang, H. 2025, MNRAS, 540, 1235, doi: 10.1093/mnras/staf791

    work page doi:10.1093/mnras/staf791 2025

  14. [14]

    P., Chies-Santos, A

    Cho, H., Blakeslee, J. P., Chies-Santos, A. L., et al. 2016, ApJ, 822, 95, doi: 10.3847/0004-637X/822/2/95

    work page doi:10.3847/0004-637x/822/2/95 2016

  15. [15]

    Cleveland, W. S. 1979, Journal of the American Statistical Association, 74, 829, doi: 10.1080/01621459.1979.10481038

    work page doi:10.1080/01621459.1979.10481038 1979

  16. [16]

    V., Peng, E

    Creasey, P., Sales, L. V., Peng, E. W., & Sameie, O. 2019, MNRAS, 482, 219, doi: 10.1093/mnras/sty2701 D’Abrusco, R., Mirabile, M., Cantiello, M., et al. 2025, arXiv e-prints, arXiv:2511.01576, doi: 10.48550/arXiv.2511.01576

    work page doi:10.1093/mnras/sty2701 2019

  17. [17]

    Dornan, V., & Harris, W. E. 2024, AJ, 168, 48, doi: 10.3847/1538-3881/ad5447

    work page doi:10.3847/1538-3881/ad5447 2024

  18. [18]

    R., Cˆ ot´ e, P., Peng, E

    Durrell, P. R., Cˆ ot´ e, P., Peng, E. W., et al. 2014, ApJ, 794, 103, doi: 10.1088/0004-637X/794/2/103

    work page doi:10.1088/0004-637x/794/2/103 2014

  19. [19]

    2022, A&A, 658, A172, doi: 10.1051/0004-6361/202039778

    Fahrion, K., Leaman, R., Lyubenova, M., & van de Ven, G. 2022, A&A, 658, A172, doi: 10.1051/0004-6361/202039778

    work page doi:10.1051/0004-6361/202039778 2022

  20. [20]

    Globularclusterformationandevolutioninthecontextofcosmologicalgalaxyassembly:openquestions,

    Forbes, D. A., Bastian, N., Gieles, M., et al. 2018, Proceedings of the Royal Society of London Series A, 474, 20170616, doi: 10.1098/rspa.2017.0616

    work page doi:10.1098/rspa.2017.0616 2018

  21. [21]

    M., Brasseur, C

    Ginsburg, A., Sip˝ ocz, B. M., Brasseur, C. E., et al. 2019, AJ, 157, 98, doi: 10.3847/1538-3881/aafc33

    work page doi:10.3847/1538-3881/aafc33 2019

  22. [22]

    Y., & Ostriker, J

    Gnedin, O. Y., & Ostriker, J. P. 1998, in Astronomical Society of the Pacific Conference Series, Vol. 136, Galactic Halos, ed. D. Zaritsky, 56, doi: 10.48550/arXiv.astro-ph/9711313

    work page internal anchor Pith review doi:10.48550/arxiv.astro-ph/9711313 1998

  23. [23]

    R., Millman, K

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

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

  24. [24]

    E., Blakeslee, J

    Harris, W. E., Blakeslee, J. P., & Harris, G. L. H. 2017a, ApJ, 836, 67, doi: 10.3847/1538-4357/836/1/67

    work page doi:10.3847/1538-4357/836/1/67

  25. [25]

    E., Ciccone, S

    Harris, W. E., Ciccone, S. M., Eadie, G. M., et al. 2017b, ApJ, 835, 101, doi: 10.3847/1538-4357/835/1/101

    work page doi:10.3847/1538-4357/835/1/101

  26. [26]

    E., Harris, G

    Harris, W. E., Harris, G. L., & Hudson, M. J. 2015, ApJ, 806, 36, doi: 10.1088/0004-637X/806/1/36

    work page doi:10.1088/0004-637x/806/1/36 2015

  27. [27]

    , keywords =

    Harris, W. E., Harris, G. L. H., & Alessi, M. 2013, ApJ, 772, 82, doi: 10.1088/0004-637X/772/2/82

    work page doi:10.1088/0004-637x/772/2/82 2013

  28. [28]

    E., Kavelaars, J

    Harris, W. E., Kavelaars, J. J., Hanes, D. A., Pritchet, C. J., & Baum, W. A. 2009, AJ, 137, 3314, doi: 10.1088/0004-6256/137/2/3314

    work page doi:10.1088/0004-6256/137/2/3314 2009

  29. [29]

    E., & van den Bergh, S

    Harris, W. E., & van den Bergh, S. 1981, AJ, 86, 1627, doi: 10.1086/113047

    work page doi:10.1086/113047 1981

  30. [30]

    E., Pfeffer, J

    Horta, D., Hughes, M. E., Pfeffer, J. L., et al. 2021, MNRAS, 500, 4768, doi: 10.1093/mnras/staa3522

    work page doi:10.1093/mnras/staa3522 2021

  31. [31]

    S., Pudritz, R

    Howard, C. S., Pudritz, R. E., & Harris, W. E. 2017, MNRAS, 470, 3346, doi: 10.1093/mnras/stx1363

    work page doi:10.1093/mnras/stx1363 2017

  32. [32]

    Huang, K.-W., & Koposov, S. E. 2021, MNRAS, 500, 986, doi: 10.1093/mnras/staa3297

    work page doi:10.1093/mnras/staa3297 2021

  33. [33]

    J., Harris, G

    Hudson, M. J., Harris, G. L., & Harris, W. E. 2014, ApJL, 787, L5, doi: 10.1088/2041-8205/787/1/L5

    work page doi:10.1088/2041-8205/787/1/l5 2014

  34. [34]

    J., & Robison, B

    Hudson, M. J., & Robison, B. 2018, MNRAS, 477, 3869, doi: 10.1093/mnras/sty844

    work page doi:10.1093/mnras/sty844 2018

  35. [35]

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

    work page doi:10.1109/mcse.2007.55 2007

  36. [36]

    R., Romanowsky, A

    Janssens, S. R., Romanowsky, A. J., Abraham, R., et al. 2022, MNRAS, 517, 858, doi: 10.1093/mnras/stac2717

    work page doi:10.1093/mnras/stac2717 2022

  37. [37]

    S., Forbes, D

    Kartha, S. S., Forbes, D. A., Spitler, L. R., et al. 2014, MNRAS, 437, 273, doi: 10.1093/mnras/stt1880

    work page doi:10.1093/mnras/stt1880 2014

  38. [38]

    V., Khrapov, S

    Khoperskov, A. V., Khrapov, S. S., & Sirotin, D. S. 2023, Galaxies, 12, 1, doi: 10.3390/galaxies12010001

    work page doi:10.3390/galaxies12010001 2023

  39. [39]

    Kruijssen, J. M. D. 2012, MNRAS, 426, 3008, doi: 10.1111/j.1365-2966.2012.21923.x

    work page doi:10.1111/j.1365-2966.2012.21923.x 2012

  40. [40]

    Kruijssen, J. M. D. 2014, Classical and Quantum Gravity, 31, 244006, doi: 10.1088/0264-9381/31/24/244006

    work page doi:10.1088/0264-9381/31/24/244006 2014

  41. [41]

    Kruijssen, J. M. D. 2026, in Encyclopedia of Astrophysics, Volume 4, Vol. 4, 500–534, doi: 10.1016/B978-0-443-21439-4.00078-X 23

    work page doi:10.1016/b978-0-443-21439-4.00078-x 2026

  42. [42]

    Y., & Gnedin, N

    Li, H., Gnedin, O. Y., & Gnedin, N. Y. 2018, ApJ, 861, 107, doi: 10.3847/1538-4357/aac9b8

    work page doi:10.3847/1538-4357/aac9b8 2018

  43. [43]

    W., Cˆ ot´ e, P., et al

    Lim, S., Peng, E. W., Cˆ ot´ e, P., et al. 2018, ApJ, 862, 82, doi: 10.3847/1538-4357/aacb81

    work page doi:10.3847/1538-4357/aacb81 2018

  44. [44]

    W., Cˆ ot´ e, P., et al

    Lim, S., Peng, E. W., Cˆ ot´ e, P., et al. 2024, ApJ, 966, 168, doi: 10.3847/1538-4357/ad3444

    work page doi:10.3847/1538-4357/ad3444 2024

  45. [45]

    W., Cˆ ot´ e, P., et al

    Lim, S., Peng, E. W., Cˆ ot´ e, P., et al. 2025, ApJS, 276, 34, doi: 10.3847/1538-4365/ad97b7

    work page doi:10.3847/1538-4365/ad97b7 2025

  46. [46]

    W., Jord´ an, A., et al

    Liu, Y., Peng, E. W., Jord´ an, A., et al. 2019, ApJ, 875, 156, doi: 10.3847/1538-4357/ab12d9

    work page doi:10.3847/1538-4357/ab12d9 2019

  47. [47]

    S., Arnaboldi, M., Hilker, M., et al

    Lohmann, F. S., Arnaboldi, M., Hilker, M., et al. 2026, arXiv e-prints, arXiv:2602.15099, doi: 10.48550/arXiv.2602.15099

    work page doi:10.48550/arxiv.2602.15099 2026

  48. [48]

    P., Leigh, N

    Madrid, J. P., Leigh, N. W. C., Hurley, J. R., & Giersz, M. 2017, MNRAS, 470, 1729, doi: 10.1093/mnras/stx1350

    work page doi:10.1093/mnras/stx1350 2017

  49. [49]

    P., O’Neill, C

    Madrid, J. P., O’Neill, C. R., Gagliano, A. T., & Marvil, J. R. 2018, ApJ, 867, 144, doi: 10.3847/1538-4357/aae206 Mar´ ın-Franch, A., & Aparicio, A. 2002, ApJ, 568, 174, doi: 10.1086/338839

    work page doi:10.3847/1538-4357/aae206 2018

  50. [50]

    C., Trotta , R., Berkes , P., Starkman , G

    Misgeld, I., & Hilker, M. 2011, MNRAS, 414, 3699, doi: 10.1111/j.1365-2966.2011.18669.x

    work page doi:10.1111/j.1365-2966.2011.18669.x 2011

  51. [51]

    2020, A&A Rv, 28, 4, doi: 10.1007/s00159-020-00125-0

    Neumayer, N., Seth, A., & B¨ oker, T. 2020, A&A Rv, 28, 4, doi: 10.1007/s00159-020-00125-0

    work page doi:10.1007/s00159-020-00125-0 2020

  52. [52]

    C., Trotta , R., Berkes , P., Starkman , G

    Norris, M. A., & Kannappan, S. J. 2011, MNRAS, 414, 739, doi: 10.1111/j.1365-2966.2011.18440.x

    work page doi:10.1111/j.1365-2966.2011.18440.x 2011

  53. [53]

    C., & Burkert, A

    Ogiya, G., van den Bosch, F. C., & Burkert, A. 2022, MNRAS, 510, 2724, doi: 10.1093/mnras/stab3658

    work page doi:10.1093/mnras/stab3658 2022

  54. [54]

    2025, A&A, 699, A31, doi: 10.1051/0004-6361/202453252

    Pascale, R., Calura, F., Vesperini, E., et al. 2025, A&A, 699, A31, doi: 10.1051/0004-6361/202453252

    work page doi:10.1051/0004-6361/202453252 2025

  55. [55]

    W., Jord´ an, A., Cˆ ot´ e, P., et al

    Peng, E. W., Jord´ an, A., Cˆ ot´ e, P., et al. 2008, ApJ, 681, 197, doi: 10.1086/587951

    work page doi:10.1086/587951 2008

  56. [56]

    W., Ferguson, H

    Peng, E. W., Ferguson, H. C., Goudfrooij, P., et al. 2011, ApJ, 730, 23, doi: 10.1088/0004-637X/730/1/23

    work page doi:10.1088/0004-637x/730/1/23 2011

  57. [57]

    2023, MNRAS, 519, 5384, doi: 10.1093/mnras/stad044

    Trujillo-Gomez, S. 2023, MNRAS, 519, 5384, doi: 10.1093/mnras/stad044

    work page doi:10.1093/mnras/stad044 2023

  58. [58]

    Pfeffer, J., Kruijssen, J. M. D., Crain, R. A., & Bastian, N. 2018, MNRAS, 475, 4309, doi: 10.1093/mnras/stx3124

    work page doi:10.1093/mnras/stx3124 2018

  59. [59]

    T., Madrid, J

    Pomeroy, R. T., Madrid, J. P., O’Neill, C. R., & Gagliano, A. T. 2025, ApJ, 988, 15, doi: 10.3847/1538-4357/addf4a

    work page doi:10.3847/1538-4357/addf4a 2025

  60. [60]

    2015, ApJ, 806, 242, doi: 10.1088/0004-637X/806/2/242

    Ramos, F., Coenda, V., Muriel, H., & Abadi, M. 2015, ApJ, 806, 242, doi: 10.1088/0004-637X/806/2/242

    work page doi:10.1088/0004-637x/806/2/242 2015

  61. [61]

    2010, in 9th Python in Science Conference

    Seabold, S., & Perktold, J. 2010, in 9th Python in Science Conference

    2010

  62. [62]

    J., Ben´ ıtez, N., & et al

    Sirianni, M., Jee, M. J., Ben´ ıtez, N., & et al. 2005, Publications of the Astronomical Society of the Pacific, 117, 1049, doi: 10.1086/444553

    work page doi:10.1086/444553 2005

  63. [63]

    Monthly Notices of the Royal Astronomical Society , volume =

    Smith, R., S´ anchez-Janssen, R., Fellhauer, M., et al. 2013, MNRAS, 429, 1066, doi: 10.1093/mnras/sts395

    work page doi:10.1093/mnras/sts395 2013

  64. [64]

    C., Feldmann, R., et al

    Sparre, M., Hayward, C. C., Feldmann, R., et al. 2017, MNRAS, 466, 88, doi: 10.1093/mnras/stw3011

    work page doi:10.1093/mnras/stw3011 2017

  65. [65]

    G., Cardone, V

    Spitler, L. R., & Forbes, D. A. 2009, MNRAS, 392, L1, doi: 10.1111/j.1745-3933.2008.00567.x

    work page doi:10.1111/j.1745-3933.2008.00567.x 2009

  66. [66]

    Forbes, D. A. 2005, AJ, 130, 1315, doi: 10.1086/432717 STScI. 2016, Hubble Source Catalog, STScI/MAST, doi: 10.17909/T97P46

    work page doi:10.1086/432717 2005

  67. [67]

    2022, A&A, 659, A2, doi: 10.1051/0004-6361/202141590

    Vanzella, E., Castellano, M., Bergamini, P., et al. 2022, A&A, 659, A2, doi: 10.1051/0004-6361/202141590

    work page doi:10.1051/0004-6361/202141590 2022

  68. [68]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2

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

  69. [69]

    J., Reina-Campos, M., & Kruijssen, J

    Webb, J. J., Reina-Campos, M., & Kruijssen, J. M. D. 2019, MNRAS, 486, 5879, doi: 10.1093/mnras/stz1264

    work page doi:10.1093/mnras/stz1264 2019

  70. [70]

    J., Sills, A., & Harris, W

    Webb, J. J., Sills, A., & Harris, W. E. 2013, ApJ, 779, 94, doi: 10.1088/0004-637X/779/2/94

    work page doi:10.1088/0004-637x/779/2/94 2013

  71. [71]

    2000, , 143, 9, 10.1051/aas:2000332

    Wenger, M., Ochsenbein, F., Egret, D., et al. 2000, A&AS, 143, 9, doi: 10.1051/aas:2000332 Wes McKinney. 2010, in Proceedings of the 9th Python in Science Conference, ed. St´ efan van der Walt & Jarrod Millman, 56 – 61, doi: 10.25080/Majora-92bf1922-00a

    work page internal anchor Pith review doi:10.1051/aas:2000332 2000

  72. [72]

    J., Cote, P., Jones, C., Forman, W., & Marzke, R

    West, M. J., Cote, P., Jones, C., Forman, W., & Marzke, R. O. 1995, ApJL, 453, L77, doi: 10.1086/309748

    work page doi:10.1086/309748 1995

  73. [73]

    C., & Harris, W

    Woodworth, S. C., & Harris, W. E. 2000, AJ, 119, 2699, doi: 10.1086/301400

    work page doi:10.1086/301400 2000