Cited by 14Stellar, planetary, and galactic studiesGalaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Assessing the robustness of the Galactic rotation curve inferred from the Jeans equations using Gaia DR3 and cosmological simulations

Open access

Abstract

Context. Several authors have recently applied Jeans modelling to Gaia-based datasets to infer the circular velocity curve for the Milky Way. These works have consistently found evidence for a continuous decline in the rotation curve beyond ~15 kpc, which may indicate the existence of a light dark matter (DM) halo. Aims. Using a large sample of Gaia DR3 data, we aim to derive the rotation curve of the Milky Way using the Jeans equations, and to quantify the role of systematic effects, both in the data and those inherent to the Jeans methodology under the assumptions of axisym-metry and time independence. Methods. We used data from the Gaia DR3 radial velocity spectrometer sample, supplemented with distances inferred through Bayesian frameworks, to determine the radial variation of the second moments of the velocity distribution for stars close to the Galactic plane. We used these profiles to determine the rotation curve using the Jeans equations under the assumption of axisym-metry and explored how they vary with azimuth and position above and below the plane of the Galactic disc. We applied the same methodology to an N-body simulation of a Milky Way-like galaxy impacted by a satellite akin the Sagittarius dwarf, and to the Auriga suite of cosmological simulations. Results. The circular velocity curve we infer for the Milky Way is consistent with previous findings out to ~15 kpc, where our statistics are robust. Due to the larger number of stars in our sample, we are able to reveal evidence of disequilibrium and deviations from axisymmetry closer in. For example, we find that the second moment of VR flattens out at R ≳ 12.5 kpc, and that the second moment of Vϕ is different above and below the plane for R ≳ 11 kpc. Our exploration of the simulations indicates that these features are typical of galaxies that have been perturbed by external satellites. From the simulations, we also estimate that the difference between the true circular velocity curve and that inferred from Jeans equations can be as high as 15%, but that it is likely of the order of 10% for the Milky Way. This is higher than the systematic uncertainties associated with the observations or those linked to most modelling assumptions when using the Jeans equations. However, if the density of the tracer population were truncated at large radii instead of being exponential as often assumed, this could lead to the erroneous conclusion of a steeply declining rotation curve. Conclusions. We find that steady-state axisymmetric Jeans modelling becomes less robust at large radii, indicating that particular caution must be exercised when interpreting the rotation curve inferred in those regions. A more careful and sophisticated approach may be necessary for precision measurements of the DM content of our Galaxy.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1051/0004-6361/202450911

Cites

90 of 90 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Koop et al. (2024) find that the difference between the true circular-speed curve and the Jeans-inferred one can reach about 10-15% in Milky Way-like systems, and caution that a radially truncated tracer density can produce a spuriously steep apparent decline at large R even when the underlying rotation curve is essentially flat.

    “A complementary Gaia DR3 Jeans-equation reanalysis by Koop et al. (2024), using both observational data and N -body simulations including a Sagittarius-like perturber, finds that the difference between the true circular-speed curve and the Jeans-inferred one can reach ∼ 10-15% in MW-like systems, and cautions specifically that a radially truncated tracer density can produce a spuriously steep”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 95

  1. Ablimit, I., & Zhao, G. 2017, ApJ, 846, 10 · DOI
  2. Anders, F., Khalatyan, A., Queiroz, A. B. A., et al. 2022, A&A, 658, A91 · DOI
  3. Andrae, R., Rix, H.-W., & Chandra, V. 2023, ApJS, 267, 8 · DOI
  4. Antoja, T., Helmi, A., Romero-Gómez, M., et al. 2018, Natur, 561, 360 · DOI
  5. Antoja, T., Ramos, P., López-Guitart, F., et al. 2022, A&A, 668, A61 · DOI
  6. Antoja, T., Ramos, P., García-Conde, B., et al. 2023, A&A, 673, A115 · DOI
  7. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 · DOI
  8. Bañares-Hernández, A., Castillo, A., Martin Camalich, J., & Iorio, G. 2023, A&A, 676, A63 · DOI
  9. Bailer-Jones, C. A. L. 2023, AJ, 166, 269 · DOI
  10. Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., Demleitner, M., & Andrae, R. 2021, AJ, 161, 147 · DOI
  11. Bland-Hawthorn, J., & Gerhard, O. 2016, ARA&A, 54, 529 · DOI
  12. Bosma, A. 1981, AJ, 86, 1825 · DOI
  13. Bovy, J., Prieto, C. A., Beers, T. C., et al. 2012, ApJ, 759, 131 · DOI
  14. Bovy, J., Rix, H.-W., Schlafly, E. F., et al. 2016, ApJ, 823, 30 · DOI
  15. Breddels, M. A., & Veljanoski, J. 2018, A&A, 618, A13 · DOI
  16. Cabrera-Gadea, M., Mateu, C., Ramos, P., et al. 2024, MNRAS, 528, 4409 · DOI
  17. Callingham, T. M., Cautun, M., Deason, A. J., et al. 2019, MNRAS, 484, 5453 · DOI
  18. Callingham, T. M., Cautun, M., Deason, A. J., et al. 2020, MNRAS, 495, 12 · DOI
  19. Cautun, M., Benítez-Llambay, A., Deason, A. J., et al. 2020, MNRAS, 494, 4291 · DOI
  20. Chabrier, G. 2003, PASP, 115, 763 · DOI
  21. Chrobáková, Ž., López-Corredoira, M., Sylos Labini, F., Wang, H. F., & Nagy, R. 2020, A&A, 642, A95 · DOI
  22. Chrobáková, Ž., Nagy, R., & López-Corredoira, M. 2022, A&A, 664, A58 · DOI
  23. de Blok, W. J. G., Walter, F., Brinks, E., et al. 2008, AJ, 136, 2648 · DOI
  24. Eilers, A.-C., Hogg, D. W., Rix, H.-W., & Ness, M. K. 2019, ApJ, 871, 120 · DOI
  25. El-Badry, K., Wetzel, A. R., Geha, M., et al. 2017, ApJ, 835, 193 · DOI
  26. Gaia Collaboration (Antoja, et al.) 2021a, A&A, 649, A8 · DOI
  27. Gaia Collaboration (Brown, A. G. A., et al.) 2021b, A&A, 649, A1 · DOI
  28. Gaia Collaboration (Drimmel, et al.) 2023a, A&A, 674, A37 · DOI
  29. Gaia Collaboration 2023b, A&A, 674, A1 · DOI
  30. García-Conde, B., Antoja, T., Roca-Fàbrega, S., et al. 2024, A&A, 683, A47 · DOI
  31. Genzel, R., Förster Schreiber, N. M., Übler, H., et al. 2017, Natur, 543, 397 · DOI
  32. Gómez, F. A., Grand, R. J. J., Monachesi, A., et al. 2017, MNRAS, 472, 3722 · DOI
  33. Grand, R. J. J., Gómez, F. A., Marinacci, F., et al. 2017, MNRAS, 467, 179 · DOI
  34. Grand, R. J. J., Helly, J., Fattahi, A., et al. 2018, MNRAS, 481, 1726 · DOI
  35. Gravity Collaboration 2018, A&A, 615, L15 · DOI
  36. Hagen, J. H. J., Helmi, A., de Zeeuw, P. T., & Posti, L. 2019, A&A, 629, A70 · DOI
  37. Haines, T., D'Onghia, E., Famaey, B., Laporte, C., & Hernquist, L. 2019, ApJ, 879, L15 · DOI
  38. Hogg, D. W., Eilers, A.-C., & Rix, H.-W. 2019, AJ, 158, 147 · DOI
  39. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 · DOI
  40. Jiao, Y., Hammer, F., Wang, H., et al. 2023, A&A, 678, A208 · DOI
  41. Jónsson, V. H., & McMillan, P. J. 2024, A&A, 688, A38 · DOI
  42. Jurić, M., Ivezić, Ž., Brooks, A., et al. 2008, ApJ, 673, 864 A50, page 16 of 20 · DOI
  43. Koop, O., et al.: A&A, 692, A50 (2024)
  44. Kafle, P. R., Sharma, S., Robotham, A. S. G., Elahi, P. J., & Driver, S. P. 2018, MNRAS, 475, 4434 · DOI
  45. Kamada, A., Kaplinghat, M., Pace, A. B., & Yu, H.-B. 2017, PhRvL, 119, 111102 · DOI
  46. Kawata, D., Baba, J., Ciucǎ, I., et al. 2018, MNRAS, 479, L108 · DOI
  47. Kluyver, T., Ragan-Kelley, B., Pérez, F., et al. 2016, in Positioning and Power in Academic Publishing: Players, Agents and Agendas, eds. F. Loizides, & B. Scmidt (IOS Press), 87 · DOI
  48. Kretschmer, M., Dekel, A., Freundlich, J., et al. 2021, MNRAS, 503, 5238 · DOI
  49. Laporte, C. F. P., Johnston, K. V., Gómez, F. A., Garavito-Camargo, N., & Besla, G. 2018, MNRAS, 481, 286 · DOI
  50. Laporte, C. F. P., Minchev, I., Johnston, K. V., & Gómez, F. A. 2019, MNRAS, 485, 3134 · DOI
  51. Lelli, F., McGaugh, S. S., & Schombert, J. M. 2016, AJ, 152, 157 · DOI
  52. López-Corredoira, M., Allende Prieto, C., Garzón, F., et al. 2018, A&A, 612, L8 · DOI
  53. Lowing, B., Wang, W., Cooper, A., et al. 2015, MNRAS, 446, 2274 · DOI
  54. Lucy, L. B. 1974, AJ, 79, 745 · DOI
  55. Luri, X., Brown, A. G. A., Sarro, L. M., et al. 2018, A&A, 616, A9 · DOI
  56. Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94 · DOI
  57. Mancera Piña, P. E., Fraternali, F., Oosterloo, T., et al. 2022, MNRAS, 514, 3329 · DOI
  58. Martinsson, T. P. K., Verheijen, M. A. W., Westfall, K. B., et al. 2013, A&A, 557, A130 · DOI
  59. McMillan, P. J. 2017, MNRAS, 465, 76 · DOI
  60. Minniti, D., Saito, R. K., Alonso-García, J., Lucas, P. W., & Hempel, M. 2011, ApJ, 733, L43 · DOI
  61. Mróz, P., Udalski, A., Skowron, D. M., et al. 2019, ApJ, 870, L10 · DOI
  62. Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, ApJ, 462, 563 · DOI
  63. Oman, K. A., & Riley, A. H. 2024, MNRAS, 532, L48 · DOI
  64. Oman, K. A., Navarro, J. F., Fattahi, A., et al. 2015, MNRAS, 452, 3650 · DOI
  65. Ou, X., Eilers, A.-C., Necib, L., & Frebel, A. 2024, MNRAS, 528, 693 · DOI
  66. Petersen, J., & Lelli, F. 2020, A&A, 636, A56 · DOI
  67. Pont, F., Queloz, D., Bratschi, P., & Mayor, M. 1997, A&A, 318, 416 · DOI
  68. Portail, M., Gerhard, O., Wegg, C., & Ness, M. 2017, MNRAS, 465, 1621 · DOI
  69. Ramos, P., Antoja, T., & Figueras, F. 2018, A&A, 619, A72 · DOI
  70. Read, J. I., Iorio, G., Agertz, O., & Fraternali, F. 2016, MNRAS, 462, 3628 · DOI
  71. Recio-Blanco, A., de Laverny, P., Palicio, P. A., et al. 2023, A&A, 674, A29 · DOI
  72. Reid, M. J., & Brunthaler, A. 2004, ApJ, 616, 872 · DOI
  73. Roman-Oliveira, F., Fraternali, F., & Rizzo, F. 2023, MNRAS, 521, 1045 · DOI
  74. Rubin, V. C., Burstein, D., & Thonnard, N. 1980, ApJ, 242, L149 · DOI
  75. Schönrich, R., Binney, J., & Dehnen, W. 2010, MNRAS, 403, 1829 · DOI
  76. Silverwood, H., Sivertsson, S., Read, J., Bertone, G., & Steger, P. 2018, in Astrometry and Astrophysics in the Gaia Sky, 330, eds. A. Recio-Blanco, P. de Laverny, A. G. A. Brown, & T. Prusti, 255 · DOI
  77. Skowron, D. M., Skowron, J., Mróz, P., et al. 2019, Science, 365, 478 · DOI
  78. Sofue, Y. 2020, Galax, 8, 37 · DOI
  79. Sofue, Y., Honma, M., & Omodaka, T. 2009, PASJ, 61, 227 · DOI
  80. Sormani, M. C., Gerhard, O., Portail, M., Vasiliev, E., & Clarke, J. 2022, MNRAS, 514, L1 · DOI
  81. Springel, V., Pakmor, R., Zier, O., & Reinecke, M. 2021, MNRAS, 506, 2871 · DOI
  82. van der Kruit, P. C. & Searle, L. 1981, A&A, 95, 105 · DOI
  83. van der Walt, S., Colbert, S. C., & Varoquaux, G. 2011, Comput. Sci. Eng., 13, 22 · DOI
  84. Vasiliev, E. 2019, MNRAS, 482, 1525 · DOI
  85. Vasiliev, E., Belokurov, V., & Erkal, D. 2021, MNRAS, 501, 2279 · DOI
  86. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261 · DOI
  87. Wang, W., Han, J., Cole, S., et al. 2018, MNRAS, 476, 5669 · DOI
  88. Wang, W., Han, J., Cautun, M., Li, Z., & Ishigaki, M. N. 2020, Sci. China Phys. Mech. Astron., 63, 109801 · DOI
  89. Wang, H.-F., Chrobáková, Ž., López-Corredoira, M., & Sylos Labini, F. 2023, ApJ, 942, 12 · DOI
  90. Wegg, C., Gerhard, O., & Portail, M. 2015, MNRAS, 450, 4050 · DOI
  91. Widrow, L. M., Gardner, S., Yanny, B., Dodelson, S., & Chen, H.-Y. 2012, ApJ, 750, L41 · DOI
  92. Williams, M. E. K., Steinmetz, M., Binney, J., et al. 2013, MNRAS, 436, 101 · DOI
  93. Xue, X.-X., Rix, H.-W., & Zhao, G. 2009, Res. Astron. Astrophys., 9, 1230 · DOI
  94. Zhou, Y., Li, X., Huang, Y., & Zhang, H. 2023, ApJ, 946, 73 · DOI
  95. Zwicky, F. 1933, Helv. Phys. Acta, 6, 110 · DOI

Cited by

Sorted by citations

Authors
Koop, O., Antoja, T., Helmi, A., Callingham, T. M., & Laporte, C. F. P.
Affiliations
  • University of Groningen (NL)
  • Institut de Ciències del Cosmos (ES)
Venue
Astronomy & Astrophysics
Publisher
EDP Sciences
Published
2024-12
Volume
692
Pages
A50
ISSN
  • 0004-6361 (ISSN-L)
  • 1432-0746
OpenAlex
W4403632602
Cited by
14
References
88
Citations by year
2026: 5 · 2025: 7 · 2024: 2
FWCI
2.64
Type
journal article
Language
en
Open access
Locations
  • Astronomy and Astrophysics (publishedVersion, cc-by)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (acceptedVersion, other-oa)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Funders
  • European Space Agency
  • European Commission (CNS2022-135232, 13039/501100011033, 501100011033, PID2021-125451NA-I00)
  • Universitat de Barcelona (CEX2019-000918-M)
  • European Regional Development Fund (MCIN/AEI/10, 13039/501100011033, RYC2018-025968-I, CEX2019-000918-M, 501100011033, MICIU/AEI/10)
  • Agencia Estatal de Investigación (501100011033, RYC2018-025968-I, 13039, CEX2019-000918-M, .13039/501100011033, PID2021-125451NA-I00, AEI/10, CNS2022-135232)
  • Institut de Ciències del Cosmos (CEX2019–000918–M)
  • European Social Fund (501100011033)
Topics
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Stellar, planetary, and galactic studies
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Astrophysical Phenomena and Observations
Keywords
Milky Way rotation curve, Jeans equation, dark matter halos, axial symmetry, velocity dispersion anisotropy, Sagittarius dwarf galaxy, satellite orbit perturbations, Auriga simulations, Gaia DR3, systematic uncertainties, stellar kinematics, Galactic disc

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review