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Home All issues Volume 689 (September 2024) A&A, 689 (2024) A58 References
Open Access
Issue
A&A
Volume 689, September 2024
Article Number A58
Number of page(s) 11
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/202449909
Published online 30 August 2024
  1. Acquaviva, V., Gawiser, E., & Guaita, L. 2011, ApJ, 737, 47 [NASA ADS] [CrossRef] [Google Scholar]
  2. Alsing, J., Wandelt, B., & Feeney, S. 2018, MNRAS, 477, 2874 [NASA ADS] [CrossRef] [Google Scholar]
  3. Alsing, J., Thorp, S., Deger, S., et al., 2024, ApJS, Submitted [arXiv:2402.00935] [Google Scholar]
  4. Angeloudi, E., Falcón-Barroso, J., Huertas-Company, M., et al. 2023, MNRAS, 523, 5408 [CrossRef] [Google Scholar]
  5. Cameron, E., & Pettitt, A. N. 2012, MNRAS, 425, 44 [NASA ADS] [CrossRef] [Google Scholar]
  6. Cappellari, M. 2023, MNRAS, 526, 3273 [NASA ADS] [CrossRef] [Google Scholar]
  7. Cappellari, M., & Emsellem, E. 2004, PASP, 116, 138 [Google Scholar]
  8. Cardoso, L. S. M., Gomes, J. M., & Papaderos, P. 2019, A&A, 622, A56 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Carnall, A. C., Leja, J., Johnson, B. D., et al. 2019, ApJ, 873, 44 [Google Scholar]
  10. Cenarro, A. J., Cardiel, N., Gorgas, J., et al. 2001, MNRAS, 326, 959 [NASA ADS] [CrossRef] [Google Scholar]
  11. Cervantes, J. L., & Vazdekis, A. 2008, MNRAS, 392, 691 [Google Scholar]
  12. Chabrier, G. 2003, PASP, 115, 763 [Google Scholar]
  13. Choi, J., Dotter, A., Conroy, C., et al. 2016, ApJ, 823, 102 [Google Scholar]
  14. Cirasuolo, M., Fairley, A., Rees, P., et al. 2020, The Messenger, 180, 10 [NASA ADS] [Google Scholar]
  15. Conroy, C. 2013, ARA&A, 51, 393 [NASA ADS] [CrossRef] [Google Scholar]
  16. Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486 [Google Scholar]
  17. Conselice, C. J. 2008, ASP Conf. Ser., 390, 403 [NASA ADS] [Google Scholar]
  18. Dalton, G., Trager, S. C., Abrams, D. C., et al. 2012, in Ground-based and Airborne Instrumentation for Astronomy IV, eds. I. S. McLean, S. K. Ramsay, & H. Takami, SPIE Conf. Ser., 8446, 84460P [NASA ADS] [Google Scholar]
  19. de Jong, R. 2011, The Messenger, 145, 14 [NASA ADS] [Google Scholar]
  20. De Masi, C., Vincenzo, F., Matteucci, F., et al. 2019, MNRAS, 483, 2217 [CrossRef] [Google Scholar]
  21. Falcón-Barroso, J., Sánchez-Blázquez, P., Vazdekis, A., et al. 2011, A&A, 532, A95 [Google Scholar]
  22. Ferland, G. J., Korista, K. T., Verner, D. A., et al. 1998, PASP, 110, 761 [Google Scholar]
  23. Fernandes, R. C., Mateus, A., Sodré, L., Stasińska, G., & Gomes, J. M. 2005, MNRAS, 358, 363 [CrossRef] [Google Scholar]
  24. Franx, M., & Illingworth, G. 1990, ApJ, 359, L41 [NASA ADS] [CrossRef] [Google Scholar]
  25. Girardi, L., Bressan, A., Bertelli, G., & Chiosi, C. 2000, A&AS, 141, 371 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Gonneau, A., Lyubenova, M., Lancon, A., et al. 2020, A&A, 634, A133 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Hahn, C., & Melchior, P. 2022, ApJ, 938, 11 [NASA ADS] [CrossRef] [Google Scholar]
  28. Hahn, C., Kwon, K. J., Tojeiro, R., et al. 2023a, ApJ, 945, 16 [NASA ADS] [CrossRef] [Google Scholar]
  29. Hahn, C., Eickenberg, M., Ho, S., et al. 2023b, JCAP, 2023, 010 [CrossRef] [Google Scholar]
  30. Hinton, G. E., & Salakhutdinov, R. R. 2006, Science, 313, 504 [Google Scholar]
  31. Huertas-Company, M., Sarmiento, R., & Knapen, J. H. 2023, RAS Tech. Instrum., 2, 441 [NASA ADS] [CrossRef] [Google Scholar]
  32. Hunt, L. J., Pimbblet, K. A., & Benoit, D. M. 2024, MNRAS, 529, 479 [CrossRef] [Google Scholar]
  33. Iyer, K., & Gawiser, E. 2017, ApJ, 838, 127 [NASA ADS] [CrossRef] [Google Scholar]
  34. Johnson, B. D., Leja, J., Conroy, C., & Speagle, J. S. 2021, ApJS, 254, 22 [NASA ADS] [CrossRef] [Google Scholar]
  35. Khullar, G., Nord, B., Ćiprijanović, A., Poh, J., & Xu, F. 2022, Mach. Learn. Sci. Technol., 3, 04LT04 [CrossRef] [Google Scholar]
  36. Kramer, M. A. 1991, AIChE J., 37, 233 [CrossRef] [Google Scholar]
  37. Kroupa, P. 2001, MNRAS, 322, 231 [NASA ADS] [CrossRef] [Google Scholar]
  38. Kwon, K. J., & Hahn, C. 2024, ApJ, submitted [arXiv:2401.12318] [Google Scholar]
  39. La Barbera, F., Ferreras, I., Vazdekis, A., et al. 2013, MNRAS, 433, 3017 [Google Scholar]
  40. Leja, J., Carnall, A. C., Johnson, B. D., Conroy, C., & Speagle, J. S. 2019, ApJ, 876, 3 [Google Scholar]
  41. Lilly, S. J., Carollo, C. M., Pipino, A., Renzini, A., & Peng, Y. 2013, ApJ, 772, 119 [NASA ADS] [CrossRef] [Google Scholar]
  42. Lovell, C. C., Acquaviva, V., Thomas, P. A., et al. 2019, MNRAS, 490, 5503 [NASA ADS] [CrossRef] [Google Scholar]
  43. Maksymowicz-Maciata, M., Spiniello, C., Martín-Navarro, I., et al. 2024, MNRAS, 531, 2864 [Google Scholar]
  44. Martín-Navarro, I., La Barbera, F., Vazdekis, A., Falcón-Barroso, J., & Ferreras, I. 2015, MNRAS, 447, 1033 [Google Scholar]
  45. Martín-Navarro, I., van de Ven, G., & Yıldırım, A. 2019, MNRAS, 487, 4939 [CrossRef] [Google Scholar]
  46. Martín-Navarro, I., Burchett, J. N., & Mezcua, M. 2020, MNRAS, 491, 1311 [Google Scholar]
  47. Martín-Navarro, I., Spiniello, C., Tortora, C., et al. 2023, MNRAS, 521, 1408 [CrossRef] [Google Scholar]
  48. McInnes, L., Healy, J., Saul, N., & Großberger, L. 2018, J. Open Source Softw., 3, 861 [CrossRef] [Google Scholar]
  49. Melchior, P., Liang, Y., Hahn, C., & Goulding, A. 2023, AJ, 166, 74 [NASA ADS] [CrossRef] [Google Scholar]
  50. Mishra-Sharma, S. 2022, Mach. Learn. Sci. Technol., 3, 01LT03 [CrossRef] [Google Scholar]
  51. Moser, B., Kacprzak, T., Fischbacher, S., et al. 2024, JCAP, 05, 049 [CrossRef] [Google Scholar]
  52. Ocvirk, P., Pichon, C., Lançon, A., & Thiébaut, E. 2006, MNRAS, 365, 74 [Google Scholar]
  53. Papamakarios, G., & Murray, I., ArXiv e-prints [arXiv:1605.06376] [Google Scholar]
  54. Papamakarios, G., Pavlakou, T., & Murray, I. 2017, ArXiv e-prints [arXiv:1705.07057] [Google Scholar]
  55. Pietrinferni, A., Cassisi, S., Salaris, M., & Castelli, F. 2006, ApJ, 642, 797 [Google Scholar]
  56. Planck Collaboration XVI. 2014, A&A, 571, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  57. Portillo, S. K. N., Parejko, J. K., Vergara, J. R., & Connolly, A. J. 2020, ApJ, 160, 45 [Google Scholar]
  58. Saleh, R. A., & Ehsanes Saleh, A. K. M. 2022, ArXiv e-prints [arXiv:2208.04564] [Google Scholar]
  59. Salpeter, E. E. 1955, ApJ, 121, 161 [Google Scholar]
  60. Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1 [Google Scholar]
  61. Silk, J., & Mamon, G. A. 2012, Res. Astron. Astrophys., 12, 917 [Google Scholar]
  62. Smith, M. J., & Geach, J. E. 2023, R. Soc. Open Sci., 10, 221454 [NASA ADS] [CrossRef] [Google Scholar]
  63. Tacchella, S., Conroy, C., Faber, S. M., et al. 2022, ApJ, 926, 134 [NASA ADS] [CrossRef] [Google Scholar]
  64. Talts, S., Betancourt, M., Simpson, D., Vehtari, A., & Gelman, A. 2018, ArXiv e-prints [arXiv:1804.06788] [Google Scholar]
  65. Teimoorinia, H., Archinuk, F., Woo, J., Shishehchi, S., & Bluck, A. F. L. 2022, ApJ, 163, 71 [Google Scholar]
  66. Tejero-Cantero, A., Boelts, J., Deistler, M., et al. 2020, J. Open Source Softw., 5, 2505 [NASA ADS] [CrossRef] [Google Scholar]
  67. Thomas, D., Maraston, C., & Bender, R. 2003, MNRAS, 339, 897 [NASA ADS] [CrossRef] [Google Scholar]
  68. Tojeiro, R., Heavens, A. F., Jimenez, R., & Panter, B. 2007, MNRAS, 381, 1252 [NASA ADS] [CrossRef] [Google Scholar]
  69. Vazdekis, A., Sánchez-Blázquez, P., Falcón-Barroso, J., et al. 2010, MNRAS, 404, 1639 [NASA ADS] [Google Scholar]
  70. Wang, B., Leja, J., Labbé, I., et al. 2024, ApJS, 270, 12 [NASA ADS] [CrossRef] [Google Scholar]
  71. Weidner, C., Ferreras, I., Vazdekis, A., & La Barbera, F. 2013, MNRAS, 435, 2274 [NASA ADS] [CrossRef] [Google Scholar]
  72. Wilkinson, D. M., Maraston, C., Goddard, D., Thomas, D., & Parikh, T. 2017, MNRAS, 472, 4297 [Google Scholar]
  73. Woo, J., Walters, D., Archinuk, F., et al. 2024, MNRAS, 530, 4260 [NASA ADS] [CrossRef] [Google Scholar]
  74. Worthey, G., Faber, S. M., & Gonzalez, J. J. 1992, ApJ, 398, 69 [Google Scholar]
  75. York, D. G., Adelman, J., Anderson, J. E., et al. 2000, AJ, 120, 1579 [Google Scholar]
  76. Zhang, K., Jayasinghe, T., & Bloom, J. 2023, Machine Learning for Astrophysics. Workshop at the Fortieth International Conference on Machine Learning (ICML 2023), 39 [Google Scholar]

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