Press Release
Open Access
Issue
A&A
Volume 691, November 2024
Article Number A98
Number of page(s) 19
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/202451427
Published online 31 October 2024
  1. Ambrosch, M., Guiglion, G., Mikolaitis, Š., et al. 2023, A&A, 672, A46 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  2. Anders, F., Chiappini, C., Santiago, B. X., et al. 2014, A&A, 564, A115 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Anders, F., Chiappini, C., Santiago, B. X., et al. 2018, A&A, 619, A125 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Anders, F., Khalatyan, A., Chiappini, C., et al. 2019, A&A, 628, A94 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Anders, F., Khalatyan, A., Queiroz, A. B. A., et al. 2022, A&A, 658, A91 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Anders, F., Gispert, P., Ratcliffe, B., et al. 2023a, A&A, 678, A158 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Anders, F., Khalatyan, A., Queiroz, A., Nepal, S., & Chiappini, C. 2023b, in Highlights on Spanish Astrophysics XI, 349 [Google Scholar]
  8. Andrae, R., Fouesneau, M., Sordo, R., et al. 2023a, A&A, 674, A27 [CrossRef] [EDP Sciences] [Google Scholar]
  9. Andrae, R., Rix, H.-W., & Chandra, V. 2023b, ApJS, 267, 8 [NASA ADS] [CrossRef] [Google Scholar]
  10. Ardern-Arentsen, A., Monari, G., Queiroz, A. B. A., et al. 2024, MNRAS, 530, 3391 [NASA ADS] [CrossRef] [Google Scholar]
  11. Ardèvol, J., Monguió, M., Figueras, F., Romero-Gómez, M., & Carrasco, J. M. 2023, A&A, 678, A111 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Arentsen, A., Starkenburg, E., Martin, N. F., et al. 2020a, MNRAS, 496, 4964 [NASA ADS] [CrossRef] [Google Scholar]
  13. Arentsen, A., Starkenburg, E., Martin, N. F., et al. 2020b, MNRAS, 491, L11 [Google Scholar]
  14. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  16. Astropy Collaboration (Price-Whelan, A. M., et al.) 2022, ApJ, 935, 167 [NASA ADS] [CrossRef] [Google Scholar]
  17. Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., Demleitner, M., & Andrae, R. 2021, AJ, 161, 147 [Google Scholar]
  18. Barbuy, B., Chiappini, C., & Gerhard, O. 2018, ARA&A, 56, 223 [Google Scholar]
  19. Baron, D. 2019, arXiv e-prints [arXiv:1904.07248] [Google Scholar]
  20. Behnel, S., Bradshaw, R., Citro, C., et al. 2011, Comput. Sci. Eng., 13, 31 [Google Scholar]
  21. Bethapudi, S., & Desai, S. 2018, Astron. Comput., 23, 15 [NASA ADS] [CrossRef] [Google Scholar]
  22. Borisov, V., Leemann, T., Seßler, K., et al. 2021, arXiv e-prints [arXiv:2110.01889] [Google Scholar]
  23. Buitinck, L., Louppe, G., Blondel, M., et al. 2013, in ECML PKDD Workshop: Languages for Data Mining and Machine Learning, 108 [Google Scholar]
  24. Cantat-Gaudin, T., Anders, F., Castro-Ginard, A., et al. 2020, A&A, 640, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Carney, B. W., Aguilar, L., Latham, D. W., & Laird, J. B. 1990, AJ, 99, 201 [NASA ADS] [CrossRef] [Google Scholar]
  26. Carrasco, J. M., Weiler, M., Jordi, C., et al. 2021, A&A, 652, A86 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Castellani, V., Maceroni, C., & Tosi, M. 1983, A&A, 128, 64 [NASA ADS] [Google Scholar]
  28. Castro-Ginard, A., Jordi, C., Luri, X., Cantat-Gaudin, T., & Balaguer-Núñez, L. 2019, A&A, 627, A35 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. Castro-Ginard, A., McMillan, P. J., Luri, X., et al. 2021, A&A, 652, A162 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Chen, T., & Guestrin, C. 2016, arXiv e-prints [arXiv:1603.02754] [Google Scholar]
  31. Chiappini, C., Minchev, I., Starkenburg, E., et al. 2019, The Messenger, 175, 30 [NASA ADS] [Google Scholar]
  32. Chiti, A., Frebel, A., Mardini, M. K., et al. 2021, ApJS, 254, 31 [NASA ADS] [CrossRef] [Google Scholar]
  33. Christlieb, N., Battistini, C., Bonifacio, P., et al. 2019, The Messenger, 175, 26 [NASA ADS] [Google Scholar]
  34. Cioni, M. . R. L., Storm, J., Bell, C. P. M., et al. 2019, The Messenger, 175, 54 [NASA ADS] [Google Scholar]
  35. Ciucă, I., Kawata, D., Miglio, A., Davies, G. R., & Grand, R. J. J. 2021, MNRAS, 503, 2814 [Google Scholar]
  36. Collette, A. 2013, Python and HDF5 (O’Reilly) [Google Scholar]
  37. Collette, A., Kluyver, T., Caswell, T. A., et al. 2023, https://doi.org/10.5281/zenodo.7560547 [Google Scholar]
  38. Conroy, C., Bonaca, A., Cargile, P., et al. 2019, ApJ, 883, 107 [NASA ADS] [CrossRef] [Google Scholar]
  39. Cui, X.-Q., Zhao, Y.-H., Chu, Y.-Q., et al. 2012, Res. Astron. Astrophys., 12, 1197 [Google Scholar]
  40. Culpan, R., Geier, S., Reindl, N., et al. 2022, A&A, 662, A40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Cunha, P. A. C., & Humphrey, A. 2022, A&A, 666, A87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  42. Cutri, R. M., Skrutskie, M. F., van Dyk, S., et al. 2003, 2MASS All Sky Catalog of point sources [Google Scholar]
  43. Cutri, R. M., Wright, E. L., Conrow, T., et al. 2013, Explanatory Supplement to the AllWISE Data Release Products, Tech. rep. [Google Scholar]
  44. Dang, Y., Chen, Z., Li, H., & Shu, H. 2022, Appl. Artif. Intell., 36, 1 [Google Scholar]
  45. Das, P., & Binney, J. 2016, MNRAS, 460, 1725 [NASA ADS] [CrossRef] [Google Scholar]
  46. De Angeli, F., Weiler, M., Montegriffo, P., et al. 2023, A&A, 674, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  47. de Jong, R. S., Agertz, O., Berbel, A. A., et al. 2019, The Messenger, 175, 3 [NASA ADS] [Google Scholar]
  48. de Jong, R. S., Bellido-Tirado, O., Brynnel, J. G., et al. 2022, SPIE Conf. Ser., 12184, 1218414 [NASA ADS] [Google Scholar]
  49. Deng, L.-C., Newberg, H. J., Liu, C., et al. 2012, Res. Astron. Astrophys., 12, 735 [Google Scholar]
  50. De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, 2604 [NASA ADS] [CrossRef] [Google Scholar]
  51. Dobbs, C., & Baba, J. 2014, PASA, 31, e035 [NASA ADS] [CrossRef] [Google Scholar]
  52. Dobbs, C. L., Burkert, A., & Pringle, J. E. 2011, MNRAS, 417, 1318 [NASA ADS] [CrossRef] [Google Scholar]
  53. Duan, T., Avati, A., Ding, D. Y., et al. 2019, Thirty-seventh International Conference on Machine Learning 2020, [arXiv:1910.03225] [Google Scholar]
  54. Echeverry, D., Torres, S., Rebassa-Mansergas, A., & Ferrer-Burjachs, A. 2022, A&A, 667, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Fallows, C. P., & Sanders, J. L. 2022, MNRAS, 516, 5521 [NASA ADS] [CrossRef] [Google Scholar]
  56. Fallows, C. P., & Sanders, J. L. 2024, MNRAS, 531, 2126 [CrossRef] [Google Scholar]
  57. Fluke, C. J., & Jacobs, C. 2020, WIREs Data Mining Knowledge Discov., 10, e1349 [NASA ADS] [CrossRef] [Google Scholar]
  58. Fouesneau, M., Frémat, Y., Andrae, R., et al. 2023, A&A, 674, A28 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  59. Frebel, A., & Norris, J. E. 2015, ARA&A, 53, 631 [NASA ADS] [CrossRef] [Google Scholar]
  60. Gaia Collaboration (Prusti, T., et al.) 2016, A&A, 595, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  61. Gaia Collaboration (Babusiaux, C., et al.) 2018a, A&A, 616, A10 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  62. Gaia Collaboration (Brown, A. G. A., et al.) 2018b, A&A, 616, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  63. Gaia Collaboration (Brown, A. G. A., et al.) 2021, A&A, 649, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  64. Gaia Collaboration (Drimmel, R., et al.) 2023a, A&A, 674, A37 [CrossRef] [EDP Sciences] [Google Scholar]
  65. Gaia Collaboration (Montegriffo, P., et al.) 2023b, A&A, 674, A33 [CrossRef] [EDP Sciences] [Google Scholar]
  66. Gaia Collaboration (Vallenari, A., et al.) 2023c, A&A, 674, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  67. Galarza, C. A., Daflon, S., Placco, V. M., et al. 2022, A&A, 657, A35 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Gavel, A., Andrae, R., Fouesneau, M., Korn, A. J., & Sordo, R. 2021, A&A, 656, A93 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Gentile Fusillo, N. P., Tremblay, P. E., Cukanovaite, E., et al. 2021, MNRAS, 508, 3877 [NASA ADS] [CrossRef] [Google Scholar]
  70. Gilmore, G., Randich, S., Asplund, M., et al. 2012, The Messenger, 147, 25 [NASA ADS] [Google Scholar]
  71. Gilmore, G., Randich, S., Worley, C. C., et al. 2022, A&A, 666, A120 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  72. Ginsburg, A., Sipocz, B. M., Brasseur, C. E., et al. 2019, AJ, 157, 98 [NASA ADS] [CrossRef] [Google Scholar]
  73. Ginsburg, A., Sipo?cz, B., Brasseur, C. E., et al. 2024, https://doi.org/10.5281/zenodo.10799414 [Google Scholar]
  74. Gommers, R., Virtanen, P., Haberland, M., et al. 2024, https://doi.org/10.5281/zenodo.10909890 [Google Scholar]
  75. Górski, K. M., Hivon, E., Banday, A. J., et al. 2005, ApJ, 622, 759 [Google Scholar]
  76. Green, G. M., Schlafly, E., Zucker, C., Speagle, J. S., & Finkbeiner, D. 2019, ApJ, 887, 93 [NASA ADS] [CrossRef] [Google Scholar]
  77. Grenon, M. 1987, J. Astrophys. Astron., 8, 123 [NASA ADS] [CrossRef] [Google Scholar]
  78. Grinsztajn, L., Oyallon, E., & Varoquaux, G. 2022, arXiv e-prints [arXiv:2207.08815] [Google Scholar]
  79. Grisel, O., Mueller, A., Lars, et al. 2024, https://doi.org/10.5281/zenodo.11237090 [Google Scholar]
  80. Guiglion, G., Matijevic?, G., Queiroz, A. B. A., et al. 2020, A&A, 644, A168 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  81. Guiglion, G., Nepal, S., Chiappini, C., et al. 2024, A&A, 682, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  82. Halle, A., Di Matteo, P., Haywood, M., & Combes, F. 2015, A&A, 578, A58 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Harris, W. E. 2010, arXiv e-prints [arXiv:1012.3224] [Google Scholar]
  84. Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357 [NASA ADS] [CrossRef] [Google Scholar]
  85. Hattori, K. 2024, AJ, submitted [arXiv:2404.01269] [Google Scholar]
  86. Hayden, M. R., Sharma, S., Bland-Hawthorn, J., et al. 2022, MNRAS, 517, 5325 [NASA ADS] [CrossRef] [Google Scholar]
  87. He, X.-J., Luo, A. L., & Chen, Y.-Q. 2022, MNRAS, 512, 1710 [NASA ADS] [CrossRef] [Google Scholar]
  88. Hunt, E. L., & Reffert, S. 2023, A&A, 673, A114 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  90. Ivezić, Ž., Connelly, A. J., VanderPlas, J. T., & Gray, A. 2014, Statistics, Data Mining, and Machine Learning in Astronomy [Google Scholar]
  91. Janes, K. A. 1979, ApJS, 39, 135 [NASA ADS] [CrossRef] [Google Scholar]
  92. Jia, Y., Guo, S., Zhu, C., et al. 2023, Res. Astron. Astrophys., 23, 105012 [CrossRef] [Google Scholar]
  93. Joshi, Y. C., Deepak, & Malhotra, S. 2024, Front. Astron. Space Sci., 11, 1348321 [NASA ADS] [CrossRef] [Google Scholar]
  94. Keller, S. C., Schmidt, B. P., Bessell, M. S., et al. 2007, PASA, 24, 1 [NASA ADS] [CrossRef] [Google Scholar]
  95. Khoperskov, S., & Gerhard, O. 2022, A&A, 663, A38 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  96. Khoperskov, S., Di Matteo, P., Haywood, M., Gómez, A., & Snaith, O. N. 2020, A&A, 638, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  97. Klambauer, G., Unterthiner, T., Mayr, A., & Hochreiter, S. 2017, arXiv e-prints [arXiv:1706.02515] [Google Scholar]
  98. Kluyver, T., Ragan-Kelley, B., Pérez, F., et al. 2016, in ELPUB, 87 [Google Scholar]
  99. Lallement, R., Babusiaux, C., Vergely, J. L., et al. 2019, A&A, 625, A135 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  100. Lallement, R., Vergely, J. L., Valette, B., et al. 2014, A&A, 561, A91 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  101. Lallement, R., Vergely, J. L., Babusiaux, C., & Cox, N. L. J. 2022, A&A, 661, A147 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  102. Laroche, A., & Speagle, J. S. 2024, ApJ, submitted [arXiv:2404.07316] [Google Scholar]
  103. Leike, R. H., Glatzle, M., & Enßlin, T. A. 2020, A&A, 639, A138 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  104. Li, C., Zhang, Y., Cui, C., et al. 2021, MNRAS, 506, 1651 [NASA ADS] [CrossRef] [Google Scholar]
  105. Li, C., Zhang, Y., Cui, C., et al. 2022a, MNRAS, 509, 2289 [Google Scholar]
  106. Li, H., Aoki, W., Matsuno, T., et al. 2022b, ApJ, 931, 147 [NASA ADS] [CrossRef] [Google Scholar]
  107. Li, J., Wong, K. W. K., Hogg, D. W., Rix, H.-W., & Chandra, V. 2024, ApJS, 272, 2 [NASA ADS] [CrossRef] [Google Scholar]
  108. Lucey, M., Al Kharusi, N., Hawkins, K., et al. 2023, MNRAS, 523, 4049 [NASA ADS] [CrossRef] [Google Scholar]
  109. Luck, R. E. 2018, AJ, 156, 171 [Google Scholar]
  110. 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. (Curran Associates, Inc.), 4765 [Google Scholar]
  111. Lundberg, S. M., Erion, G., Chen, H., et al. 2020, Nat. Mach. Intell., 2, 2522 [Google Scholar]
  112. Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94 [NASA ADS] [CrossRef] [Google Scholar]
  113. Marín-Franch, A., Chueca, S., Moles, M., et al. 2012, SPIE Conf. Ser., 8450, 84503S [Google Scholar]
  114. Monachesi, A., Bell, E. F., Radburn-Smith, D. J., et al. 2016, MNRAS, 457, 1419 [Google Scholar]
  115. Montegriffo, P., De Angeli, F., Andrae, R., et al. 2023, A&A, 674, A3 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  116. Nepal, S., Chiappini, C., Guiglion, G., et al. 2024a, A&A, 681, L8 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  117. Nepal, S., Chiappini, C., Queiroz, A. B., et al. 2024b, A&A, 688, A167 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  118. Ness, M., Hogg, D. W., Rix, H. W., Ho, A. Y. Q., & Zasowski, G. 2015, ApJ, 808, 16 [NASA ADS] [CrossRef] [Google Scholar]
  119. Pantaleoni González, M., Maíz Apellániz, J., Barbá, R. H., & Reed, B. C. 2021, MNRAS, 504, 2968 [CrossRef] [Google Scholar]
  120. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  121. Perez, F., & Granger, B. E. 2007, Comput. Sci. Eng., 9, 21 [Google Scholar]
  122. Poggio, E., Drimmel, R., Cantat-Gaudin, T., et al. 2021, A&A, 651, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  123. Queiroz, A. B. A., Anders, F., Santiago, B. X., et al. 2018, MNRAS, 476, 2556 [Google Scholar]
  124. Queiroz, A. B. A., Anders, F., Chiappini, C., et al. 2020, A&A, 638, A76 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  125. Queiroz, A. B. A., Chiappini, C., Perez-Villegas, A., et al. 2021, A&A, 656, A156 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  126. Queiroz, A. B. A., Anders, F., Chiappini, C., et al. 2023, A&A, 673, A155 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  127. Rezaei Kh., S., Bailer-Jones, C. A. L., Soler, J. D., & Zari, E. 2020, A&A, 643, A151 [EDP Sciences] [Google Scholar]
  128. Rix, H.-W., Chandra, V., Andrae, R., et al. 2022, ApJ, 941, 45 [NASA ADS] [CrossRef] [Google Scholar]
  129. Rix, H.-W., Chandra, V., Zasowski, G., et al. 2024, ApJ, submitted [arXiv:2406.01706] [Google Scholar]
  130. Ruz-Mieres, D. 2022, https://doi.org/10.5281/zenodo.6674521 [Google Scholar]
  131. Rybizki, J., Green, G. M., Rix, H.-W., et al. 2022, MNRAS, 510, 2597 [NASA ADS] [CrossRef] [Google Scholar]
  132. Sale, S. E., & Magorrian, J. 2018, MNRAS, 481, 494 [NASA ADS] [CrossRef] [Google Scholar]
  133. Sen, S., Agarwal, S., Chakraborty, P., & Singh, K. P. 2022, Exp. Astron., 53, 1 [NASA ADS] [CrossRef] [Google Scholar]
  134. Shetty, R., & Ostriker, E. C. 2008, ApJ, 684, 978 [NASA ADS] [CrossRef] [Google Scholar]
  135. Shwartz-Ziv, R., & Armon, A. 2021, arXiv e-prints [arXiv:2106.03253] [Google Scholar]
  136. Soubiran, C., Brouillet, N., & Casamiquela, L. 2022, A&A, 663, A4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  137. Starkenburg, E., Martin, N., Youakim, K., et al. 2017, MNRAS, 471, 2587 [NASA ADS] [CrossRef] [Google Scholar]
  138. Steinmetz, M., Zwitter, T., Siebert, A., et al. 2006, AJ, 132, 1645 [Google Scholar]
  139. Steinmetz, M., Matijevic?, G., Enke, H., et al. 2020, AJ, 160, 82 [NASA ADS] [CrossRef] [Google Scholar]
  140. Suda, T., Katsuta, Y., Yamada, S., et al. 2008, PASJ, 60, 1159 [NASA ADS] [Google Scholar]
  141. The pandas development team, T. 2023, https://doi.org/10.5281/zenodo.10426137 [Google Scholar]
  142. Thomas, G. F., Battaglia, G., Gran, F., et al. 2024, A&A, 690, A54 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  143. Ting, Y.-S., Conroy, C., Rix, H.-W., & Cargile, P. 2019, ApJ, 879, 69 [Google Scholar]
  144. Tolamatti, A., Singh, K. K., & Yadav, K. K. 2023, MNRAS, 523, 5341 [CrossRef] [Google Scholar]
  145. Tsantaki, M., Pancino, E., Marrese, P., et al. 2022, A&A, 659, A95 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  146. Tunçel Güçtekin, S., Bilir, S., Karaali, S., Plevne, O., & Ak, S. 2019, Adv. Space Res., 63, 1360 [CrossRef] [Google Scholar]
  147. Van Rossum, G. & Drake, F. L. 2009, Python 3 Reference Manual (Scotts Valley, CA: CreateSpace) [Google Scholar]
  148. Vavilova, I., Pakuliak, L., Babyk, I., et al. 2020, in Knowledge Discovery in Big Data from Astronomy and Earth Observation, eds. P. Škoda, & F. Adam, 57 [CrossRef] [Google Scholar]
  149. Vergely, J. L., Lallement, R., & Cox, N. L. J. 2022, A&A, 664, A174 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  150. Vickers, J. J., Li, Z.-Y., Smith, M. C., & Shen, J. 2021, ApJ, 912, 32 [NASA ADS] [CrossRef] [Google Scholar]
  151. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261 [CrossRef] [Google Scholar]
  152. Wagg, T., & Broekgaarden, F. 2024a, The Software Citation Station [Google Scholar]
  153. Wagg, T., & Broekgaarden, F. S. 2024b, arXiv e-prints [arXiv:2406.04405] [Google Scholar]
  154. Waskom, M. L. 2021, J. Open Source Softw., 6, 3021 [CrossRef] [Google Scholar]
  155. Weiler, M., Carrasco, J. M., Fabricius, C., & Jordi, C. 2023, A&A, 671, A52 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  156. Wes McKinney. 2010, in Proceedings of the 9th Python in Science Conference, eds. S. van der Walt, & J. Millman, 56 [CrossRef] [Google Scholar]
  157. Whitten, D. D., Placco, V. M., Beers, T. C., et al. 2019, A&A, 622, A182 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  158. Witten, C. E. C., Aguado, D. S., Sanders, J. L., et al. 2022, MNRAS, 516, 3254 [NASA ADS] [CrossRef] [Google Scholar]
  159. Xiang, M., Rix, H.-W., Ting, Y.-S., et al. 2022, A&A, 662, A66 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  160. Xu, X.-j., Shao, Y., & Li, X.-D. 2024, ApJ, 962, 126 [NASA ADS] [CrossRef] [Google Scholar]
  161. Xylakis-Dornbusch, T., Christlieb, N., Lind, K., & Nordlander, T. 2022, A&A, 666, A58 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  162. Xylakis-Dornbusch, T., Christlieb, N., Hansen, T. T., et al. 2024, A&A, 687, A177 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  163. Yanny, B., Rockosi, C., Newberg, H. J., et al. 2009, AJ, 137, 4377 [Google Scholar]
  164. Yao, Y., Ji, A. P., Koposov, S. E., & Limberg, G. 2024, MNRAS, 527, 10937 [Google Scholar]
  165. Yi, Z., Chen, Z., Pan, J., et al. 2019, ApJ, 887, 241 [NASA ADS] [CrossRef] [Google Scholar]
  166. Yong, D., Da Costa, G. S., Bessell, M. S., et al. 2021, MNRAS, 507, 4102 [CrossRef] [Google Scholar]
  167. Youakim, K., Starkenburg, E., Aguado, D. S., et al. 2017, MNRAS, 472, 2963 [NASA ADS] [CrossRef] [Google Scholar]
  168. Zari, E., Rix, H. W., Frankel, N., et al. 2021, A&A, 650, A112 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  169. Zhang, X., Green, G. M., & Rix, H.-W. 2023, MNRAS, 524, 1855 [NASA ADS] [CrossRef] [Google Scholar]
  170. Zoccali, M. 2019, Bol. Asoc. Argentina Astron. Plata Argentina, 61, 137 [Google Scholar]
  171. Zonca, A., Singer, L., Lenz, D., et al. 2019, J. Open Source Softw., 4, 1298 [Google Scholar]
  172. Zonca, A., Singer, L., crosset, et al. 2024, https://doi.org/10.5281/zenodo.11337740 [Google Scholar]

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