Pith. sign in

REVIEW 3 major objections 4 minor 1 cited by

Weighing the Milky Way's Satellite Galaxies Using Pulsar Accelerations

T0 review · 3 major / 4 minor · reviewed 2026-08-03 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read The paper argues that the lopsided vertical pull measured in pulsar accelerations is produced by the LMC and Sagittarius dwarf, and that its amplitude scales with their masses.

desk verdict First satellite masses from direct pulsar accelerations: a credible proof-of-concept whose error bars live inside one fixed host model. read the letter →

arxiv 2512.10883 v2 pith:ZN75YQ5E submitted 2025-12-11 astro-ph.GA

Thomas Donlon II , Sukanya Chakrabarti , Jason A. S. Hunt This is my paper · ORCID
classification astro-ph.GA
keywords pulsartimingmillisecondpulsarsverticalaccelerationasymmetryLargeMagellanicCloudSagittariusdwarfsatellitegalaxymassesMilkyWaydynamicsN-bodysimulations
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 tries to prove that the observed up-down asymmetry in the accelerations of millisecond pulsars near the Sun is caused by the two most massive Milky Way satellites, the Large Magellanic Cloud and the Sagittarius dwarf, and that the size of the asymmetry records their masses. Using direct, instantaneous pulsar accelerations rather than inferred stellar kinematics, the authors run simulations with different satellite masses and match the predicted asymmetry to the observed one. Their best fit gives an initial total mass of about 2.0×10^11 solar masses for the LMC and 4.4×10^9 solar masses for Sagittarius, corresponding to present-day enclosed masses of 4.1×10^10 and 3.5×10^8 solar masses within 16.6 kpc and 5 kpc, respectively. If correct, this provides a new way to weigh dwarf galaxies that is fully independent of stellar kinematic data for the first time.

What carries the argument

The load-bearing observable is the vertical acceleration asymmetry Δa(z) = a_los,z(+z) − a_los,z(−z): the difference in line-of-sight accelerations measured at equal heights above and below the Galactic midplane. In an equilibrium disk this difference is zero. The machinery producing it is the combination of satellite-induced disk waves and a large-scale offset between the center of mass of the dark halo and that of the baryonic disk. The paper isolates the mass dependence of this asymmetry by running a grid of self-consistent N-body simulations in which the two satellites' masses and scale radii are varied while their present-day positions and velocities are held fixed, then comparing the s

What would settle it

Rerun the best-fit satellite configuration in a host with a more massive or differently shaped dark halo; if the vertical acceleration asymmetry at the Sun changes by more than the quoted 1σ uncertainty, the inferred satellite masses are conditioned on the host model rather than determined by the data. The observational counterpart would be a larger, higher-precision pulsar sample showing whether the asymmetry grows with height exactly as the best-fit simulation predicts.

Watch

Extended reading notes

Core claim

The paper's central claim is that the vertical acceleration asymmetry in pulsar data—accelerations toward the disk midplane are stronger just above the plane than just below it—is a gravitational signature of the Large Magellanic Cloud and the Sagittarius dwarf spheroidal. As those satellites orbit the Milky Way, they launch waves in the disk and displace the dark matter halo's center of mass from the baryonic disk's center of mass. Simulations with varying satellite masses show that the amplitude and shape of this asymmetry at the Sun scale with satellite mass, and a best-fit simulation reproduces the pulsar-measured asymmetry within about 1σ. The implied initial total masses are (2.0±0.5)×

Load-bearing premise

The inference assumes the simulated host Milky Way—halo mass 7.3×10^11 solar masses within 200 kpc and total about 8×10^11 solar masses—responds to the satellites the way the real Galaxy does; if the actual Milky Way is more massive or different in shape, the same satellite masses would not produce the same asymmetry, so the inferred masses could lie outside the quoted errors.

Editorial extensions

If this is right

  • Direct pulsar accelerations can serve as a mass probe for Milky Way satellites, independent of Jeans modeling, stream fitting, or other stellar kinematic techniques.
  • The LMC mass inferred here—about 4.1×10^10 solar masses enclosed within 16.6 kpc today—is consistent with previous estimates, suggesting the method works for the dominant satellite.
  • The method is primarily sensitive to the LMC; the Sagittarius mass is constrained only to about 1σ because its multiple disk passages make the asymmetry a non-monotonic function of its mass.
  • As pulsar timing baselines lengthen and more pulsars with measured parallaxes are added, the same comparison should sharpen both satellite mass estimates without any new stellar kinematic input.

Reading between the lines

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

  • Because the paper fixes the Milky Way halo at a total mass near 8×10^11 solar masses, a natural testable extension is to repeat the simulation grid with heavier or triaxial halos; if the inferred LMC and Sagittarius masses shift by more than the quoted errors, the host model is the dominant source of systematic uncertainty.
  • A discrepancy between the pulsar-derived LMC mass and stream-based masses could be used to separate the halo-wake contribution from direct disk forcing, since those two mechanisms respond differently to host halo properties.
  • The best-fit simulation predicts a specific relationship between the vertical acceleration asymmetry across the disk and the disk warp; future acceleration measurements away from the Solar neighborhood could test whether the same satellite configuration explains both features simultaneously.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper presents a proof-of-concept method for inferring the total masses of the Milky Way's two most prominent satellites, the LMC and Sgr dSph, using direct line-of-sight accelerations of 53 millisecond pulsars rather than stellar kinematics. The authors run a grid of self-consistent N-body simulations with a fixed MW host and varying initial masses and scale radii for the two satellites, measure the resulting vertical acceleration asymmetry at the Sun, and compare it to the observed pulsar asymmetry. The best-fit simulation yields initial (3 Gyr ago) total masses of 2.0±0.5×10^11 M_sun for the LMC and 4.4±3.1×10^9 M_sun for Sgr, corresponding to present-day enclosed masses of 4.1±1.0×10^10 M_sun within 16.6 kpc and 3.5±2.4×10^8 M_sun within 5 kpc, respectively. The authors argue that these results are consistent with previous determinations and demonstrate a new, independent observational route to satellite masses.

Significance. If the result is robust, this is a genuinely new tool: direct acceleration measurements from pulsar timing would provide the first satellite-mass constraints independent of stellar kinematics, and the method could improve as pulsar timing baselines grow. The paper is strengthened by the public availability of the pulsar acceleration catalog, the use of live N-body simulations that reproduce the observed LMC/Sgr configuration, and an explicit comparison to a broad set of literature mass estimates. The authors also state several caveats about the fixed host galaxy and the coarse simulation grid. However, the quoted uncertainties are conditional on a single MW host model and on a sparse likelihood evaluation, so the central quantitative claim—that the mass constraints are 'competitive with kinematic methods'—is not yet fully supported. The concept is promising and worth publishing after the identified robustness issues are addressed.

major comments (3)
  1. [§4.2, Eqs. (3)–(5)] The inference is performed for a single fixed MW host model with total mass ~8×10^11 M_sun, which the authors themselves note is on the low side of estimates. The acceleration asymmetry at the Sun arises from the combined response of the disk, halo, and satellites; changing the host mass or shape alters dynamical friction, the halo-disk reflex offset, and the phase of the disk response, and can plausibly shift the best-fit satellite masses beyond the quoted 1σ errors. The Cramér-Rao covariance in Eqs. (3)–(5) is computed from the Hessian at this one host realization and does not propagate host-model uncertainty. A concrete test—e.g., re-fitting with a heavier MW halo (say 10^12 M_sun) or varying halo concentration/triaxiality—is needed before the claim of 'competitive with kinematic methods' is justified.
  2. [§4.2] The reported 1σ uncertainties are derived from finite-difference Hessian estimates on a half-step grid centered on the best fit. The authors explicitly state that the grid is coarse, that the uncertainties 'should be treated as estimates', and that the best fit may be a local maximum. Given the nonlinear and non-monotonic behavior documented in §4.4 (especially for Sgr), a sparse-grid Hessian is not a reliable covariance estimator. A denser likelihood sampling or a Bayesian exploration is required to support the abstract's error bars. This does not invalidate the proof-of-concept, but the formal uncertainties as quoted are not yet load-bearing.
  3. [§4.4] The asymmetry does not increase monotonically with satellite mass, and the LMC and Sgr perturbations can add or partially cancel. The best-fit pair is selected from a coarse 3×3 grid plus a half-step refinement; no evidence is presented that this is a global maximum rather than a local one. The text acknowledges this possibility, but the conclusion and abstract still present the inferred masses with formal error bars. To make the central claim robust, the authors should either add a wider/denser search or temper the abstract's language to make the proof-of-concept status explicit.
minor comments (4)
  1. [Table 1] The LMC 'Heavy' row lists M_Tot = 12.0 in units of 10^11 M_sun, which is inconsistent with the best-fit total mass of 2.0×10^11 M_sun quoted in §4.1 and with the 'Heavy-Plus' value of 2.25. This appears to be a typo: '12.0' should likely read '2.0'.
  2. [Eq. (3)] The expression for L is unclear as typeset: the integration variable z' appears both as the integration variable and as the upper limit, and the leading '1R' is garbled. Please rewrite with a fixed upper limit (e.g., z_max = 1 kpc) and a single integral, so readers can verify the χ²-like statistic.
  3. [§4.4] The sentence 'we are also able to constrain the mass of the Sgr dwarf to within better than 1 sigma' is misleading given that the relative uncertainty is about 70% (σ_M/M ≈ 3.1/4.4). Consider rephrasing to 'within about 1σ' or 'to order unity'.
  4. [§3.2] The iterative orbit-correction procedure uses a frozen-snapshot potential, and the authors note that final positions agree between low- and medium-resolution runs. It would help to state explicitly whether the orbital phase difference between the low- and medium-resolution runs (e.g., the small offset from exactly 3.0 Gyr) affects the acceleration asymmetry at the level of the quoted errors.

Circularity Check

0 steps flagged · score 2.0 of 10

Forward N-body grid fitted to measured pulsar asymmetry; no equation reduces the inference to its inputs; only same-group data and fixed-host conditioning produce minor caveats.

full rationale

The derivation chain is: observed pulsar line-of-sight accelerations (Eqs. 1-2, catalog from Donlon et al. 2025a) -> vertical asymmetry Delta-a(z) = a(+z) - a(-z) -> self-consistent N-body suite with varied LMC/Sgr masses (Section 3.1, Table 1) -> likelihood L (Eq. 3) -> Hessian/Cramer-Rao uncertainties (Eqs. 4-5) -> best-fit masses. The fitted parameter (satellite mass) is not the same quantity as the data being compared: the observed asymmetry is inherited from pulsar timing and the simulated asymmetry is produced by forward dynamics with explicit initial satellite masses. No equation sets a fitted parameter equal to the data by construction, no claimed prediction is just a renamed fit, and no author-supplied uniqueness theorem or ansatz is invoked to force the result. The main caveats—one fixed MW host model with total mass ~8e11 Msun noted as on the low side (Section 3.1), coarse grid and possible local maximum (Section 4.2)—are model/systematic uncertainties, not circularity. The comparison to independent literature mass determinations (Section 4.3, Table 2, Figure 4) is an external benchmark. The same-group citations (Chakrabarti et al. 2021; Donlon et al. 2024, 2025a) provide the empirical acceleration catalog and prior interpretation, but the current inference is tested with new simulations and is not reduced to those citations. Thus no significant circularity is identified; score 2 reflects only the minor self-citation conditioning, not a definitional or fitted-input circularity.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The central inference does not introduce new physical entities; it relies on data products from the authors' own prior papers (pulsar catalog, asymmetry measurement) and on a fixed, unvaried host galaxy model. The only fitted parameters are the two satellite masses (with their tied scale radii).

free parameters (5)
  • LMC initial total mass = 2.0×10^11 M_sun (best-fit grid point)
    Main fitted parameter; grid values 1.0, 1.5, 1.75, 2.0, 2.25 ×10^11 M_sun (Table 1).
  • Sgr initial total mass = 4.4×10^9 M_sun (best-fit grid point; M_*=2.3e8 + M_DM=4.19e9)
    Second fitted parameter; grid values ~2.2–8.8×10^9 M_sun (Table 1).
  • LMC scale radius = 12.9 kpc (Heavy model)
    Scale radius is tied one-to-one to the mass model (Table 1), so it is not independently constrained.
  • Sgr stellar/DM scale radii = 1.0 kpc / 8.0 kpc (Medium model)
    Tied to mass model (Table 1); jointly varied with mass.
  • Acceleration noise term (MSP surface-B scatter) = from Donlon et al. (2025a) appendix
    Added to pulsar acceleration uncertainties; sets sigma in the likelihood and therefore affects the reported error bars.
assumptions (4)
  • domain assumption Host galaxy model (bulge+disk+halo) from Vasiliev et al. (2021)/Stelea et al. (2024) with reduced disk velocity dispersion is an adequate representation of the MW
    Section 3.1; the mapping from satellite mass to vertical asymmetry depends on the host's response; host mass is not varied.
  • domain assumption The observed pulsar vertical acceleration asymmetry is dominated by the LMC and Sgr; other satellites and disequilibrium processes contribute negligibly
    Section 1 and 4.6; triaxial halo models are checked and found subdominant, but no general scan of other processes is made.
  • domain assumption The pulsar acceleration catalog and the asymmetry profile from Donlon et al. (2025a) are correct and adequately deprojected to vertical accelerations
    Section 2; this paper uses the catalog and the previously derived asymmetry without re-deriving them.
  • domain assumption Dynamical friction is small enough to be corrected by iterating the satellite start time by <100 Myr in a frozen potential, and low-resolution orbits match medium-resolution orbits
    Section 3.2; the linear time-shift correction is verified only implicitly against low-res runs.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Weighing the Milky Way's Satellite Galaxies Using Pulsar Accelerations." pith.science (2026). https://pith.science/paper/ZN75YQ5E

@misc{pith2026251210883,
  author       = {Pith},
  title        = {Pith review of: Weighing the Milky Way's Satellite Galaxies Using Pulsar Accelerations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ZN75YQ5E}},
  note         = {Machine review of arXiv:2512.10883}
}
abstract

The properties of dwarf galaxies orbiting the Milky Way (MW) are useful for testing models of the formation of our Galaxy, and by extension various theories of cosmology. Recent efforts to measure the masses of the MW's satellite dwarf galaxies have relied on the motions and positions of stars in the MW's disk and halo, which are perturbed by the passage of satellite galaxies. As there are many known processes in our Galaxy that lead to observed disequilibrium in stars, these kinematic methods have been limited by the inherent difficulty in identifying only the perturbations due to particular satellite galaxies. We present a novel method for determining the masses of two MW satellite galaxies -- the Large Magellanic Cloud (LMC) and the Sagittarius Dwarf Spheroidal Galaxy (Sgr dSph) -- using only direct, instantaneous acceleration data derived from extremely precise timing of millisecond pulsars near the Sun. As the LMC and Sgr dSph orbit the MW, they cause wave-like distortions in the structure of the disk plus a large-scale offset in the centers of mass of the dark matter halo and the baryonic disk. These two effects lead to asymmetric accelerations above and below the disk midplane near the Sun, which is observed in the pulsar acceleration data. Notably, the amplitude of this asymmetry is shown to depend on the masses of the orbiting satellites. We analyze a grid of simulations with varying masses of each satellite. We find the total (dark + baryon) mass enclosed within the tidal radius at the present day for the LMC to be 4.1 $\pm$ 1.0 $\times$ 10$^{10}$ M$_\odot$ within a radius of 16.6 kpc, and for Sgr to be 3.5 $\pm$ 2.4 $\times$ 10$^8$ M$_\odot$ within a radius of 5 kpc. These results are generally consistent and competitive with previous determinations of the masses of these objects, but entirely independent of any stellar kinematic data for the first time.

Figures

Figures reproduced from arXiv: 2512.10883 by the authors.

Figure 1
Figure 1. Panel (a): Simulation of the Milky Way, the LMC and the Sgr dwarf galaxy/tidal stream. The density of the dwarf galaxies and their stripped material have been enhanced compared to the host galaxy to make them more visible. The locations and velocities of the orbiting satellites match their observed present-day locations. Panel (b): The locations of the pulsar data compared to the Sun, plotted on top of the simulated… view at source ↗
Figure 2
Figure 2. The simulated and observed acceleration asymmetry. Panel (a) shows the vertical component of the line-of-sight acceleration (alos,z) for the best-fit simulation above and below the Solar position. The acceleration below the midplane has been mirrored to positive z for easier comparison (dashed lines). This acceleration is shown at the beginning of the simulation (red), where the profile is identical above and below … view at source ↗
Figure 3
Figure 3. The vertical acceleration asymmetry at the location of the Sun for simulations with different masses of the LMC and Sgr dwarfs. Each column corresponds to a different mass of the LMC, and each row corresponds to a different mass of the Sgr dSph (see [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Mass profiles as a function of radius for the best-fit satellite models. Also shown are various literature values for the masses; bound and/or total masses are shown as horizontal lines, and masses enclosed within some radius are shown as points with error bars. Our de…
Figure 5
Figure 5. Figure 5: The vertical acceleration asymmetry across a face-on projection of the disk for simulations with different masses of the LMC and Sgr dwarfs. Columns and rows are the same as in [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: The vertical acceleration asymmetry across a face-on projection of the disk for simulations with different combinations of the LMC and Sgr dwarfs. The top row shows simulations with only the LMC, the middle row shows simulations with only Sgr, and the bottom row shows …
Figure 7
Figure 7. Figure 7: Vertical disk structure in the best-fit simulation. All panels show a face-on projection of the disk, and the location of the Sun is shown as a golden star. Panel (a) shows the mean vertical acceleration across the disk. Panel (b) shows the vertical acceleration asymme…
Figure 8
Figure 8. Figure 8: The observed vertical acceleration asymmetry (dashed black line, 1 and 2σ uncertainty regions shown as the gray bands) and the prediction for the acceleration asym￾metry produced by two different (tilted) triaxial halo models by Law & Majewski (2010) and Han et al. (20…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Reconstructing Galactic Gravitational Potentials from Stellar Kinematics with Physics-Informed Neural Networks

    astro-ph.GA 2026-06 unverdicted novelty 6.0 of 10

    A PINN approach learns galactic gravitational potentials from acceleration data, achieving sub-percent errors on simulations while outperforming analytic models and retaining interpretability via structured priors.

Reference graph

Works this paper leans on

83 extracted references · 6 canonical work pages · cited by 1 Pith paper

  1. [1]

    Alves, D. R. 2004, NewAR, 48, 659, doi: 10.1016/j.newar.2004.03.001

    doi:10.1016/j.newar.2004.03.001 2004

  2. [2]

    2018, Nature, 561, 360, doi: 10.1038/s41586-018-0510-7

    Antoja, T., Helmi, A., Romero-G´ omez, M., et al. 2018, Nature, 561, 360, doi: 10.1038/s41586-018-0510-7

    doi:10.1038/s41586-018-0510-7 2018

  3. [3]

    M., & Dodelson, S

    Banik, N., Widrow, L. M., & Dodelson, S. 2017, MNRAS, 464, 3775, doi: 10.1093/mnras/stw2603

    doi:10.1093/mnras/stw2603 2017

  4. [4]

    2023, ApJ, 958, 44, doi: 10.3847/1538-4357/acea79

    Baptista, J., Sanderson, R., Huber, D., et al. 2023, ApJ, 958, 44, doi: 10.3847/1538-4357/acea79

    work page doi:10.3847/1538-4357/acea79 2023

  5. [5]

    2019, MNRAS, 482, 1417, doi: 10.1093/mnras/sty2813 —

    Bennett, M., & Bovy, J. 2019, MNRAS, 482, 1417, doi: 10.1093/mnras/sty2813 —. 2021, MNRAS, 503, 376, doi: 10.1093/mnras/stab524

    doi:10.1093/mnras/sty2813 2019

  6. [6]

    Bennett, M., Bovy, J., & Hunt, J. A. S. 2022, ApJ, 927, 131, doi: 10.3847/1538-4357/ac5021

    doi:10.3847/1538-4357/ac5021 2022

  7. [7]

    2007, ApJ, 668, 949, doi: 10.1086/521385 —

    Besla, G., Kallivayalil, N., Hernquist, L., et al. 2007, ApJ, 668, 949, doi: 10.1086/521385 —. 2012, MNRAS, 421, 2109, doi: 10.1111/j.1365-2966.2012.20466.x 15

    arXiv 2007

  8. [8]

    2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441

    Bland-Hawthorn, J., & Gerhard, O. 2016, ARA&A, 54, 529, doi: 10.1146/annurev-astro-081915-023441

    doi:10.1146/annurev-astro-081915-023441 2016

Show all 83 references
  1. [9]

    2019, MNRAS, 486, 1167, doi: 10.1093/mnras/stz217

    Bland-Hawthorn, J., Sharma, S., Tepper-Garcia, T., et al. 2019, MNRAS, 486, 1167, doi: 10.1093/mnras/stz217

    2019 doi

  2. [10]

    V., & Baykova, A

    Bobylev, V. V., & Baykova, A. T. 2023, Astronomy Reports, 67, 812, doi: 10.1134/S1063772923080024

    2023 doi

  3. [11]

    M., Cautun, M., Deason, A

    Callingham, T. M., Cautun, M., Deason, A. J., et al. 2019, MNRAS, 484, 5453, doi: 10.1093/mnras/stz365

    2019 doi

  4. [12]

    2009, MNRAS, 399, L118, doi: 10.1111/j.1745-3933.2009.00735.x

    Chakrabarti, S., & Blitz, L. 2009, MNRAS, 399, L118, doi: 10.1111/j.1745-3933.2009.00735.x

    2009

  5. [13]

    Quillen, A. C. 2021, ApJL, 907, L26, doi: 10.3847/2041-8213/abd635

    2021 doi

  6. [14]

    2025, arXiv e-prints, arXiv:2507.16932, doi: 10.48550/arXiv.2507.16932

    Chakrabarti, S., Chang, P., Profumo, S., & Craig, P. 2025, arXiv e-prints, arXiv:2507.16932, doi: 10.48550/arXiv.2507.16932

    2025 doi

  7. [15]

    J., Wright, J., et al

    Chakrabarti, S., Stevens, D. J., Wright, J., et al. 2022, ApJL, 928, L17, doi: 10.3847/2041-8213/ac5c43

    2022 doi

  8. [16]

    2020, ApJL, 902, L28, doi: 10.3847/2041-8213/abb9b5

    Chakrabarti, S., Wright, J., Chang, P., et al. 2020, ApJL, 902, L28, doi: 10.3847/2041-8213/abb9b5

    2020 doi

  9. [17]

    P., Conroy, C., et al

    Chandra, V., Naidu, R. P., Conroy, C., et al. 2025, ApJ, 988, 156, doi: 10.3847/1538-4357/addab6

    2025 doi

  10. [18]

    1943, ApJ, 97, 255, doi: 10.1086/144517

    Chandrasekhar, S. 1943, ApJ, 97, 255, doi: 10.1086/144517

    1943 doi

  11. [19]

    R., & Arras, P

    Cheng, X., Anguiano, B., Majewski, S. R., & Arras, P. 2024, MNRAS, 527, 959, doi: 10.1093/mnras/stad3013

    2024 doi

  12. [20]

    E., & Nikakhtar, F

    Craig, P., Chakrabarti, S., Sanderson, R. E., & Nikakhtar, F. 2023, ApJL, 945, L32, doi: 10.3847/2041-8213/acba15

    2023 doi

  13. [21]

    A., Chakrabarti, S., Baum, S., & Lewis, B

    Craig, P. A., Chakrabarti, S., Baum, S., & Lewis, B. T. 2022, MNRAS, 517, 1737, doi: 10.1093/mnras/stac2308

    2022 doi

  14. [22]

    T., Fonseca, E., Ransom, S

    Cromartie, H. T., Fonseca, E., Ransom, S. M., et al. 2020, Nature Astronomy, 4, 72, doi: 10.1038/s41550-019-0880-2

    2020 doi

  15. [23]

    2025, arXiv e-prints, arXiv:2511.02031, doi: 10.48550/arXiv.2511.02031

    Darragh-Ford, E., Garavito-Camargo, N., Arora, A., et al. 2025, arXiv e-prints, arXiv:2511.02031, doi: 10.48550/arXiv.2511.02031

    2025 doi

  16. [24]

    1986, ApJ, 303, 39, doi: 10.1086/164050

    Dekel, A., & Silk, J. 1986, ApJ, 303, 39, doi: 10.1086/164050

    1986 doi

  17. [25]

    Doliva-Dolinsky, A., Collins, M. L. M., & Martin, N. F. 2025, arXiv e-prints, arXiv:2502.06948, doi: 10.48550/arXiv.2502.06948 D’Onghia, E., Madau, P., Vera-Ciro, C., Quillen, A., &

    2025 doi arXiv

  18. [26]

    2016, ApJ, 823, 4, doi: 10.3847/0004-637X/823/1/4

    Hernquist, L. 2016, ApJ, 823, 4, doi: 10.3847/0004-637X/823/1/4

    2016 doi

  19. [27]

    2025a, PhRvD, 111, 103036, doi: 10.1103/PhysRevD.111.103036

    Donlon, T., Chakrabarti, S., Vanderwaal, S., et al. 2025a, PhRvD, 111, 103036, doi: 10.1103/PhysRevD.111.103036

    doi

  20. [28]

    M., et al

    Donlon, T., Chakrabarti, S., Widrow, L. M., et al. 2024, PhRvD, 110, 023026, doi: 10.1103/PhysRevD.110.023026

    2024 doi

  21. [29]

    T., et al

    Donlon, T., Chakrabarti, S., Lam, M. T., et al. 2025b, ApJ, 983, 62, doi: 10.3847/1538-4357/adbf90

    doi

  22. [30]

    J., & Elmegreen, B

    Edelsohn, D. J., & Elmegreen, B. G. 1997, MNRAS, 287, 947, doi: 10.1093/mnras/287.4.947

    1997 doi

  23. [31]

    Erkal, D., & Belokurov, V. A. 2020, MNRAS, 495, 2554, doi: 10.1093/mnras/staa1238

    2020 doi

  24. [32]

    Erkal, D., Belokurov, V., Laporte, C. F. P., et al. 2019, MNRAS, 487, 2685, doi: 10.1093/mnras/stz1371

    2019 doi

  25. [33]

    A., van der Marel, R

    Fardal, M. A., van der Marel, R. P., Law, D. R., et al. 2019, MNRAS, 483, 4724, doi: 10.1093/mnras/sty3428

    2019 doi

  26. [34]

    S., White, S

    Frenk, C. S., White, S. D. M., Davis, M., & Efstathiou, G. 1988, ApJ, 327, 507, doi: 10.1086/166213

    1988 doi

  27. [35]

    Garavito-Camargo, N., Besla, G., Laporte, C. F. P., et al. 2021, ApJ, 919, 109, doi: 10.3847/1538-4357/ac0b44 Garc ´ ıa-Ruiz, I., Kuijken, K., & Dubinski, J. 2002, MNRAS, 337, 459, doi: 10.1046/j.1365-8711.2002.05923.x

    2021

  28. [36]

    Gibbons, S. L. J., Belokurov, V., & Evans, N. W. 2017, MNRAS, 464, 794, doi: 10.1093/mnras/stw2328

    2017 doi

  29. [37]

    2022, ApJ, 936, 103, doi: 10.3847/1538-4357/ac86cd

    Guo, R., Shen, J., Li, Z.-Y., Liu, C., & Mao, S. 2022, ApJ, 936, 103, doi: 10.3847/1538-4357/ac86cd

    2022 doi

  30. [38]

    2019, ApJL, 879, L15, doi: 10.3847/2041-8213/ab25f3

    Hernquist, L. 2019, ApJL, 879, L15, doi: 10.3847/2041-8213/ab25f3

    2019 doi

  31. [39]

    J., Conroy, C., & Hernquist, L

    Han, J. J., Conroy, C., & Hernquist, L. 2023a, Nature Astronomy, 7, 1481, doi: 10.1038/s41550-023-02076-9

    doi

  32. [40]

    J., Semenov, V., Conroy, C., & Hernquist, L

    Han, J. J., Semenov, V., Conroy, C., & Hernquist, L. 2023b, ApJL, 957, L24, doi: 10.3847/2041-8213/ad0641

    doi

  33. [41]

    J., Conroy, C., Johnson, B

    Han, J. J., Conroy, C., Johnson, B. D., et al. 2022a, AJ, 164, 249, doi: 10.3847/1538-3881/ac97e9

    doi

  34. [42]

    J., Naidu, R

    Han, J. J., Naidu, R. P., Conroy, C., et al. 2022b, ApJ, 934, 14, doi: 10.3847/1538-4357/ac795f

    doi

  35. [43]

    2020, ARA&A, 58, 205, doi: 10.1146/annurev-astro-032620-021917

    Helmi, A. 2020, ARA&A, 58, 205, doi: 10.1146/annurev-astro-032620-021917

    2020 doi

  36. [44]

    Hunt, J. A. S., Stelea, I. A., Johnston, K. V., et al. 2021, MNRAS, 508, 1459, doi: 10.1093/mnras/stab2580

    2021 doi

  37. [45]

    Hunt, J. A. S., & Vasiliev, E. 2025, NewAR, 100, 101721, doi: 10.1016/j.newar.2024.101721

    2025

  38. [46]

    A., Gilmore, G., & Irwin, M

    Ibata, R. A., Gilmore, G., & Irwin, M. J. 1994, Nature, 370, 194, doi: 10.1038/370194a0

    1994 doi

  39. [47]

    2016, MNRAS, 461, 2212, doi: 10.1093/mnras/stw1343

    Jethwa, P., Erkal, D., & Belokurov, V. 2016, MNRAS, 461, 2212, doi: 10.1093/mnras/stw1343

    2016 doi

  40. [48]

    N., Cohen, J

    Kirby, E. N., Cohen, J. G., Guhathakurta, P., et al. 2013, ApJ, 779, 102, doi: 10.1088/0004-637X/779/2/102

    2013 doi

  41. [49]

    E., Erkal, D., Li, T

    Koposov, S. E., Erkal, D., Li, T. S., et al. 2023, MNRAS, 521, 4936, doi: 10.1093/mnras/stad551

    2023 doi

  42. [50]

    V., Gnedin, O

    Kravtsov, A. V., Gnedin, O. Y., & Klypin, A. A. 2004, ApJ, 609, 482, doi: 10.1086/421322

    2004 doi

  43. [51]

    1991, ApJL, 367, L9, doi: 10.1086/185920

    Kuijken, K., & Gilmore, G. 1991, ApJL, 367, L9, doi: 10.1086/185920

    1991 doi

  44. [52]

    Laporte, C. F. P., G´ omez, F. A., Besla, G., Johnston, K. V., & Garavito-Camargo, N. 2018, MNRAS, 473, 1218, doi: 10.1093/mnras/stx2146 16

    2018 doi

  45. [53]

    Laporte, C. F. P., Minchev, I., Johnston, K. V., & G´ omez, F. A. 2019, MNRAS, 485, 3134, doi: 10.1093/mnras/stz583

    2019 doi

  46. [54]

    R., Johnston, K

    Law, D. R., Johnston, K. V., & Majewski, S. R. 2005, ApJ, 619, 807, doi: 10.1086/426779

    2005 doi

  47. [55]

    R., & Majewski, S

    Law, D. R., & Majewski, S. R. 2010, ApJ, 714, 229, doi: 10.1088/0004-637X/714/1/229 Lokas, E. L. 2019, A&A, 629, A52, doi: 10.1051/0004-6361/201936056 Lokas, E. L., Kazantzidis, S., Majewski, S. R., et al. 2010, ApJ, 725, 1516, doi: 10.1088/0004-637X/725/2/1516

    2010 doi

  48. [56]

    F., Parravano, A., & Hollenbach, D

    McKee, C. F., Parravano, A., & Hollenbach, D. J. 2015, ApJ, 814, 13, doi: 10.1088/0004-637X/814/1/13

    2015 doi

  49. [57]

    Moran, A., Mingarelli, C. M. F., Van Tilburg, K., & Good, D. 2024, PhRvD, 109, 123015, doi: 10.1103/PhysRevD.109.123015

    2024 doi

  50. [58]

    2017, A&A, 605, A46, doi: 10.1051/0004-6361/201730707

    Mucciarelli, A., Bellazzini, M., Ibata, R., et al. 2017, A&A, 605, A46, doi: 10.1051/0004-6361/201730707

    2017 doi

  51. [59]

    J., Yanny, B., Rockosi, C., et al

    Newberg, H. J., Yanny, B., Rockosi, C., et al. 2002, ApJ, 569, 245, doi: 10.1086/338983

    2002 doi

  52. [60]

    Oort, J. H. 1932, BAN, 6, 249 Pe˜ narrubia, J., G´ omez, F. A., Besla, G., Erkal, D., & Ma, Y.-Z. 2016, MNRAS, 456, L54, doi: 10.1093/mnrasl/slv160

    1932 doi

  53. [61]

    Perera, B. B. P., DeCesar, M. E., Demorest, P. B., et al. 2019, MNRAS, 490, 4666, doi: 10.1093/mnras/stz2857

    2019 doi

  54. [62]

    S., & Pe˜ narrubia, J

    Petersen, M. S., & Pe˜ narrubia, J. 2021, Nature Astronomy, 5, 251, doi: 10.1038/s41550-020-01254-3

    2021 doi

  55. [63]

    2025, A&A, 699, A199, doi: 10.1051/0004-6361/202451668

    Poggio, E., Khanna, S., Drimmel, R., et al. 2025, A&A, 699, A199, doi: 10.1051/0004-6361/202451668

    2025 doi

  56. [64]

    2011, Nature, 477, 301, doi: 10.1038/nature10417

    Chakrabarti, S. 2011, Nature, 477, 301, doi: 10.1038/nature10417

    2011 doi

  57. [65]

    2009, MNRAS, 397, 1599, doi: 10.1111/j.1365-2966.2009.15054.x

    Haywood, M. 2009, MNRAS, 397, 1599, doi: 10.1111/j.1365-2966.2009.15054.x

    2009

  58. [66]

    D., Frenk, C

    Schneider, M. D., Frenk, C. S., & Cole, S. 2012, JCAP, 2012, 030, doi: 10.1088/1475-7516/2012/05/030

    2012 doi

  59. [67]

    2021, ApJ, 923, 149, doi: 10.3847/1538-4357/ac2e93

    Shipp, N., Erkal, D., Drlica-Wagner, A., et al. 2021, ApJ, 923, 149, doi: 10.3847/1538-4357/ac2e93

    2021 doi

  60. [68]

    Shklovskii, I. S. 1970, Soviet Ast., 13, 562

    1970

  61. [69]

    M., Skowron, J., Mr´ oz, P., et al

    Skowron, D. M., Skowron, J., Mr´ oz, P., et al. 2019, Science, 365, 478, doi: 10.1126/science.aau3181

    2019 doi

  62. [70]

    S., & Dav´ e, R

    Somerville, R. S., & Dav´ e, R. 2015, ARA&A, 53, 51, doi: 10.1146/annurev-astro-082812-140951

    2015 doi

  63. [71]

    2021, MNRAS, 506, 2871, doi: 10.1093/mnras/stab1855

    Springel, V., Pakmor, R., Zier, O., & Reinecke, M. 2021, MNRAS, 506, 2871, doi: 10.1093/mnras/stab1855

    2021 doi

  64. [72]

    A., Hunt, J

    Stelea, I. A., Hunt, J. A. S., & Johnston, K. V. 2024, ApJ, 977, 252, doi: 10.3847/1538-4357/ad901b

    2024 doi

  65. [73]

    E., Bullock, J

    Strigari, L. E., Bullock, J. S., Kaplinghat, M., et al. 2008, Nature, 454, 1096, doi: 10.1038/nature07222 van der Marel, R. P., & Kallivayalil, N. 2014, ApJ, 781, 121, doi: 10.1088/0004-637X/781/2/121

    2008 doi

  66. [74]

    2018, arXiv e-prints, arXiv:1802.08255, doi: 10.48550/arXiv.1802.08255

    Vasiliev, E. 2018, arXiv e-prints, arXiv:1802.08255, doi: 10.48550/arXiv.1802.08255

    2018 doi arXiv

  67. [75]

    2020, MNRAS, 497, 4162, doi: 10.1093/mnras/staa2114

    Vasiliev, E., & Belokurov, V. 2020, MNRAS, 497, 4162, doi: 10.1093/mnras/staa2114

    2020 doi

  68. [76]

    2021, MNRAS, 501, 2279, doi: 10.1093/mnras/staa3673

    Vasiliev, E., Belokurov, V., & Erkal, D. 2021, MNRAS, 501, 2279, doi: 10.1093/mnras/staa3673

    2021 doi

  69. [77]

    F., Mackey, D., & Ibata, R

    Wan, Z., Guglielmo, M., Lewis, G. F., Mackey, D., & Ibata, R. A. 2020, MNRAS, 492, 782, doi: 10.1093/mnras/stz3493

    2020 doi

  70. [78]

    Wang, W., Han, J., Cautun, M., Li, Z., & Ishigaki, M. N. 2020, Science China Physics, Mechanics, and Astronomy, 63, 109801, doi: 10.1007/s11433-019-1541-6

    2020 doi

  71. [79]

    T., Newberg, H

    Warren, H. T., Newberg, H. J., Guffey, A. G., et al. 2025, ApJ, 994, 161, doi: 10.3847/1538-4357/ae0e6d

    2025 doi

  72. [80]

    M., & Huang, Y

    Weisberg, J. M., & Huang, Y. 2016, ApJ, 829, 55, doi: 10.3847/0004-637X/829/1/55

    2016 doi

  73. [81]

    2012, ApJL, 750, L41, doi: 10.1088/2041-8205/750/2/L41

    Chen, H.-Y. 2012, ApJL, 750, L41, doi: 10.1088/2041-8205/750/2/L41

    2012 doi

  74. [82]

    J., Carlin, J

    Xu, Y., Newberg, H. J., Carlin, J. L., et al. 2015, ApJ, 801, 105, doi: 10.1088/0004-637X/801/2/105

    2015 doi

  75. [83]

    2013, ApJ, 777, 91, doi: 10.1088/0004-637X/777/2/91 17 LMC Constraint or Radius (kpc) Mass (10 11 M⊙) Reference Total Mass 1.8 Besla et al

    Yanny, B., & Gardner, S. 2013, ApJ, 777, 91, doi: 10.1088/0004-637X/777/2/91 17 LMC Constraint or Radius (kpc) Mass (10 11 M⊙) Reference Total Mass 1.8 Besla et al. (2012) 8.7 0.17(7) van der Marel & Kallivayalil (2014) Total Mass 2.5(9) Pe˜ narrubia et al. (2016) Total Mass 1...

    2013 doi

Pith tools

Reviewed August 3, 2026 · model on record in the stance chip above.