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The Spatial Distribution of Globular Cluster Systems in Early Type Galaxies: Estimation Procedure and Catalog of Properties for Globular Cluster Systems Observed with Deep Imaging Surveys

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read A uniform fitting procedure measures globular cluster system sizes for 118 early-type galaxies.

desk verdict Largest homogeneous GC system catalog to date, built with careful but rigid modeling; the constant-background assumption is a real structural caveat, but the paper deserves refereeing. read the letter →

arxiv 2411.17049 v1 pith:TW7CJ7RJ submitted 2024-11-26 astro-ph.GA

Sungsoon Lim , Eric W. Peng , Patrick Côté , Laura Ferrarese , Joel C. Roediger , Chengze Liu , Chelsea Spengler , Elisabeth Sola
show 13 more authors
Pierre-Alain Duc Laura V. Sales John P. Blakeslee Jean-Charles Cuillandre Patrick R. Durrell Eric Emsellem Stephen D. J. Gwyn Ariane Lançon Francine R. Marleau J. Christopher Mihos Oliver Müller Thomas H. Puzia Rubén Sánchez-Janssen
This is my paper · ORCID
classification astro-ph.GA
keywords globularclustersystemsearly-typegalaxiesSérsicprofileeffectiveradiusgalaxysurveysVirgospecificfrequencyGaussianmixturemodeling
verification ladder T0 review T1 audit T2 compute T3 formal

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 establishes a uniform procedure for measuring how far globular cluster systems extend around early-type galaxies and applies it to 118 galaxies from the NGVS and MATLAS deep surveys. It claims that a two-dimensional Sérsic profile plus a constant background, fitted to individual GC candidates and corrected for incompleteness, gives reliable effective radii, Sérsic indices, total GC numbers, and specific frequencies across a factor of more than a thousand in GC richness. The paper also reports that 68 of the systems have bimodal GC color distributions and fits the blue and red subpopulations separately. If correct, the catalog gives the largest homogeneous reference set for testing how GC system size tracks galaxy mass, environment, and assembly history.

What carries the argument

The central object is the modified two-dimensional Sérsic function $\Sigma(R) = \Sigma_e \exp(-b_n[(R/R_e)^{1/n} - 1]) + \Sigma_b$ (Eq. 4), fitted to individual GC candidates with an MCMC sampler. The constant background term $\Sigma_b$ absorbs contamination from foreground stars, background galaxies, and intracluster GCs; completeness corrections from injected artificial stars, plus HST/ACS catalogs in the centers of bright galaxies, handle incompleteness. When a neighbor contributes its own GC system, two such functions are fitted simultaneously under the same likelihood. Gaussian Mixture Modeling on background-subtracted colors decides bimodality and splits the blue and red subpopulations for their own spatial fits.

What would settle it

Refit one well-observed system, such as NGC4649, with a spatially varying background derived from independent deep wide-field imaging; if the effective radius and total GC count move by more than the quoted 1σ errors, the constant-background assumption is falsified. A second check: compare this catalog's total GC counts for low-mass galaxies with counts from future space-based wide surveys that cover the full halo without ground-based background modeling.

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Extended reading notes

Core claim

On its own terms, the paper's central contribution is a uniform measurement campaign: the spatial distribution of globular cluster systems in 118 early-type galaxies is described by a two-dimensional Sérsic function added to a constant background, fitted to individual GC candidates with MCMC. The paper reports effective radii from sub-arcminute scales to roughly 16 arcminutes, Sérsic indices mostly between 0.5 and 4, and total GC numbers ranging from fewer than ten in faint dwarfs to more than 17,000 in the richest giants. For the 68 systems whose color distributions are bimodal, the blue and red GC subpopulations are fitted separately, yielding distinct effective radii and peak colors. The paper argues that this constitutes the largest and most homogeneous sample to date for studying the spatial distribution of GC systems, and that the fitted profiles are consistent with published GC number density profiles where those exist.

Load-bearing premise

The load-bearing premise is that after masking, the remaining background contamination is a single constant across the whole fitted field, although intracluster GCs and unmasked companions can make the real background spatially varying.

Editorial extensions

If this is right

  • GC system effective radii across the full mass range become directly comparable, enabling scaling relations with galaxy stellar mass, luminosity, and environment that previously rested on 20–30 galaxies.
  • Separate blue and red effective radii for 68 bimodal systems provide spatial information on metal-poor and metal-rich subpopulations, allowing direct tests of two-phase galaxy formation.
  • The comparison with ACSVCS indicates that HST-only counts underestimate GC numbers in galaxies with roughly one hundred GCs, and more so below that, implying that wide-field ground-based coverage is necessary for total GC inventories.
  • The procedure supplies a ready pipeline for next-generation deep imaging surveys to produce GC system catalogs at larger scale.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If blue GC systems prove systematically more extended than red ones across the whole sample, the color bimodality itself becomes a spatial diagnostic of accretion history, a step beyond color-only studies.
  • For the sparsest systems (fewer than ~20 GCs), the constant-background term and the Sérsic parameters are likely degenerate; targeted deep halo imaging of low-mass dwarfs could test whether the reported sub-arcminute effective radii are physical or set by the fitting floor.
  • Extending the two-Sérsic simultaneous fitting to groups and clusters, not just close pairs, could resolve earlier literature discrepancies (e.g., NGC3608/3607) and provide a uniform way to separate intracluster GC populations.
  • The catalog's specific frequencies, computed in g′, could be re-expressed in V via standard colors to merge with older SN values, enabling a direct test of the U-shaped SN–magnitude relation over a wider baseline.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This paper presents the spatial distribution analysis of globular cluster (GC) systems for 118 early-type galaxies from the NGVS and MATLAS surveys. The authors describe a GC candidate selection procedure, fit two-dimensional Sérsic profiles plus a constant background to the GC number density distributions, estimate total GC numbers by integrating the fitted profiles and applying GCLF corrections, and classify GC color distributions as uni- or bimodal using Gaussian Mixture Modeling. For bimodal systems they provide separate blue/red effective radii. The resulting catalog includes effective radii, Sérsic indices, total GC numbers, and GC specific frequencies. The paper also compares its results with ACSVCS counts and literature profiles, and notes individual-galaxy peculiarities in an appendix.

Significance. If the catalog is reliable, this would be the largest homogeneous sample of GC system spatial distributions to date, providing effective radii and Sérsic indices for 118 galaxies, separate blue/red radii for 68 bimodal systems, and total GC numbers that can inform scaling relations and galaxy formation studies. The paper is careful in several respects: it performs extensive completeness tests with hundreds of thousands of artificial stars, uses simultaneous two-component fits for neighboring galaxies, and validates its GCLF width estimates against Villegas et al. (2010). However, the central catalog values rest on strong modeling assumptions, notably a constant background and a shape-only likelihood; these assumptions directly affect the headline quantities (Re,gc and N_GC). The significance of the catalog as a reference product therefore depends on whether these systematics are quantified and the affected values appropriately flagged.

major comments (3)
  1. [Section 2.8, Eqs. (4) and (8); Section 2.10; Table 2] The likelihood in Eq. (8) is a product of normalized radial probability densities, so the data constrain only the shape parameters and the ratio Σe/Σb, not the absolute amplitude of the Sérsic component. The absolute scale of Σe, and therefore the integrated total numbers N_GC in Table 2 (Section 2.10), is set by the Gaussian prior placed on Σb in Section 2.8. In dense Virgo environments, intracluster GCs and unmasked neighboring structures make a constant background (Eq. 4) questionable; the Appendix A note on NGC4649 explicitly attributes a factor-of-two discrepancy with literature to background estimation and states that the GC number density profile is not well fit by a single Sérsic profile. Because Re,gc and N_GC are the headline catalog quantities, the authors should demonstrate the robustness of their results to background modeling choices (e.g., a spatially varying background, or a background estimated from an outer annulus) and propagate the resulting systematic uncertainty into the catalog values and error bars.
  2. [Section 2.8, prior 0.25<n<8.0; Table 2] Several galaxies in Table 2 have Sérsic indices at the upper prior boundary with very small formal uncertainties: NGC3379 (n=7.97+0.02/-0.05), NGC3607 (7.97+0.03/-0.07), NGC4283 (7.99+0.01/-0.02), NGC4425 (7.85+0.09/-0.10), IC3383 (7.92+0.07/-0.19), IC798 (7.89+0.10/-0.34), and VCC1661 (7.87+0.10/-0.33). This pile-up indicates that the data prefer n>8 or a different functional form; the quoted parameter uncertainties are not credible in these cases, and Re,gc is likely biased. The paper should either widen the prior, adopt a different profile family, or explicitly flag these solutions as censored or upper-limit values in the catalog rather than reporting them as ordinary detections with small errors.
  3. [Section 3.2, Figure 8] The comparison with ACSVCS total numbers shows systematic differences that grow toward low N_GC, and the paper offers plausible explanations (spatial coverage, GC selection, GCLF treatment). However, both this study and Peng et al. (2008) rely on background subtraction, so agreement between them does not validate the absolute background scale. A direct check that compares the observed azimuthally averaged radial counts, after subtracting the fitted background, with the integral of the fitted Sérsic component would quantify how much of N_GC is actually required by the data rather than by the background prior. Such a test is important because the current method's N_GC values for low-mass galaxies are systematically higher than ACSVCS values even within matched apertures (right panel of Figure 8).
minor comments (5)
  1. [Section 2.7] The completeness-test text reports 'more than 150,000 artificial stars' and then 'about 200,000 artificial stars to each target image'; please clarify whether the former is a per-field total or a typo, since 200,000 per field across 118 fields would be far larger.
  2. [Section 2.8] The sentence 'We applied a completeness correction to each data point Ri' is ambiguous; presumably the model probability density is completeness-corrected as a function of radius, not the data point itself. Please rephrase.
  3. [Table 2 caption] The caption text about which column lists median GC colors and which lists specific frequencies should be checked against the actual table headers; the current wording appears inconsistent with the printed column order.
  4. [Appendix A, NGC4649] The placeholder 'Fig. ??' remains in the NGC4649 note; please replace it with the appropriate figure reference from the figure set.
  5. [Throughout] There are several typographical inconsistencies, including 'Ngc' instead of 'NGC' in the appendix notes and non-standard apostrophes in author names (e.g., 'De B´ortoli'); a careful proofreading pass is recommended.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the catalog values are fit-based estimates with external comparisons, not predictions equivalent to their inputs.

full rationale

The paper's derivation chain consists of fitting a 2D Sérsic plus constant background (Eq. 4) to GC candidate positions via an MCMC likelihood (Eq. 8), then reporting the fitted parameters (R_e, n) and integrating the fitted profile to obtain N_GC (Section 2.10). These are summary statistics of a model fit, not first-principles predictions, so deriving N_GC from the same Sérsic function is a definitional estimation step rather than a circularity. The likelihood in Eq. 8 is shape-only in the sense that the absolute normalization of the Sérsic component is tied to the adopted Sigma_b prior; this is a potential systematic bias (especially in dense Virgo fields, as the NGC4649 appendix note concedes: "This discrepancy is mainly due to background estimation"), but it is a modeling and identifiability limitation, not a circular reduction of an output to an input. The GCLF parameters adopted from Villegas et al. (2010) involve overlapping authorship, but they are an external empirical calibration and the paper checks the resulting GCLF widths against its own measurements (Figure 6), so the citation is not load-bearing circularity. External benchmarks (NGC4486 profile vs McLaughlin 1999 and Harris 2009; R_e comparisons with Kartha et al., Caso et al., and De Bortoli et al.; N_GC comparison with Peng et al. 2008) provide independent checks. The paper is a catalog and estimation paper and does not claim to derive a result from first principles; no step in the claimed chain reduces by construction to its own inputs.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The catalog depends on adopted GCLF calibration, selection thresholds, and strong priors on ellipticity and position angle. These are fitting hyperparameters and domain assumptions, not newly derived physical laws.

free parameters (6)
  • GCLF peak magnitude and dispersion = Adopted from Villegas et al. (2010) galaxy-luminosity relation
    Used in Section 2.10 to correct total GC numbers for the magnitude limit; not re-fitted here.
  • Magnitude limit for GC selection = g' = 24.5 mag
    Chosen in Section 2.5; affects completeness and sample size.
  • Point-source inverse concentration range = -0.08 <= Delta_m4-8 <= 0.08 (extended to 0.16 for nearby galaxies)
    Defined in Section 2.5; sets the stellar/boundary of compact sources.
  • Sersic parameter priors = 0.25 < n < 8.0, 0.05 < Re < 30 arcmin
    Flat priors in Section 2.8; restrict the fitted range and can affect posterior shapes.
  • Ellipticity and position angle priors = 0 <= epsilon < 0.1 and -10 deg < theta < 10 deg for most galaxies
    Section 2.8; strong circularity assumption that directly affects Re estimates for elongated systems.
  • Completeness function parameters m50 and alpha = Fitted per radial bin from artificial star tests
    Section 2.7; used in likelihood corrections; fitted to simulations.
assumptions (5)
  • domain assumption The GC surface density is described by a 2D Sersic function plus a constant background.
    Section 2.8, Eq. (4); the central model used for all fits.
  • domain assumption The GC luminosity function is a Gaussian with parameters depending only on host galaxy luminosity.
    Section 2.10, from Harris (2001) and Villegas et al. (2010); used for total count correction.
  • domain assumption GC color distributions are mixtures of Gaussian components, with bimodality judged by D > 2.
    Section 2.9, using GMM; defines blue/red subpopulations.
  • domain assumption The color-color selection polygons based on M87 spectroscopically confirmed GCs apply to all target galaxies.
    Section 2.5; assumes similar GC color properties across galaxies.
  • standard math The Ciotti and Bertin (1999) approximation for the Sersic bn constant is accurate.
    Section 2.8; used to convert index to profile normalization.

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Cite this review

Pith. "Pith review of The Spatial Distribution of Globular Cluster Systems in Early Type Galaxies: Estimation Procedure and Catalog of Properties for Globular Cluster Systems Observed with Deep Imaging Surveys." pith.science (2026). https://pith.science/paper/TW7CJ7RJ

@misc{pith2026241117049,
  author       = {Pith},
  title        = {Pith review of: The Spatial Distribution of Globular Cluster Systems in Early Type Galaxies: Estimation Procedure and Catalog of Properties for Globular Cluster Systems Observed with Deep Imaging Surveys},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TW7CJ7RJ}},
  note         = {Machine review of arXiv:2411.17049}
}
read the original abstract

We present an analysis of the spatial distribution of globular cluster (GC) systems of 118 nearby early-type galaxies in the Next Generation Virgo Cluster Survey (NGVS) and Mass Assembly of early-Type GaLAxies with their fine Structures (MATLAS) survey programs, which both used MegaCam on the Canada-France-Hawaii Telescope. We describe the procedure used to select GC candidates and fit the spatial distributions of GCs to a two-dimensional S\'ersic function, which provides effective radii (half number radii) and S\'ersic indices, and estimate background contamination by adding a constant term to the S'ersic function. In cases where a neighboring galaxy affects the estimation of the GC spatial distribution in the target galaxy, we fit two 2D S\'ersic functions, simultaneously. We also investigate the color distributions of GCs in our sample by using Gaussian Mixture Modeling. For GC systems with bimodal color distributions, we divide the GCs into blue and red subgroups and fit their respective spatial distributions with S\'ersic functions. Finally, we measure the total number of GCs based on our fitted S\'ersic function, and calculate the GC specific frequency.

Figures

Figures reproduced from arXiv: 2411.17049 by the authors.

Figure 1
Figure 1. (Left) Inverse concentration index, ∆m4−8, ver￾sus g-band magnitude for sources in the NGC4472 region. The red dotted box shows the point-like source region used for this galaxy. (Right) (u ∗ − g ′ )-(g ′ − i ′ ) color-color dia￾gram of point-like sources in the NGC4472 region. The red dashed polygon shows the globular cluster (GC) selection region used in this study, with red sources showing GC can￾didates [PITH_F… view at source ↗
Figure 2
Figure 2. (Left) Inverse concentration index, ∆m4−8, ver￾sus g-band magnitude for sources in the NGC524 region. The red dotted box shows the point-like source region used for this galaxy. (Right) (g ′ − r ′ )-(g ′ − i ′ ) color-color diagram of point-like sources in the NGC524 region. The red dashed polygon shows the GC selection region used in this study, with red sources showing GC candidates. the GC samples will still be i… view at source ↗
Figure 3
Figure 3. (a) Number density map of GC candidates in the NGC524 region. The colorbar is on logarithmic scale. Red circles represent 1Re,GC and 3Re, GC, respectively. Green shaded areas show the masked regions; (b) Two-dimensional and marginalized posterior probability density functions for the number density at the effective radius (Σe), the effective radius of the GC system (Re), S´ersic index (n), and constant background (Σ… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: (a) Number density map of GC candidates in the NGC821 region. The colorbar is on logarithmic scale. Red circles represent 1Re,GC and 3Re, GC, respectively. Green shaded areas show the masked regions, but there is no masked region in NGC821; (b) Two-dimensional and marg…
Figure 5
Figure 5. Figure 5: Comparison of the GC number density profile in NGC4486 with the literature. X-axis is the radial distance from the center of NGC4486, and Y-axis is the GC number density. Gray circles and red dashed line show data points and fitted results from this study. For comparis…
Figure 7
Figure 7. Figure 7: The GC specific frequencies (SN,g′ ) are plotted against the absolute g ′ -band magnitudes of their host galax￾ies. Gray filled circles show GC systems from this study; well-fitted systems (error of Re,gc < 50%) are shown with large heavy symbols, and MATLAS galaxies a…
Figure 8
Figure 8. Figure 8: Comparison of NGC,total from the ACSVCS results (Peng et al. 2008) with this study. (left panel): Direct comparison of the total number of GCs from between this study and ACSVCS. The black dashed line and the red dotted line show the one-to-one relation and the linear …
Figure 9
Figure 9. Figure 9: Comparison of Re,gc from literature with this study. The downward triangle shows NGC4365 (Blom et al. 2012); the triangle shows NGC4278 (Usher et al. 2013), and pentagons show three galaxies from the SLUGGS sur￾vey (Kartha et al. 2014, 2016), diamonds, NGC4472 and NGC4…
Figure 10
Figure 10. Figure 10: NGC936. See [PITH_FULL_IMAGE:figures/full_fig_p029_10.png]

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Works this paper leans on

93 extracted references · 27 canonical work pages · cited by 2 Pith papers

  1. [1]

    ˹ 6,K yxsf> vf DQ ADDDDDDG :

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    2021

  2. [2]

    R., Kartha , S

    Akhil , K. R., Kartha , S. S., & Mathew , B. 2024, , 530, 2907, 10.1093/mnras/stae1061

    work page doi:10.1093/mnras/stae1061 2024

  3. [3]

    A., & Blakeslee , J

    Alamo-Mart \' nez , K. A., & Blakeslee , J. P. 2017, , 849, 6, 10.3847/1538-4357/aa8f44

    doi:10.3847/1538-4357/aa8f44 2017

  4. [4]

    A., Chies-Santos , A

    Alamo-Mart \' nez , K. A., Chies-Santos , A. L., Beasley , M. A., et al. 2021, , 503, 2406, 10.1093/mnras/stab538

    doi:10.1093/mnras/stab538 2021

  5. [5]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

    doi:10.1051/0004-6361/201322068 2013

  6. [6]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

    doi:10.3847/1538-3881/aabc4f 2018

  7. [7]

    M., Lim , P

    Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, , 935, 167, 10.3847/1538-4357/ac7c74

    doi:10.3847/1538-4357/ac7c74 2022

  8. [9]

    1996, , 117, 393, 10.1051/aas:1996164

    Bertin , E., & Arnouts , S. 1996, , 117, 393, 10.1051/aas:1996164

    doi:10.1051/aas:1996164 1996

Show all 93 references
  1. [10]

    2020, , 498, 2138, 10.1093/mnras/staa2248

    B \' lek , M., Duc , P.-A., Cuillandre , J.-C., et al. 2020, , 498, 2138, 10.1093/mnras/staa2248

    2020 doi

  2. [11]

    P., Tonry , J

    Blakeslee , J. P., Tonry , J. L., & Metzger , M. R. 1997, , 114, 482, 10.1086/118488

    1997 doi

  3. [12]

    P., Jord \'a n , A., Mei , S., et al

    Blakeslee , J. P., Jord \'a n , A., Mei , S., et al. 2009, , 694, 556, 10.1088/0004-637X/694/1/556

    2009 doi

  4. [13]

    A., Foster , C., Romanowsky , A

    Blom , C., Forbes , D. A., Foster , C., Romanowsky , A. J., & Brodie , J. P. 2014, , 439, 2420, 10.1093/mnras/stu095

    2014 doi

  5. [14]

    R., & Forbes , D

    Blom , C., Spitler , L. R., & Forbes , D. A. 2012, , 420, 37, 10.1111/j.1365-2966.2011.19963.x

    2012

  6. [15]

    2003, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Boulade , O., Charlot , X., Abbon , P., et al. 2003, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 4841, Instrument Design and Performance for Optical/Infrared Ground-based Telescopes, ed. M. Iye & A. F. M. Moorwood , 72--81, 10.1117/12.459890

    2003 doi

  7. [16]

    P., Strader , J., Denicol \'o , G., et al

    Brodie , J. P., Strader , J., Denicol \'o , G., et al. 2005, , 129, 2643, 10.1086/429889

    2005 doi

  8. [17]

    P., Romanowsky , A

    Brodie , J. P., Romanowsky , A. J., Strader , J., et al. 2014, , 796, 52, 10.1088/0004-637X/796/1/52

    2014 doi

  9. [18]

    P., & Raimondo , G

    Cantiello , M., Blakeslee , J. P., & Raimondo , G. 2007, , 668, 209, 10.1086/521218

    2007 doi

  10. [19]

    2011, , 413, 813, 10.1111/j.1365-2966.2010.18174.x

    Cappellari , M., Emsellem , E., Krajnovi \'c , D., et al. 2011, , 413, 813, 10.1111/j.1365-2966.2010.18174.x

    2011

  11. [20]

    M., Alatalo , K., et al

    Cappellari , M., McDermid , R. M., Alatalo , K., et al. 2013, , 432, 1862, 10.1093/mnras/stt644

    2013 doi

  12. [21]

    2019, , 485, 382, 10.1093/mnras/stz383

    Carleton , T., Errani , R., Cooper , M., et al. 2019, , 485, 382, 10.1093/mnras/stz383

    2019 doi

  13. [22]

    P., De B \'o rtoli , B

    Caso , J. P., De B \'o rtoli , B. J., Ennis , A. I., & Bassino , L. P. 2019, , 488, 4504, 10.1093/mnras/stz2039

    2019 doi

  14. [23]

    L., Larsen , S

    Chies-Santos , A. L., Larsen , S. S., Wehner , E. M., et al. 2011, , 525, A19, 10.1051/0004-6361/201015681

    2011 doi

  15. [24]

    1999, , 352, 447, 10.48550/arXiv.astro-ph/9911078

    Ciotti , L., & Bertin , G. 1999, , 352, 447, 10.48550/arXiv.astro-ph/9911078

    1999 doi arXiv

  16. [25]

    E., Cohen , J

    C \^o t \'e , P., McLaughlin , D. E., Cohen , J. G., & Blakeslee , J. P. 2003, , 591, 850, 10.1086/375488

    2003 doi

  17. [26]

    P., Ferrarese , L., et al

    C \^o t \'e , P., Blakeslee , J. P., Ferrarese , L., et al. 2004, , 153, 223, 10.1086/421490

    2004 doi

  18. [27]

    J., Caso , J

    De B \'o rtoli , B. J., Caso , J. P., Ennis , A. I., & Bassino , L. P. 2022, , 510, 5725, 10.1093/mnras/stac010

    2022 doi

  19. [28]

    2022, , 664, A129, 10.1051/0004-6361/202142402

    de Brito Silva , D., Coelho , P., Cortesi , A., et al. 2022, , 664, A129, 10.1051/0004-6361/202142402

    2022 doi

  20. [29]

    2020, arXiv e-prints, arXiv:2007.13874, 10.48550/arXiv.2007.13874

    Duc , P.-A. 2020, arXiv e-prints, arXiv:2007.13874, 10.48550/arXiv.2007.13874

    2020 doi arXiv

  21. [30]

    2015, , 446, 120, 10.1093/mnras/stu2019

    Duc , P.-A., Cuillandre , J.-C., Karabal , E., et al. 2015, , 446, 120, 10.1093/mnras/stu2019

    2015 doi

  22. [31]

    R., Harris , W

    Durrell , P. R., Harris , W. E., Geisler , D., & Pudritz , R. E. 1996, , 112, 972, 10.1086/118071

    1996 doi

  23. [32]

    R., C \^o t \'e , P., Peng , E

    Durrell , P. R., C \^o t \'e , P., Peng , E. W., et al. 2014, , 794, 103, 10.1088/0004-637X/794/2/103

    2014 doi

  24. [33]

    2012, , 200, 4, 10.1088/0067-0049/200/1/4

    Ferrarese , L., C \^o t \'e , P., Cuillandre , J.-C., et al. 2012, , 200, 4, 10.1088/0067-0049/200/1/4

    2012 doi

  25. [34]

    A., et al

    Ferrarese , L., C \^o t \'e , P., MacArthur , L. A., et al. 2020, , 890, 128, 10.3847/1538-4357/ab339f

    2020 doi

  26. [35]

    Forbes , D. A. 1996, , 112, 954, 10.1086/118069

    1996 doi

  27. [36]

    2017, , 472, L104, 10.1093/mnrasl/slx148

    ---. 2017, , 472, L104, 10.1093/mnrasl/slx148

    2017 doi

  28. [37]

    A., Brodie , J

    Forbes , D. A., Brodie , J. P., & Huchra , J. 1997, , 113, 887, 10.1086/118308

    1997 doi

  29. [38]

    A., Georgakakis , A

    Forbes , D. A., Georgakakis , A. E., & Brodie , J. P. 2001, , 325, 1431, 10.1046/j.1365-8711.2001.04543.x

    2001

  30. [39]

    A., Faifer , F

    Forbes , D. A., Faifer , F. R., Forte , J. C., et al. 2004, , 355, 608, 10.1111/j.1365-2966.2004.08333.x

    2004

  31. [40]

    W., Lang , D., & Goodman , J

    Foreman-Mackey , D., Hogg , D. W., Lang , D., & Goodman , J. 2013, , 125, 306, 10.1086/670067

    2013 doi

  32. [41]

    Y., Puzia , T

    Georgiev , I. Y., Puzia , T. H., Hilker , M., & Goudfrooij , P. 2009, , 392, 879, 10.1111/j.1365-2966.2008.14104.x

    2009

  33. [42]

    2004, , 415, 499, 10.1051/0004-6361:20034610

    G \'o mez , M., & Richtler , T. 2004, , 415, 499, 10.1051/0004-6361:20034610

    2004 doi

  34. [43]

    Gwyn , S. D. J. 2008, , 120, 212, 10.1086/526794

    2008 doi

  35. [44]

    R., & Rhode , K

    Hargis , J. R., & Rhode , K. L. 2012, , 144, 164, 10.1088/0004-6256/144/6/164

    2012 doi

  36. [45]

    2014, , 796, 62, 10.1088/0004-637X/796/1/62

    ---. 2014, , 796, 62, 10.1088/0004-637X/796/1/62

    2014 doi

  37. [46]

    R., Rhode , K

    Hargis , J. R., Rhode , K. L., Strader , J., & Brodie , J. P. 2011, , 738, 113, 10.1088/0004-637X/738/1/113

    2011 doi

  38. [47]

    Harris , W. E. 2001, in Star Clusters, Vol. 28, 223, 10.1007/3-540-31634-5_2

    2001 doi

  39. [48]

    2009, , 703, 939, 10.1088/0004-637X/703/1/939

    ---. 2009, , 703, 939, 10.1088/0004-637X/703/1/939

    2009 doi

  40. [49]

    2023, , 265, 9, 10.3847/1538-4365/acab5c

    ---. 2023, , 265, 9, 10.3847/1538-4365/acab5c

    2023 doi

  41. [50]

    E., Blakeslee , J

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

    2017 doi

  42. [51]

    E., Morningstar , W., Gnedin , O

    Harris , W. E., Morningstar , W., Gnedin , O. Y., et al. 2014, , 797, 128, 10.1088/0004-637X/797/2/128

    2014 doi

  43. [52]

    E., Blakeslee , J

    Hartman , K., Harris , W. E., Blakeslee , J. P., Ma , C.-P., & Greene , J. E. 2023, , 953, 154, 10.3847/1538-4357/ace340

    2023 doi

  44. [53]

    J., & Robison , B

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

    2018 doi

  45. [54]

    P., C \^o t \'e , P., et al

    Jord \'a n , A., Blakeslee , J. P., C \^o t \'e , P., et al. 2007 a , , 169, 213, 10.1086/512778

    2007 doi

  46. [55]

    E., C \^o t \'e , P., et al

    Jord \'a n , A., McLaughlin , D. E., C \^o t \'e , P., et al. 2007 b , , 171, 101, 10.1086/516840

    2007 doi

  47. [56]

    S., Forbes , D

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

    2014 doi

  48. [57]

    S., Forbes , D

    Kartha , S. S., Forbes , D. A., Alabi , A. B., et al. 2016, , 458, 105, 10.1093/mnras/stw185

    2016 doi

  49. [58]

    Kundu , A., & Whitmore , B. C. 2001 a , , 122, 1251, 10.1086/322095

    2001 doi

  50. [59]

    2001 b , , 121, 2950, 10.1086/321073

    ---. 2001 b , , 121, 2950, 10.1086/321073

    2001 doi

  51. [60]

    E., Hempel , M., et al

    Kundu , A., Zepf , S. E., Hempel , M., et al. 2005, , 634, L41, 10.1086/498746

    2005 doi

  52. [61]

    A., Rhode , K

    Lambert , R. A., Rhode , K. L., & Vesperini , E. 2020, , 900, 45, 10.3847/1538-4357/abaab2

    2020 doi

  53. [62]

    S., & Brodie , J

    Larsen , S. S., & Brodie , J. P. 2000, , 120, 2938, 10.1086/316847

    2000 doi

  54. [63]

    S., Brodie , J

    Larsen , S. S., Brodie , J. P., Huchra , J. P., Forbes , D. A., & Grillmair , C. J. 2001, , 121, 2974, 10.1086/321081

    2001 doi

  55. [64]

    Lee , M. G. 2003, Journal of Korean Astronomical Society, 36, 189, 10.5303/JKAS.2003.36.3.189

    2003 doi

  56. [65]

    G., Kim , E., & Geisler , D

    Lee , M. G., Kim , E., & Geisler , D. 1998, , 115, 947, 10.1086/300249

    1998 doi

  57. [66]

    G., Park , H

    Lee , M. G., Park , H. S., & Hwang , H. S. 2010, Science, 328, 334, 10.1126/science.1186496

    2010 doi

  58. [67]

    G., Park , H

    Lee , M. G., Park , H. S., Kim , E., et al. 2008, , 682, 135, 10.1086/587469

    2008 doi

  59. [68]

    W., C \^o t \'e , P., et al

    Lim , S., Peng , E. W., C \^o t \'e , P., et al. 2018, , 862, 82, 10.3847/1538-4357/aacb81

    2018 doi

  60. [69]

    W., Duc , P.-A., et al

    Lim , S., Peng , E. W., Duc , P.-A., et al. 2017, , 835, 123, 10.3847/1538-4357/835/2/123

    2017 doi

  61. [70]

    W., et al

    Lim , S., C \^o t \'e , P., Peng , E. W., et al. 2020, , 899, 69, 10.3847/1538-4357/aba433

    2020 doi

  62. [71]

    W., C \^o t \'e , P., et al

    Lim , S., Peng , E. W., C \^o t \'e , P., et al. 2024, , 966, 168, 10.3847/1538-4357/ad3444

    2024 doi

  63. [72]

    W., Toloba , E., et al

    Liu , C., Peng , E. W., Toloba , E., et al. 2015, , 812, L2, 10.1088/2041-8205/812/1/L2

    2015 doi

  64. [73]

    Maybhate , A., Goudfrooij , P., Chandar , R., & Puzia , T. H. 2010, , 721, 893, 10.1088/0004-637X/721/1/893

    2010 doi

  65. [74]

    McLaughlin , D. E. 1999, , 117, 2398, 10.1086/300836

    1999 doi

  66. [75]

    P., C \^o t \'e , P., et al

    Mei , S., Blakeslee , J. P., C \^o t \'e , P., et al. 2007, , 655, 144, 10.1086/509598

    2007 doi

  67. [76]

    W., & Lotz , J

    Miller , B. W., & Lotz , J. M. 2007, , 670, 1074, 10.1086/522323

    2007 doi

  68. [77]

    L., & Gnedin , O

    Muratov , A. L., & Gnedin , O. Y. 2010, , 718, 1266, 10.1088/0004-637X/718/2/1266

    2010 doi

  69. [78]

    W., Jord \'a n , A., C \^o t \'e , P., et al

    Peng , E. W., Jord \'a n , A., C \^o t \'e , P., et al. 2006, , 639, 95, 10.1086/498210

    2006 doi

  70. [79]

    2008, , 681, 197, 10.1086/587951

    ---. 2008, , 681, 197, 10.1086/587951

    2008 doi

  71. [80]

    W., Ferguson , H

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

    2011 doi

  72. [81]

    J., Hilker , M., van der Burg , R

    Prole , D. J., Hilker , M., van der Burg , R. F. J., et al. 2019, , 484, 4865, 10.1093/mnras/stz326

    2019 doi

  73. [82]

    H., Zepf , S

    Puzia , T. H., Zepf , S. E., Kissler-Patig , M., et al. 2002, , 391, 453, 10.1051/0004-6361:20020835

    2002 doi

  74. [83]

    Rhode , K. L. 2012, , 144, 154, 10.1088/0004-6256/144/5/154

    2012 doi

  75. [84]

    L., & Zepf , S

    Rhode , K. L., & Zepf , S. E. 2001, , 121, 210, 10.1086/318039

    2001 doi

  76. [85]

    2004, , 127, 302, 10.1086/380616

    ---. 2004, , 127, 302, 10.1086/380616

    2004 doi

  77. [86]

    L., Zepf , S

    Rhode , K. L., Zepf , S. E., Kundu , A., & Larner , A. N. 2007, , 134, 1403, 10.1086/521397

    2007 doi

  78. [87]

    R., & Forbes , D

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

    2009

  79. [88]

    R., Forbes , D

    Spitler , L. R., Forbes , D. A., Strader , J., Brodie , J. P., & Gallagher , J. S. 2008, , 385, 361, 10.1111/j.1365-2966.2007.12823.x

    2008

  80. [89]

    M., Arimoto , N., et al

    Tamura , N., Sharples , R. M., Arimoto , N., et al. 2006, , 373, 588, 10.1111/j.1365-2966.2006.11067.x

    2006

  81. [90]

    A., Spitler , L

    Usher , C., Forbes , D. A., Spitler , L. R., et al. 2013, , 436, 1172, 10.1093/mnras/stt1637

    2013 doi

  82. [91]

    2018, , 856, L30, 10.3847/2041-8213/aab60b

    van Dokkum , P., Cohen , Y., Danieli , S., et al. 2018, , 856, L30, 10.3847/2041-8213/aab60b

    2018 doi

  83. [92]

    W., et al

    Villegas , D., Jord \'a n , A., Peng , E. W., et al. 2010, , 717, 603, 10.1088/0004-637X/717/2/603

    2010 doi

  84. [93]

    D., Dowell , J

    Young , M. D., Dowell , J. L., & Rhode , K. L. 2012, , 144, 103, 10.1088/0004-6256/144/4/103

    2012 doi

  85. [94]

    2015, , 799, 159, 10.1088/0004-637X/799/2/159

    Zaritsky , D., Aravena , M., Athanassoula , E., et al. 2015, , 799, 159, 10.1088/0004-637X/799/2/159

    2015 doi

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.