Open Access
Issue
A&A
Volume 701, September 2025
Article Number A136
Number of page(s) 10
Section Galactic structure, stellar clusters and populations
DOI https://doi.org/10.1051/0004-6361/202452736
Published online 09 September 2025
  1. Ablimit, I., Zhao, G., Flynn, C., & Bird, S. A. 2020, ApJ, 895, L12 [Google Scholar]
  2. Amôres, E. B., Robin, A. C., & Reylé, C. 2017, A&A, 602, A67 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Anders, F., Gispert, P., Ratcliffe, B., et al. 2023, A&A, 678, A158 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Ardèvol, J., Monguió, M., Figueras, F., Romero-Gómez, M., & Carrasco, J. M. 2023, A&A, 678, A111 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  6. Bland-Hawthorn, J., & Tepper-García, T. 2021, MNRAS, 504, 3168 [CrossRef] [Google Scholar]
  7. Burke, B. F. 1957, AJ, 62, 90 [Google Scholar]
  8. Cabrera-Gadea, M., Mateu, C., Ramos, P., et al. 2024, MNRAS, 528, 4409 [NASA ADS] [CrossRef] [Google Scholar]
  9. Chen, X., Wang, S., Deng, L., et al. 2019, Nat. Astron., 3, 320 [NASA ADS] [CrossRef] [Google Scholar]
  10. Cheng, X., Anguiano, B., Majewski, S. R., et al. 2020, ApJ, 905, 49 [Google Scholar]
  11. Chequers, M. H., & Widrow, L. M. 2017, MNRAS, 472, 2751 [NASA ADS] [CrossRef] [Google Scholar]
  12. Chequers, M. H., Widrow, L. M., & Darling, K. 2018, MNRAS, 480, 4244 [CrossRef] [Google Scholar]
  13. Chrobáková, Ž., Nagy, R., & López-Corredoira, M. 2020, A&A, 637, A96 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  14. Clementini, G., Ripepi, V., Garofalo, A., et al. 2023, A&A, 674, A18 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Das, P., Huang, Y., Ciuca˘, I., & Fragkoudi, F. 2024, MNRAS, 527, 4505 [Google Scholar]
  16. Dehnen, W., Semczuk, M., & Schönrich, R. 2023, MNRAS, 523, 1556 [NASA ADS] [CrossRef] [Google Scholar]
  17. Gaia Collaboration (Antoja, T., et al.) 2021, A&A, 649, A8 [EDP Sciences] [Google Scholar]
  18. Gaia Collaboration (Drimmel, R., et al.) 2023, A&A, 674, A37 [CrossRef] [EDP Sciences] [Google Scholar]
  19. Garofalo, A., Delgado, H. E., Sarro, L. M., et al. 2022, MNRAS, 513, 788 [NASA ADS] [CrossRef] [Google Scholar]
  20. Girardi, L. 2016, ARA&A, 54, 95 [Google Scholar]
  21. Green, G. M., Schlafly, E., Zucker, C., Speagle, J. S., & Finkbeiner, D. 2019, ApJ, 887, 93 [NASA ADS] [CrossRef] [Google Scholar]
  22. Han, J. J., Conroy, C., & Hernquist, L. 2023, Nat. Astron., 7, 1481 [CrossRef] [Google Scholar]
  23. Hawkins, K. 2023, MNRAS, 525, 3318 [NASA ADS] [CrossRef] [Google Scholar]
  24. He, Z. 2023, ApJ, 954, L9 [Google Scholar]
  25. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  26. Ideta, M., Hozumi, S., Tsuchiya, T., & Takizawa, M. 2000, MNRAS, 311, 733 [Google Scholar]
  27. Iorio, G., & Belokurov, V. 2021, MNRAS, 502, 5686 [Google Scholar]
  28. Ivezic´, Ž., Connolly, A., Vanderplas, J., & Gray, A. 2014a, Statistics, Data Mining and Machine Learning in Astronomy (Princeton University Press) [Google Scholar]
  29. Ivezic´, Ž., Connolly, A. J., VanderPlas, J. T., & Gray, A. 2014b, Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data (Princeton: Princeton University Press) [Google Scholar]
  30. Iwanek, P., Poleski, R., Kozłowski, S., et al. 2023, ApJS, 264, 20 [NASA ADS] [CrossRef] [Google Scholar]
  31. Jayasinghe, T., Stanek, K. Z., Kochanek, C. S., et al. 2019, MNRAS, 486, 1907 [NASA ADS] [Google Scholar]
  32. Jeon, M., Kim, S. S., & Ann, H. B. 2009, ApJ, 696, 1899 [Google Scholar]
  33. Jónsson, V. H., & McMillan, P. J. 2024, A&A, 688, A38 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Kinemuchi, K., Smith, H. A., Woz´niak, P. R., McKay, T. A., & ROTSE Collaboration. 2006, AJ, 132, 1202 [Google Scholar]
  35. 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. Schmidt, IOS Press, 87 [Google Scholar]
  36. Layden, A. C. 1995, AJ, 110, 2288 [NASA ADS] [CrossRef] [Google Scholar]
  37. Li, X., Wang, H.-F., Luo, Y.-P., et al. 2023a, ApJ, 943, 88 [CrossRef] [Google Scholar]
  38. Li, X.-Y., Huang, Y., Liu, G.-C., Beers, T. C., & Zhang, H.-W. 2023b, ApJ, 944, 88 [NASA ADS] [CrossRef] [Google Scholar]
  39. Lindegren, L., Klioner, S. A., & Hernández, J. 2021, A&A, 649, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. López-Corredoira, M., Cabrera-Lavers, A., Garzón, F., & Hammersley, P. L. 2002, A&A, 394, 883 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Marsakov, V. A., Gozha, M. L., & Koval’, V. V. 2019, Astrophysics, 62, 467 [Google Scholar]
  42. Mateu, C. 2024, RNAAS, 8, 85 [Google Scholar]
  43. Mateu, C., & Vivas, A. K. 2018, MNRAS, 479, 211 [NASA ADS] [CrossRef] [Google Scholar]
  44. Mateu, C., Holl, B., De Ridder, J., & Rimoldini, L. 2020, MNRAS, 496, 3291 [Google Scholar]
  45. McMillan, P. J., Petersson, J., Tepper-Garcia, T., et al. 2022, MNRAS, 516, 4988 [NASA ADS] [CrossRef] [Google Scholar]
  46. Poggio, E., Drimmel, R., Andrae, R., et al. 2020, Nat. Astron., 4, 590 [NASA ADS] [CrossRef] [Google Scholar]
  47. Poggio, E., Laporte, C. F. P., Johnston, K. V., et al. 2021, MNRAS, 508, 541 [NASA ADS] [CrossRef] [Google Scholar]
  48. Poggio, E., Khanna, S., Drimmel, R., et al. 2025, A&A, 699, A199 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  49. Prudil, Z., Dékány, I., Grebel, E. K., & Kunder, A. 2020, MNRAS, 492, 3408 [Google Scholar]
  50. Ramos, P., Mateu, C., Antoja, T., et al. 2020, A&A, 640, C5 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Ramos, P., Antoja, T., Mateu, C., et al. 2021, A&A, 646, A99 [EDP Sciences] [Google Scholar]
  52. Ramos, P., Antoja, T., Yuan, Z., et al. 2022, A&A, 666, A64 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Reid, M. J., & Brunthaler, A. 2020, ApJ, 892, 39 [Google Scholar]
  54. Romero-Gómez, M., Mateu, C., Aguilar, L., Figueras, F., & Castro-Ginard, A. 2019, A&A, 627, A150 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Roškar, R., Debattista, V. P., Brooks, A. M., et al. 2010, MNRAS, 408, 783 [CrossRef] [Google Scholar]
  56. Sanders, J. L., & Das, P. 2018, MNRAS, 481, 4093 [CrossRef] [Google Scholar]
  57. Sarbadhicary, S. K., Heiger, M., Badenes, C., et al. 2021, ApJ, 912, 140 [Google Scholar]
  58. Schönrich, R., Binney, J., & Dehnen, W. 2010, MNRAS, 403, 1829 [NASA ADS] [CrossRef] [Google Scholar]
  59. Semczuk, M., Łokas, E. L., D’Onghia, E., et al. 2020, MNRAS, 498, 3535 [NASA ADS] [CrossRef] [Google Scholar]
  60. Sesar, B., Hernitschek, N., Mitrovic´, S., et al. 2017, AJ, 153, 204 [NASA ADS] [CrossRef] [Google Scholar]
  61. Skowron, D. M., Skowron, J., Mróz, P., et al. 2019, Science, 365, 478 [Google Scholar]
  62. Sparke, L. S. 1984, MNRAS, 211, 911 [Google Scholar]
  63. Sun, W., Huang, Y., Shen, H., et al. 2024, ApJ, 961, 141 [Google Scholar]
  64. Taylor, M. B. 2005, in Astronomical Data Analysis Software and Systems XIV, eds. P. Shopbell, M. Britton, & R. Ebert, Astronomical Society of the Pacific Conference Series, 347, 29 [NASA ADS] [Google Scholar]
  65. Taylor, M. B. 2006, in Astronomical Data Analysis Software and Systems XV, eds. C. Gabriel, C. Arviset, D. Ponz, & S. Enrique, Astronomical Society of the Pacific Conference Series, 351, 666 [Google Scholar]
  66. Uppal, N., Ganesh, S., & Schultheis, M. 2024, MNRAS, 527, 4863 [Google Scholar]
  67. Vanderplas, J., Connolly, A., Ivezic´, Ž., & Gray, A. 2012, in Conference on Intelligent Data Understanding (CIDU), 47 [Google Scholar]
  68. Walt, S. v. d., Colbert, S. C., & Varoquaux, G. 2011, Comput. Sci. Eng., 13, 22 [Google Scholar]
  69. Wang, H. F., López-Corredoira, M., Huang, Y., et al. 2020, ApJ, 897, 119 [NASA ADS] [CrossRef] [Google Scholar]
  70. Yusifov, I. 2004, in The Magnetized Interstellar Medium, eds. B. Uyaniker, W. Reich, & R. Wielebinski, 165 [Google Scholar]
  71. Zinn, R., Chen, X., Layden, A. C., & Casetti-Dinescu, D. I. 2020, MNRAS, 492, 2161 [NASA ADS] [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.