EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 699 (July 2025) A&A, 699 (2025) A273 References
Open Access
Issue
A&A
Volume 699, July 2025
Article Number A273
Number of page(s) 18
Section Galactic structure, stellar clusters and populations
DOI https://doi.org/10.1051/0004-6361/202452614
Published online 16 July 2025
  1. Alessi, B. S., Moitinho, A., & Dias, W. S. 2003, A&A, 410, 565 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  2. Almeida, A., Monteiro, H., & Dias, W. S. 2023, MNRAS, 525, 2315 [NASA ADS] [CrossRef] [Google Scholar]
  3. Almeida, D., Moitinho, A., & Moreira, S. 2025, A&A, 693, A305 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Anders, F., Cantat-Gaudin, T., Quadrino-Lodoso, I., et al. 2021, A&A, 645, L2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  7. Astropy Collaboration (Price-Whelan, A. M., et al.) 2022, ApJ, 935, 167 [NASA ADS] [CrossRef] [Google Scholar]
  8. Behnel, S., Bradshaw, R., Citro, C., et al. 2011, Comput. Sci. Eng., 13, 31 [Google Scholar]
  9. Bovy, J. 2015, ApJS, 216, 29 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127 [NASA ADS] [CrossRef] [Google Scholar]
  11. Brown, A. G. A. 2021, ARA&A, 59, 59 [NASA ADS] [CrossRef] [Google Scholar]
  12. Buitinck, L., Louppe, G., Blondel, M., et al. 2013, in ECML PKDD Workshop: Languages for Data Mining and Machine Learning, 108 [Google Scholar]
  13. Campello, R. J. G. B., Moulavi, D., & Sander, J. 2013, in Advances in Knowledge Discovery and Data Mining, eds. J. Pei, V. S. Tseng, L. Cao, H. Motoda, & G. Xu (Berlin, Heidelberg: Springer), 160 [Google Scholar]
  14. Cantat-Gaudin, T. 2022, Universe, 8, 111 [NASA ADS] [CrossRef] [Google Scholar]
  15. Cantat-Gaudin, T., & Anders, F. 2020, A&A, 633, A99 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  16. Cantat-Gaudin, T., Donati, P., Vallenari, A., et al. 2016, A&A, 588, A120 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  17. Cantat-Gaudin, T., Jordi, C., Vallenari, A., et al. 2018, A&A, 618, A93 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Cantat-Gaudin, T., Krone-Martins, A., Sedaghat, N., et al. 2019, A&A, 624, A126 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Cantat-Gaudin, T., Anders, F., Castro-Ginard, A., et al. 2020, A&A, 640, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Cantat-Gaudin, T., Fouesneau, M., Rix, H.-W., et al. 2023, A&A, 669, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  21. Carbajo-Hijarrubia, J., Casamiquela, L., Carrera, R., et al. 2024, A&A, 687, A239 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. Carraro, G., Geisler, D., Villanova, S., Frinchaboy, P. M., & Majewski, S. R. 2007, A&A, 476, 217 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Castro-Ginard, A., Jordi, C., Luri, X., et al. 2018, A&A, 618, A59 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Castro-Ginard, A., Jordi, C., Luri, X., et al. 2020, A&A, 635, A45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Castro-Ginard, A., Brown, A. G. A., Kostrzewa-Rutkowska, Z., et al. 2023, A&A, 677, A37 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Cavallo, L., Spina, L., Carraro, G., et al. 2024, AJ, 167, 12 [NASA ADS] [CrossRef] [Google Scholar]
  27. Chen, T., & Guestrin, C. 2016, in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’16 (New York, NY, USA: ACM), 785 [Google Scholar]
  28. Chen, Y. Q., & Zhao, G. 2020, MNRAS, 495, 2673 [NASA ADS] [CrossRef] [Google Scholar]
  29. Chen, Y., Girardi, L., Bressan, A., et al. 2014, MNRAS, 444, 2525 [Google Scholar]
  30. Chen, Y., Bressan, A., Girardi, L., et al. 2015, MNRAS, 452, 1068 [Google Scholar]
  31. Chen, X., Wang, S., Deng, L., et al. 2019, Nat. Astron., 3, 320 [NASA ADS] [CrossRef] [Google Scholar]
  32. Dias, W. S., Alessi, B. S., Moitinho, A., & Lépine, J. R. D. 2002, A&A, 389, 871 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2020, AJ, 159, 199 [NASA ADS] [CrossRef] [Google Scholar]
  34. Fabricius, C., Luri, X., Arenou, F., et al. 2021, A&A, 649, A5 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Feast, M. W., Menzies, J. W., Matsunaga, N., & Whitelock, P. A. 2014, Nature, 509, 342 [Google Scholar]
  36. Froebrich, D., Scholz, A., & Raftery, C. L. 2007, MNRAS, 374, 399 [Google Scholar]
  37. Gaia Collaboration (Prusti, T., et al.) 2016, A&A, 595, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Gaia Collaboration (Brown, A. G. A., et al.) 2018, A&A, 616, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Gaia Collaboration (Antoja, T., et al.) 2021a, A&A, 649, A8 [EDP Sciences] [Google Scholar]
  40. Gaia Collaboration (Brown, A. G. A., et al.) 2021b, A&A, 649, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Ginsburg, A., Sipőcz, B. M., Brasseur, C. E., et al. 2019, AJ, 157, 98 [Google Scholar]
  42. Ginsburg, A., Sipőcz, B., Brasseur, C. E., et al. 2024, https://doi.org/10.5281/zenodo.10799414 [Google Scholar]
  43. Gommers, R., Virtanen, P., Haberland, M., et al. 2024, https://doi.org/10.5281/zenodo.10909890 [Google Scholar]
  44. Górski, K. M., Hivon, E., Banday, A. J., et al. 2005, ApJ, 622, 759 [Google Scholar]
  45. Green, G. M., Schlafly, E., Zucker, C., Speagle, J. S., & Finkbeiner, D. 2019, ApJ, 887, 93 [NASA ADS] [CrossRef] [Google Scholar]
  46. Grisel, O., Mueller, A., Lars, et al. 2024, https://doi.org/10.5281/zenodo.10951361 [Google Scholar]
  47. Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357 [NASA ADS] [CrossRef] [Google Scholar]
  48. He, Z. 2023, ApJ, 954, L9 [Google Scholar]
  49. Herschel, W. 1786, Phil. Trans. R. Soc. London Ser. I, 76, 457 [Google Scholar]
  50. Herschel, W. 1789, Phil. Trans. R. Soc. London Ser. I, 79, 212 [Google Scholar]
  51. Hobbs, D., & Hog, E. 2018, IAU Symp., 330, 67 [Google Scholar]
  52. Hunt, E. L., & Reffert, S. 2021, A&A, 646, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Hunt, E. L., & Reffert, S. 2023, A&A, 673, A114 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Hunt, E. L., & Reffert, S. 2024, A&A, 686, A42 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  56. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  57. Janes, K., & Adler, D. 1982, ApJS, 49, 425 [Google Scholar]
  58. Kalberla, P. M. W., Dedes, L., Kerp, J., & Haud, U. 2007, A&A, 469, 511 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  59. Kharchenko, N. V., Piskunov, A. E., Röser, S., Schilbach, E., & Scholz, R. D. 2005, A&A, 440, 403 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  60. Kharchenko, N. V., Piskunov, A. E., Schilbach, E., Röser, S., & Scholz, R. D. 2013, A&A, 558, A53 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  61. King, I. 1962, AJ, 67, 471 [Google Scholar]
  62. Kluyver, T., Ragan-Kelley, B., Pérez, F., et al. 2016, in ELPUB, 87 [Google Scholar]
  63. Koposov, S., Belokurov, V., Evans, N. W., et al. 2008, ApJ, 686, 279 [NASA ADS] [CrossRef] [Google Scholar]
  64. Kroupa, P. 2001, MNRAS, 322, 231 [NASA ADS] [CrossRef] [Google Scholar]
  65. Krumholz, M. R., McKee, C. F., & Bland-Hawthorn, J. 2019, ARA&A, 57, 227 [NASA ADS] [CrossRef] [Google Scholar]
  66. Lada, C. J., & Lada, E. A. 2003, ARA&A, 41, 57 [Google Scholar]
  67. Lam, S. K., Pitrou, A., & Seibert, S. 2015, in Proc. Second Workshop on the LLVM Compiler Infrastructure in HPC, 1 [Google Scholar]
  68. Lam, S. K., stuartarchibald, Pitrou, A., et al. 2024, https://doi.org/10.5281/zenodo.10839385 [Google Scholar]
  69. Lamers, H. J. G. L. M., Gieles, M., Bastian, N., et al. 2005, A&A, 441, 117 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  70. Lemasle, B., Lala, H. N., Kovtyukh, V., et al. 2022, A&A, 668, A40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  71. Levine, E. S., Blitz, L., & Heiles, C. 2006, ApJ, 643, 881 [NASA ADS] [CrossRef] [Google Scholar]
  72. Lindegren, L., & Dravins, D. 2021, A&A, 652, A45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  73. Lindegren, L., Klioner, S. A., Hernández, J., et al. 2021, A&A, 649, A2 [EDP Sciences] [Google Scholar]
  74. Lundberg, S. M., & Lee, S.-I. 2017, in Advances in Neural Information Processing Systems 30, eds. I. Guyon, U. V. Luxburg, S. Bengio, et al. (UK: Curran Associates, Inc.), 4765 [Google Scholar]
  75. Magrini, L., Viscasillas Vázquez, C., Spina, L., et al. 2023, A&A, 669, A119 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  76. McInnes, L., Healy, J., & Astels, S. 2017, J. Open Source Softw., 2, 205 [NASA ADS] [CrossRef] [Google Scholar]
  77. McKinney, W. 2010, in Proceedings of the 9th Python in Science Conference, eds. S. van der Walt, & J. Millman, 56 [Google Scholar]
  78. Messier, C. 1781, Catalogue des Nébuleuses et des Amas d’étoiles (Catalog of Nebulae and Star Clusters), Connaissance des Temps ou des Mouvements Célestes, for 1784, 227 [Google Scholar]
  79. Moe, M., & Di Stefano, R. 2017, ApJS, 230, 15 [Google Scholar]
  80. Moitinho, A., Vázquez, R. A., Carraro, G., et al. 2006, MNRAS, 368, L77 [Google Scholar]
  81. Momany, Y., Zaggia, S., Gilmore, G., et al. 2006, A&A, 451, 515 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  82. Moreira, S., Moitinho, A., Silva, A., & Almeida, D. 2025, A&A, 694, A70 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Myers, N., Donor, J., Spoo, T., et al. 2022, AJ, 164, 85 [NASA ADS] [CrossRef] [Google Scholar]
  84. Netopil, M., Paunzen, E., & Stütz, C. 2012, in Star Clusters in the Era of Large Surveys, Astrophysics and Space Science Proceedings (Berlin: Springer), 29, 53 [Google Scholar]
  85. Netopil, M., Oralhan, I. A., Çakmak, H., Michel, R., & Karataş, Y. 2022, MNRAS, 509, 421 [Google Scholar]
  86. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  87. Perez, F., & Granger, B. E. 2007, Comput. Sci. Eng., 9, 21 [Google Scholar]
  88. Perren, G. I., Pera, M. S., Navone, H. D., & Vázquez, R. A. 2022, A&A, 663, A131 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Perren, G. I., Pera, M. S., Navone, H. D., & Vázquez, R. A. 2023, MNRAS, 526, 4107 [NASA ADS] [CrossRef] [Google Scholar]
  90. Petroff, M. A. 2021, ArXiv e-prints [arXiv:2107.02270] [Google Scholar]
  91. Pflamm-Altenburg, J., & Kroupa, P. 2008, Nature, 455, 641 [Google Scholar]
  92. Pflamm-Altenburg, J., González-Lópezlira, R. A., & Kroupa, P. 2013, MNRAS, 435, 2604 [CrossRef] [Google Scholar]
  93. Portegies Zwart, S. F., McMillan, S. L. W., & Gieles, M. 2010, ARA&A, 48, 431 [NASA ADS] [CrossRef] [Google Scholar]
  94. Riello, M., De Angeli, F., Evans, D. W., et al. 2021, A&A, 649, A3 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  95. Rix, H.-W., Hogg, D. W., Boubert, D., et al. 2021, AJ, 162, 142 [NASA ADS] [CrossRef] [Google Scholar]
  96. Rybizki, J., Green, G. M., Rix, H.-W., et al. 2022, MNRAS, 510, 2597 [NASA ADS] [CrossRef] [Google Scholar]
  97. Skowron, D. M., Skowron, J., Mróz, P., et al. 2019, Science, 365, 478 [Google Scholar]
  98. Spina, L., Magrini, L., & Cunha, K. 2022, Universe, 8, 87 [NASA ADS] [CrossRef] [Google Scholar]
  99. Sun, W., de Grijs, R., Fan, Z., & Cameron, E. 2016, ApJ, 816, 9 [Google Scholar]
  100. Tang, J., Bressan, A., Rosenfield, P., et al. 2014, MNRAS, 445, 4287 [NASA ADS] [CrossRef] [Google Scholar]
  101. Tarricq, Y., Soubiran, C., Casamiquela, L., et al. 2021, A&A, 647, A19 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  102. The Pandas development team 2024, https://doi.org/10.5281/zenodo.10957263 [Google Scholar]
  103. Trumpler, R. J. 1930, Lick Observ. Bull., 420, 154 [CrossRef] [Google Scholar]
  104. Usher, C., Dage, K. C., Girardi, L., et al. 2023, PASP, 135, 074201 [NASA ADS] [CrossRef] [Google Scholar]
  105. Van Rossum, G., & Drake, F. L. 2009, Python 3 Reference Manual (Scotts Valley, CA: CreateSpace) [Google Scholar]
  106. Vázquez, R. A., May, J., Carraro, G., et al. 2008, ApJ, 672, 930 [CrossRef] [Google Scholar]
  107. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Methods, 17, 261 [Google Scholar]
  108. Viscasillas Vázquez, C., Magrini, L., Spina, L., et al. 2023, A&A, 679, A122 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  109. Wagg, T., & Broekgaarden, F. S. 2024, ArXiv e-prints [arXiv:2406.04405] [Google Scholar]
  110. Wagg, T., Broekgaarden, F., & Gültekin, K. 2024, https://doi.org/10.5281/zenodo.13225824 [Google Scholar]
  111. Wenger, M., Ochsenbein, F., Egret, D., et al. 2000, Astron. Astrophys. Suppl. Ser., 143, 9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  112. Zhang, H., Chen, Y., & Zhao, G. 2021, ApJ, 919, 52 [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.