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Leo I: the classical dwarf spheroidal galaxy with the highest dark-matter density

T0 review · 3 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read Leo I has the highest dark-matter density of classical dwarfs

desk verdict A clear, honest analysis whose headline claim of highest DM density is conditional on one dataset—the paper's own sensitivity test shows the value drops to normal without the central LOSVDs. read the letter →

arxiv 2506.13847 v2 pith:6RIHUMYM submitted 2025-06-16 astro-ph.GA

classification astro-ph.GA
keywords LeoIdwarfspheroidalgalaxiesdarkmatterdensitycore-cuspproblemaction-baseddistributionfunctionsstellarkinematicspericentre-densityanticorrelationJ-factor
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 argues that Leo I, the most distant classical dwarf spheroidal satellite of the Milky Way, is also the one with the highest central dark-matter density. Using dynamical models based on action-based distribution functions, the authors infer a dark-matter density at 150 pc of $\rho_{150}=35.5_{-4.7}^{+3.8}\times10^7\,M_\odot\,\mathrm{kpc}^{-3}$, roughly twice previous estimates, and an inner density profile that flattens into a core with radius $r_c=72^{+40}_{-32}$ pc. If correct, this makes Leo I the anchor point of the observed anticorrelation between orbital pericentre and central dark-matter density, sharpening that relation and tightening constraints on self-interacting dark matter. It also places Leo I in the cored rather than cusped camp, although the paper shows that this conclusion depends on the central velocity data included in the fit.

What carries the argument

The central object is a family of analytic distribution functions of the action integrals, $f_i(\mathbf{J})$ (the orbital labels that specify each orbit), one for the stellar component and one for the dark-matter halo, with an optional central black-hole potential added to the total gravitational potential. These functions are flexible enough to produce either cusped or cored density profiles with adjustable inner and outer slopes and velocity anisotropy, and the Poisson equation is solved self-consistently for each component. The machinery works by fitting, simultaneously, the ground-based surface-brightness profile, the central line-of-sight velocity distributions from integral-field spectroscopy, and the outer velocity-dispersion profile from discrete radial velocities. The higher central dark-matter density is driven by the central velocity distributions, whose dispersions reach about 12 km/s within 110 pc and require more mass in the inner regions.

What would settle it

An independent measurement of Leo I's inner velocity dispersion profile — for example, high-resolution spectroscopy inside 100 pc showing dispersions closer to 8 km/s than to 12 km/s — would bring $\rho_{150}$ down toward the values found before this paper; the paper's own fit without those central velocities already demonstrates that collapse.

Watch

Extended reading notes

Core claim

According to the authors, Leo I is the classical dwarf spheroidal galaxy with the highest dark-matter density, with $\rho_{150}=35.5_{-4.7}^{+3.8}\times10^7\,M_\odot\,\mathrm{kpc}^{-3}$ at 150 pc. The inferred density profile has logarithmic slope $\gamma_{150}=-0.89_{-0.17}^{+0.21}$ at that radius, consistent with earlier determinations, but flattens into a core at smaller radii, with core radius $r_c=72^{+40}_{-32}$ pc. The galaxy is dark-matter dominated throughout: the dynamical-to-stellar mass ratio is about 6.4 within the effective radius and 32.5 within the truncation radius. The paper also shows that removing the central line-of-sight velocity distributions from the fit brings the density back into agreement with previous studies, identifying that dataset as the source of the higher normalization. The inferred decay and annihilation factors, $\log D(0.5^\circ)=17.94_{-0.25}^{+0.17}$ and $\log J(0.5^\circ)=18.13_{-0.18}^{+0.17}$ in the stated units, remain within literature ranges, so Leo I is not promoted to a leading indirect-detection target.

Load-bearing premise

The higher density rests on the assumption that the central stellar velocity measurements from integral-field spectroscopy, which reach about 12 km/s in the inner 110 pc, are accurate; when those measurements are removed from the fit, the inferred density falls back to the values found by earlier studies.

Editorial extensions

If this is right

  • Leo I becomes the decisive anchor of the pericentre--density anticorrelation: combining its small pericentre of $35^{+24}_{-20}$ kpc with the new high density makes the trend steeper and potentially more significant.
  • The inferred profile is cored only in the very centre ($r_c=72^{+40}_{-32}$ pc) and mildly cusped at 150 pc ($\gamma_{150}=-0.89^{+0.21}_{-0.17}$), which is consistent with the R19 comparison profile and narrows the conflict over Leo I's inner slope.
  • Self-interacting dark-matter models require a larger cross-section to explain Leo I's high central density, and velocity-independent SIDM becomes harder to reconcile with the observed $\rho_{150}$--$r_{\rm peri}$ relation.
  • The annihilation and decay factors stay within previously published ranges, so even though Leo I is the densest classical dSph, it is not the best target for gamma-ray searches for dark matter.

Reading between the lines

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

  • An implication the authors leave implicit is that the core-versus-cusp classification of Leo I is dataset-dependent: with the central integral-field velocities the inner profile is cored, without them it is consistent with cuspy models, so future work should treat this classification as conditional on the data.
  • A testable extension would be to apply the same action-based models to the other classical dSphs while including their central integral-field velocity data; if those galaxies also show a central dispersion rise, their published $\rho_{150}$ values could be systematically underestimated.
  • If the sharpened pericentre--density relation is real, it strengthens tidal or self-interacting explanations for satellite structure and predicts that ultrafaint dwarfs with small pericentres should show similarly high central densities.
  • Space-based surface-brightness data of the quality the paper expects from Euclid would provide a direct check on the ground-based photometry that the model currently fits, and could resolve whether the high central density is real or a product of photometric systematics.
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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. The paper re-analyzes the dynamical models of Pascale et al. (2024) for the dwarf spheroidal galaxy Leo I and derives the dark matter (DM) density profile, logarithmic slope, core radius, and J/D factors. The central claim is that Leo I has the highest DM density among classical dSphs, with rho150 = 35.5_{-4.7}^{+3.8} x 10^7 Msun kpc^-3 at 150 pc, a cored central profile with core radius r_c = 72^{+40}_{-32} pc, and slope gamma150 = -0.89^{+0.21}_{-0.17}. The authors also place this measurement in the context of the pericenter-anticorrelation and DM indirect detection. Importantly, the paper reports its own control test: excluding the central LOSVDs from Bustamante-Rosell et al. (2021) yields a DM density profile consistent with previous estimates, indicating that the high central density is driven by that dataset.

Significance. If the central claim is robust, the result is significant for the core-cusp problem, for self-interacting dark matter models, and for the interpretation of the rho150-rperi anticorrelation. The paper is commendably transparent: it performs a control fit without the central LOSVDs, shows the resulting profile drop, and openly discusses the role of the additional kinematic dataset. It also provides posterior-derived quantities and profiles that are useful for future studies. However, the main headline result is conditional on the reliability of a single dataset and on assumptions about the surface brightness profile and distance; the quoted error bars do not cover the systematic shift demonstrated by the paper's own control model. The significance of the superlative is therefore not established as a robust property of Leo I.

major comments (3)
  1. [Section 3.1, Fig. 1, Table 3] The central claim that Leo I has the highest DM density among classical dSphs is not robust to the inclusion/exclusion of the central LOSVDs. The paper's own no-LOSVD fit yields a DM density profile and rho150 consistent with previous studies (R19, H20), as shown by the blue dashed line in Fig. 1 and stated in Section 3.1. The 1-sigma uncertainty quoted in Table 3 for rho150 is conditioned on the full dataset, so it does not cover this systematic shift. The paper does not report the numerical value of rho150 for the no-LOSVD model, making the shift difficult to quantify. Since the abstract and conclusions present rho150 as a property of Leo I, the authors should either provide external validation of the central LOSVDs, perform sensitivity tests to individual bins, or reframe the claim as conditional on the Bustamante-Rosell et al. (2021) dataset. As written, the superlative is a property of a particular model-data combination rather than a robust empirical result.
  2. [Section 2.1, Table 1] The quoted uncertainties on rho150, r_c, gamma150, and the dynamical masses are purely statistical and are computed at a fixed distance D = 256.7 kpc. The distance uncertainty of ±13.3 kpc (Table 1) is not propagated into any of the derived quantities, even though the physical scale, luminosity, and thus the inferred DM density depend on distance. The comparison with other dSphs in Fig. 1 and the claim of the 'highest DM density' also involve different distances and surface-brightness modeling across studies, none of which are included in the error budget. A proper systematic treatment of the distance uncertainty is required before the comparative claim can be considered supported.
  3. [Section 3.1, Fig. 2] The high central density is driven by LOSVDs with velocity dispersions up to ~12 km/s within 110 pc, whereas the outer profile from Mateo et al. (2008) and H20's inner values are lower (~8 km/s). The paper acknowledges photometric systematics in Section 2.1 but does not assess kinematic systematics: unresolved binaries, residual rotation, membership contamination, or template mismatch could produce a similar central velocity-dispersion excess. Since the entire high-rho150 result hinges on these data, a bin-by-bin jackknife or a test with alternative kinematic cuts is needed. Without such tests, the possibility that the central LOSVDs are biased cannot be excluded, and the main claim remains fragile.
minor comments (5)
  1. [Table 3 note] The note contains the typo 'annhilation'; it should be 'annihilation'.
  2. [Figure 4] The axis labels in Fig. 4 use 'Gev' and 'Gev cm^-2'; these should be 'GeV' and 'GeV cm^-2'.
  3. [Introduction] The text contains the typo 'baryions'; it should be 'baryons'.
  4. [Section 3.2, Fig. 3] When adding the new Leo I rho150 point to the rho150-rperi diagram, the authors do not refit the anticorrelation or quantify the change in its statistical significance. A quantitative refit would strengthen the claim that the new measurement 'could significantly steepen' the anticorrelation.
  5. [Section 3.1] The statement attributing H20's large error bars to their use of flattened models is speculative; consider softening or providing a more quantitative justification.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: rho150 is a fitted model output, not a self-defined prediction; the no-LOSVD rerun is a sensitivity test, not a circular validation.

full rationale

The paper explicitly builds on the dynamical models of Pascale et al. (2024, P24) and analyzes the posterior samples of those models. The headline quantity rho150 is computed as a percentile of the marginalized posterior distribution of the DM density at 150 pc; it is a derived summary of a fit to photometric and kinematic data, not an input used to define the model. No equation in the paper defines the DM density in terms of rho150, nor is rho150 used as a prior or constraint. The statement that the central LOSVDs are 'the primary reason for our higher inferred DM density' is a data-sensitivity finding, and the rerun without those LOSVDs is a standard robustness check; it shows that the result depends on a particular dataset, but that is not circular. Comparisons to R19, H20, Kaplinghat et al. (2019), and Andrade et al. (2024) provide external benchmarks. The only self-citation is to P24 for the models and Bayesian machinery, and P24 is a published, peer-reviewed analysis using independent data (Bustamante-Rosell et al. 2021 and Mateo et al. 2008); citing it for methodological details does not make the present inference circular. Although the text loosely refers to 'accurate predictions' for the DM distribution, this is ordinary model-output language, not a claim that an independent quantity is predicted from itself. No circular step can be exhibited, so the score is 0.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central claim is a measurement derived from a multi-parameter Bayesian model posterior inherited from P24. The density profile shape and normalization are fitted degrees of freedom, not derived from first principles. The result is strongly sensitive to the inclusion of the central LOSVDs and to the adopted distance, and these systematic uncertainties are not included in the quoted error bars.

free parameters (3)
  • DM halo mass log M_DM = 8.846 (median from P24 posterior)
    Normalization of the DM component in Eq. (3); directly sets rho150. It is fitted to photometry and kinematics in P24.
  • DM inner slope parameters (Gamma_DM, B_DM, eta_DM) = Gamma=1.301, B=5.479, eta=2.985 (medians)
    Shape parameters of the action-based DF (Eq. 3) that control whether the profile is cored or cuspy. These are fitted, not derived.
  • Distance D = 256.7 kpc (adopted)
    Fixed from literature (Mendez et al. 2002; Pacucci et al. 2023) with a 13.3 kpc uncertainty that is not propagated into rho150, gamma150, or the J/D factors.
assumptions (4)
  • domain assumption The galaxy is in dynamical equilibrium and is spherically symmetric.
    The DFs depend only on action integrals with spherical symmetry (Eq. 3 and Section 2.2), yet Leo I has ellipticity 0.31. Flattening is ignored, which can bias density estimates.
  • domain assumption The surface brightness profile from ground-based SDSS g-band imaging (Bustamante-Rosell et al. 2021) accurately represents the stellar distribution after corrections.
    Section 2.1 acknowledges crowding and background-subtraction issues; the model fits this profile simultaneously with kinematics, but any bias in the profile propagates into the DM density.
  • domain assumption The central LOSVDs from Bustamante-Rosell et al. (2021) are unbiased tracers of the inner stellar kinematics.
    These data drive the higher rho150; if their velocity dispersions are overestimated by systematics, the central claim fails. The paper tests exclusion but does not validate the LOSVDs against an independent dataset.
  • standard math Uniform priors on model parameters (Table 2) are sufficiently broad to avoid biasing posteriors.
    Bayesian inference uses these priors; the paper quotes posterior percentiles without a robustness check of prior boundaries.

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Cite this review

Pith. "Pith review of Leo I: the classical dwarf spheroidal galaxy with the highest dark-matter density." pith.science (2026). https://pith.science/paper/6RIHUMYM

@misc{pith2026250613847,
  author       = {Pith},
  title        = {Pith review of: Leo I: the classical dwarf spheroidal galaxy with the highest dark-matter density},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/6RIHUMYM}},
  note         = {Machine review of arXiv:2506.13847}
}
abstract

Dwarf spheroidal galaxies (dSphs) are known for being strongly dominated by dark matter (DM), which makes them convenient targets for investigating the DM nature and distribution. Recently, renewed interest in the dSph Leo I has resulted from claims suggesting the presence of a central supermassive black hole (BH), with mass estimates that challenge the typical expectations for dSphs, which are generally thought to host intermediate-mass black holes (IMBHs). However, Pascale et al. 2024 presented new upper limits on the BH mass, which are consistent with the range for IMBHs, solving the concerns raised in previous studies. Building on the analysis of Pascale et al. 2024, we examine the DM properties of Leo I inferred from the dynamical models of that paper. Our results indicate that Leo I is the galaxy with the highest DM density among the classical dSphs, with a central DM density (measured at a distance of $150$ pc from the galaxy centre) $\rho_{150}=35.5_{-4.7}^{+3.8}\times10^7\,M_\odot\,$kpc$^{-3}$. The DM density profile has logarithmic slope $\gamma_{150}=-0.89_{-0.17}^{+0.21}$ at $150$ pc, in line with literature values. At smaller distances the DM distribution flattens into a core, with a core radius of $r_c=72^{+40}_{-32}$ pc. Combined with the small pericentric distance of Leo I's orbit in the Milky Way, the new estimate of $\rho_{150}$ makes Leo I decisive in the study of the anticorrelation between pericentre and central DM density, and suggests that the anticorrelation could be significantly steeper and more pronounced than previously estimated. Despite its DM dominance, Leo I does not emerge as the most favorable target for indirect DM detection: the inferred DM decay $D$ and annihilation $J$ factors, $\log D(0.5^{\circ})$ [GeV cm$^{-2}$] = $17.94_{-0.25}^{+0.17}$ and $\log J(0.5^{\circ})$ [GeV$^2$ cm$^{-5}$]= $18.13_{-0.18}^{+0.17}$ are consistent with previous estimates.

Figures

Figures reproduced from arXiv: 2506.13847 by the authors.

Figure 1
Figure 1. DM Properties. Left panel: DM density profile from the reference model (black solid line) with 1 [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Kinematic properties of Leo I. Top panel: Median l.o.s. stellar velocity dispersion profile from [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. rperi - ρ150 anticorrelation for the eight classical dSphs from Cardona-Barrero et al. (2023). Central ρ150 densities are taken from Kaplinghat et al. (2019), while pericentric distances are from Battaglia et al. (2022). The orange band represents the fit to the grey and black points as derived by Cardona-Barrero et al. (2023). The blue point corresponds to the measurement for Leo I, with ρ150 derived in this work. … view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Left panel: DM decay D-factor computed from the reference model of P24 (black solid line) together with the 1σ and 3σ bands. Right panel: same as the left panel but showing the model’s J-factor profile. The small insets in the bottom panel show the models D and J facto…

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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Reference graph

Works this paper leans on

62 extracted references · 47 canonical work pages · cited by 2 Pith papers

  1. [1]

    2015, Phys

    Ackermann, M., Albert, A., Anderson, B., et al. 2015, Phys. Rev. Lett., 115, 231301

  2. [2]

    Amorisco, N. C. & Evans, N. W. 2011, MNRAS, 411, 2118

  3. [3]

    E., Kaplinghat, M., & Valli, M

    Andrade, K. E., Kaplinghat, M., & Valli, M. 2024, MNRAS, 532, 4157

  4. [4]

    & Nipoti, C

    Battaglia, G. & Nipoti, C. 2022, Nature Astronomy, 6, 659

  5. [5]

    F., & Fritz, T

    Battaglia, G., Taibi, S., Thomas, G. F., & Fritz, T. K. 2022, A&A, 657, A54

  6. [6]

    R., & Sollima, A

    Bellazzini, M., Gennari, N., Ferraro, F. R., & Sollima, A. 2004, MNRAS, 354, 708

  7. [7]

    2014, MNRAS, 440, 787

    Binney, J. 2014, MNRAS, 440, 787

  8. [8]

    & Tremaine, S

    Binney, J. & Tremaine, S. 2008, Galactic Dynamics: Second Edition (Princeton University Press)

Show all 62 references
  1. [9]

    K., Kumar, J., Pace, A

    Boddy, K. K., Kumar, J., Pace, A. B., Runburg, J., & Strigari, L. E. 2020, Phys. Rev. D, 102, 023029

  2. [10]

    2015, MNRAS, 453, 849

    Bonnivard, V ., Combet, C., Daniel, M., et al. 2015, MNRAS, 453, 849

  3. [11]

    Breddels, M. A. & Helmi, A. 2013, A&A, 558, A35

  4. [12]

    Bullock, J. S. & Boylan-Kolchin, M. 2017, ARA&A, 55, 343

  5. [13]

    J., Noyola, E., Gebhardt, K., et al

    Bustamante-Rosell, M. J., Noyola, E., Gebhardt, K., et al. 2021, ApJ, 921, 107

  6. [14]

    2023, MNRAS, 522, 3058

    Cardona-Barrero, S., Battaglia, G., Nipoti, C., & Di Cintio, A. 2023, MNRAS, 522, 3058

  7. [15]

    Cole, D. R. & Binney, J. 2017, MNRAS, 465, 798

  8. [16]

    Correa, C. A. 2021, MNRAS, 503, 920

  9. [17]

    A., Wyithe, J

    Correa, C. A., Wyithe, J. S. B., Schaye, J., & Duffy, A. R. 2015, MNRAS, 452, 1217 Crnogorˇcevi´c, M. & Linden, T. 2024, Phys. Rev. D, 109, 083018

  10. [18]

    C., Bertin, E., Bolzonella, M., et al

    Cuillandre, J. C., Bertin, E., Bolzonella, M., et al. 2025, A&A, 697, A6 de Blok, W. J. G. 2010, Advances in Astronomy, 2010, 789293 Di Mauro, M., Stref, M., & Calore, F. 2022, Phys. Rev. D, 106, 123032

  11. [19]

    2022, Phys

    Ebisu, T., Ishiyama, T., & Hayashi, K. 2022, Phys. Rev. D, 105, 023016 Article number, page 9 of 10 A&A proofs:manuscript no. main

  12. [20]

    W., Sanders, J

    Evans, N. W., Sanders, J. L., & Geringer-Sameth, A. 2016, Phys. Rev. D, 93, 103512

  13. [21]

    K., Battaglia, G., Pawlowski, M

    Fritz, T. K., Battaglia, G., Pawlowski, M. S., et al. 2018, A&A, 619, A103 Gaia Collaboration, Helmi, A., van Leeuwen, F., et al. 2018, A&A, 616, A12

  14. [22]

    M., & Walker, M

    Geringer-Sameth, A., Koushiappas, S. M., & Walker, M. 2015, ApJ, 801, 74

  15. [23]

    I., Wyse, R

    Gilmore, G., Wilkinson, M. I., Wyse, R. F. G., et al. 2007, ApJ, 663, 948

  16. [24]

    2015, MNRAS, 448, 792

    Governato, F., Weisz, D., Pontzen, A., et al. 2015, MNRAS, 448, 792

  17. [25]

    2012, MNRAS, 422, 1231

    Governato, F., Zolotov, A., Pontzen, A., et al. 2012, MNRAS, 422, 1231

  18. [26]

    2020, ApJ, 904, 45

    Hayashi, K., Chiba, M., & Ishiyama, T. 2020, ApJ, 904, 45

  19. [27]

    2016, MNRAS, 461, 2914

    Hayashi, K., Ichikawa, K., Matsumoto, S., et al. 2016, MNRAS, 461, 2914

  20. [28]

    V ., Gullieuszik, M., Rizzi, L., et al

    Held, E. V ., Gullieuszik, M., Rizzi, L., et al. 2010, MNRAS, 404, 1475

  21. [29]

    1990, ApJ, 356, 359

    Hernquist, L. 1990, ApJ, 356, 359

  22. [30]

    Hoof, S., Geringer-Sameth, A., & Trotta, R. 2020, J. Cosmology Astropart. Phys., 2020, 012

  23. [31]

    P., Tremaine, S., & Witten, E

    Hui, L., Ostriker, J. P., Tremaine, S., & Witten, E. 2017, Phys. Rev. D, 95, 043541

  24. [32]

    K., Annibali, F., Cuillandre, J

    Hunt, L. K., Annibali, F., Cuillandre, J. C., et al. 2025, A&A, 697, A9

  25. [33]

    & Hatzidimitriou, D

    Irwin, M. & Hatzidimitriou, D. 1995, MNRAS, 277, 1354

  26. [34]

    2019, MNRAS, 490, 231

    Kaplinghat, M., Valli, M., & Yu, H.-B. 2019, MNRAS, 490, 231

  27. [35]

    I., Kleyna, J

    Koch, A., Wilkinson, M. I., Kleyna, J. T., et al. 2007, ApJ, 657, 241

  28. [36]

    & Cole, S

    Lacey, C. & Cole, S. 1993, MNRAS, 262, 627

  29. [37]

    & Cole, S

    Lacey, C. & Cole, S. 1994, MNRAS, 271, 676

  30. [38]

    2021, Phys

    Li, S., Liang, Y .-F., & Fan, Y .-Z. 2021, Phys. Rev. D, 104, 083037

  31. [39]

    O., da Costa, L

    Marzke, R. O., da Costa, L. N., Pellegrini, P. S., Willmer, C. N. A., & Geller, M. J. 1998, ApJ, 503, 617

  32. [40]

    W., & Walker, M

    Mateo, M., Olszewski, E. W., & Walker, M. G. 2008, ApJ, 675, 201

  33. [41]

    McConnachie, A. W. 2012, AJ, 144, 4 Méndez, B., Davis, M., Moustakas, J., et al. 2002, AJ, 124, 213 Muñoz, R. R., Côté, P., Santana, F. A., et al. 2018, ApJ, 860, 66

  34. [42]

    & Binney, J

    Nipoti, C. & Binney, J. 2015, MNRAS, 446, 1820

  35. [43]

    Nipoti, C., Pascale, R., & Arroyo-Polonio, J. M. 2024, arXiv e-prints, arXiv:2411.05084

  36. [44]

    2023, ApJ, 956, L37

    Pacucci, F., Ni, Y ., & Loeb, A. 2023, ApJ, 956, L37

  37. [45]

    2019, MNRAS, 488, 2423

    Pascale, R., Binney, J., Nipoti, C., & Posti, L. 2019, MNRAS, 488, 2423

  38. [46]

    2024, A&A, 684, L19

    Pascale, R., Nipoti, C., Calura, F., & Della Croce, A. 2024, A&A, 684, L19

  39. [47]

    2018, MNRAS, 480, 927

    Pascale, R., Posti, L., Nipoti, C., & Binney, J. 2018, MNRAS, 480, 927

  40. [48]

    Read, J. I. & Gilmore, G. 2005, MNRAS, 356, 107

  41. [49]

    Read, J. I. & Steger, P. 2017, MNRAS, 471, 4541

  42. [50]

    I., Walker, M

    Read, J. I., Walker, M. G., & Steger, P. 2019, MNRAS, 484, 1401

  43. [51]

    I., Wilkinson, M

    Read, J. I., Wilkinson, M. I., Evans, N. W., Gilmore, G., & Kleyna, J. T. 2006, MNRAS, 366, 429

  44. [52]

    H., Kelley, T., Bullock, J

    Robles, V . H., Kelley, T., Bullock, J. S., & Kaplinghat, M. 2019, MNRAS, 490, 2117

  45. [53]

    2021, MNRAS, 501, 3962

    Ruiz-Lara, T., Gallart, C., Monelli, M., et al. 2021, MNRAS, 501, 3962

  46. [54]

    V ., Wetzel, A., & Fattahi, A

    Sales, L. V ., Wetzel, A., & Fattahi, A. 2022, Nature Astronomy, 6, 897

  47. [55]

    T., Besla, G., van der Marel, R

    Sohn, S. T., Besla, G., van der Marel, R. P., et al. 2013, ApJ, 768, 139

  48. [56]

    E., Bullock, J

    Strigari, L. E., Bullock, J. S., Kaplinghat, M., et al. 2008, Nature, 454, 1096

  49. [57]

    E., Frenk, C

    Strigari, L. E., Frenk, C. S., & White, S. D. M. 2017, ApJ, 838, 123

  50. [58]

    S., Steigman, G., & Krauss, L

    Turner, M. S., Steigman, G., & Krauss, L. M. 1984, Phys. Rev. Lett., 52, 2090

  51. [59]

    2019, MNRAS, 482, 1525

    Vasiliev, E. 2019, MNRAS, 482, 1525

  52. [60]

    G., Mateo, M., Olszewski, E

    Walker, M. G., Mateo, M., Olszewski, E. W., et al. 2009, ApJ, 704, 1274

  53. [61]

    B., Klypin, A., Khlopov, M

    Zeldovich, Y . B., Klypin, A., Khlopov, M. Y ., & Chechetkin, V . M. 1980, Soviet Journal of Nuclear Physics, 31, 664

  54. [62]

    1996, MNRAS, 278, 488 Article number, page 10 of 10

    Zhao, H. 1996, MNRAS, 278, 488 Article number, page 10 of 10

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