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Home All issues Volume 687 (July 2024) A&A, 687 (2024) A24 References
Open Access
Issue
A&A
Volume 687, July 2024
Article Number A24
Number of page(s) 25
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202348239
Published online 26 June 2024
  1. Ackermann, S., Schawinski, K., Zhang, C., Weigel, A. K., & Turp, M. D. 2018, MNRAS, 479, 415 [NASA ADS] [CrossRef] [Google Scholar]
  2. Aihara, H., Arimoto, N., Armstrong, R., et al. 2018, PASJ, 70, S4 [NASA ADS] [Google Scholar]
  3. Aihara, H., AlSayyad, Y., Ando, M., et al. 2022, PASJ, 74, 247 [NASA ADS] [CrossRef] [Google Scholar]
  4. Albawi, S., Mohammed, T. A., & Al-Zawi, S. 2017, in 2017 International Conference on Engineering and Technology (ICET), 1 [Google Scholar]
  5. Aubert, D., Pichon, C., & Colombi, S. 2004, MNRAS, 352, 376 [Google Scholar]
  6. Benítez, N. 2000, ApJ, 536, 571 [Google Scholar]
  7. Berg, T. A. M., Simard, L., Mendel, T. J., & Ellison, S. L. 2014, MNRAS, 440, L66 [NASA ADS] [CrossRef] [Google Scholar]
  8. Bickley, R. W., Bottrell, C., Hani, M. H., et al. 2021, MNRAS, 504, 372 [NASA ADS] [CrossRef] [Google Scholar]
  9. Bickley, R. W., Ellison, S. L., Patton, D. R., et al. 2022, MNRAS, 514, 3294 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bickley, R. W., Ellison, S. L., Patton, D. R., & Wilkinson, S. 2023, MNRAS, 519, 6149 [CrossRef] [Google Scholar]
  11. Bosch, J., Armstrong, R., Bickerton, S., et al. 2018, PASJ, 70, S5 [Google Scholar]
  12. Bottrell, C., Hani, M. H., Teimoorinia, H., et al. 2019, MNRAS, 490, 5390 [NASA ADS] [CrossRef] [Google Scholar]
  13. Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000 [NASA ADS] [CrossRef] [Google Scholar]
  14. Bustamante, S., Ellison, S. L., Patton, D. R., & Sparre, M. 2020, MNRAS, 494, 3469 [NASA ADS] [CrossRef] [Google Scholar]
  15. Calzetti, D., Kinney, A. L., & Storchi-Bergmann, T. 1994, ApJ, 429, 582 [Google Scholar]
  16. Chabrier, G. 2003, PASP, 115, 763 [Google Scholar]
  17. Cheng, T.-Y., Conselice, C. J., Aragón-Salamanca, A., et al. 2020, MNRAS, 493, 4209 [Google Scholar]
  18. Ciprijanovic, A., Kafkes, D., Jenkins, S., et al. 2020a, arXiv e-prints [arXiv: 2011.03591] [Google Scholar]
  19. Ciprijanovic, A., Snyder, G. F., Nord, B., & Peek, J. E. G. 2020b, Astron. Comput., 32, 100390 [NASA ADS] [CrossRef] [Google Scholar]
  20. Clauwens, B., Schaye, J., Franx, M., & Bower, R. G. 2018, MNRAS, 478, 3994 [NASA ADS] [CrossRef] [Google Scholar]
  21. Conselice, C. J. 2009, MNRAS, 399, L16 [NASA ADS] [Google Scholar]
  22. Conselice, C. J., Bershady, M. A., Dickinson, M., & Papovich, C. 2003, AJ, 126, 1183 [CrossRef] [Google Scholar]
  23. Conselice, C. J., Bluck, A. F. L., Mortlock, A., Palamara, D., & Benson, A. J. 2014, MNRAS, 444, 1125 [Google Scholar]
  24. Cortijo-Ferrero, C., González Delgado, R. M., Pérez, E., et al. 2017, A&A, 607, A70 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Darg, D. W., Kaviraj, S., Lintott, C. J., et al. 2010, MNRAS, 401, 1043 [NASA ADS] [CrossRef] [Google Scholar]
  26. Davis, M., Efstathiou, G., Frenk, C. S., & White, S. D. M. 1985, ApJ, 292, 371 [Google Scholar]
  27. de Ravel, L., Le Fèvre, O., Tresse, L., et al. 2009, A&A, 498, 379 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Desmons, A., Brough, S., Martínez-Lombilla, C., et al. 2023, MNRAS, 523, 4381 [CrossRef] [Google Scholar]
  29. Dieleman, S., Willett, K. W., & Dambre, J. 2015, MNRAS, 450, 1441 [NASA ADS] [CrossRef] [Google Scholar]
  30. Di Matteo, T., Khandai, N., DeGraf, C., et al. 2012, ApJ, 745, L29 [NASA ADS] [CrossRef] [Google Scholar]
  31. Dolag, K., Borgani, S., Murante, G., & Springet, V. 2009, MNRAS, 399, 497 [NASA ADS] [CrossRef] [Google Scholar]
  32. Domingos, P. 2012, Commun. ACM, 55, 78 [Google Scholar]
  33. Domínguez Sánchez, H., Huertas-Company, M., Bernardi, M., Tuccillo, D., & Fischer, J. L. 2018, MNRAS, 476, 3661 [Google Scholar]
  34. Domínguez Sánchez, H., Martin, G., Damjanov, I., et al. 2023, MNRAS, 521, 3861 [CrossRef] [Google Scholar]
  35. Dubois, Y., Pichon, C., Welker, C., et al. 2014, MNRAS, 444, 1453 [Google Scholar]
  36. Dubois, Y., Peirani, S., Pichon, C., et al. 2016, MNRAS, 463, 3948 [Google Scholar]
  37. Duncan, K., Conselice, C. J., Mundy, C., et al. 2019, ApJ, 876, 110 [NASA ADS] [CrossRef] [Google Scholar]
  38. Edge, A., Sutherland, W., Kuijken, K., et al. 2013, The Messenger, 154, 32 [NASA ADS] [Google Scholar]
  39. Eisert, L., Pillepich, A., Nelson, D., et al. 2023, MNRAS, 519, 2199 [Google Scholar]
  40. Ellison, S. L., Mendel, J. T., Scudder, J. M., Patton, D. R., & Palmer, M. J. D. 2013, MNRAS, 430, 3128 [NASA ADS] [CrossRef] [Google Scholar]
  41. Ellison, S. L., Viswanathan, A., Patton, D. R., et al. 2019, MNRAS, 487, 2491 [NASA ADS] [CrossRef] [Google Scholar]
  42. Fakhouri, O., & Ma, C.-P. 2008, MNRAS, 386, 577 [NASA ADS] [CrossRef] [Google Scholar]
  43. Ferreira, L., Conselice, C. J., Duncan, K., et al. 2020, ApJ, 895, 115 [NASA ADS] [CrossRef] [Google Scholar]
  44. Fitts, A., Boylan-Kolchin, M., Bullock, J. S., et al. 2018, MNRAS, 479, 319 [CrossRef] [Google Scholar]
  45. Fukushima, K. 1988, Neural Networks, 1, 119 [CrossRef] [Google Scholar]
  46. Girardi, L., Bressan, A., Bertelli, G., & Chiosi, C. 2000, A&AS, 141, 371 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  47. Goodfellow, I., Bengio, Y., & Courville, A. 2016, Deep Learning (MIT Press) [Google Scholar]
  48. Goulding, A. D., Greene, J. E., Bezanson, R., et al. 2018, PASJ, 70, S37 [NASA ADS] [CrossRef] [Google Scholar]
  49. Guzmán-Ortega, A., Rodriguez-Gomez, V., Snyder, G. F., Chamberlain, K., & Hernquist, L. 2023, MNRAS, 519, 4920 [CrossRef] [Google Scholar]
  50. Haardt, F., & Madau, P. 1996, ApJ, 461, 20 [Google Scholar]
  51. Hani, M. H., Sparre, M., Ellison, S. L., Torrey, P., & Vogelsberger, M. 2018, MNRAS, 475, 1160 [CrossRef] [Google Scholar]
  52. Ho, T. K. 1995, in Proceedings of 3rd International Conference on Document Analysis and Recognition, 1, IEEE, 278 [Google Scholar]
  53. Hopkins, P. F., Wetzel, A., Kereš, D., et al. 2018, MNRAS, 480, 800 [NASA ADS] [CrossRef] [Google Scholar]
  54. Huertas-Company, M., & Lanusse, F. 2023, PASA, 40, e001 [NASA ADS] [CrossRef] [Google Scholar]
  55. Huertas-Company, M., Gravet, R., Cabrera-Vives, G., et al. 2015, ApJS, 221, 8 [NASA ADS] [CrossRef] [Google Scholar]
  56. Huertas-Company, M., Primack, J. R., Dekel, A., et al. 2018, ApJ, 858, 114 [NASA ADS] [CrossRef] [Google Scholar]
  57. Huško, F., Lacey, C. G., & Baugh, C. M. 2022, MNRAS, 509, 5918 [Google Scholar]
  58. Ibata, R. A., McConnachie, A., Cuillandre, J.-C., et al. 2017, ApJ, 848, 128 [Google Scholar]
  59. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  60. Jackson, R. A., Kaviraj, S., Martin, G., et al. 2022, MNRAS, 511, 607 [NASA ADS] [CrossRef] [Google Scholar]
  61. Jiang, C. Y., Jing, Y. P., & Han, J. 2014, ApJ, 790, 7 [NASA ADS] [CrossRef] [Google Scholar]
  62. Karsten, J., Wang, L., Margalef-Bentabol, B., et al. 2023, A&A, 675, A159 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  63. Kennicutt, Jr., R. C. 1998, ApJ, 498, 541 [Google Scholar]
  64. Kitzbichler, M. G., & White, S. D. M. 2008, MNRAS, 391, 1489 [NASA ADS] [CrossRef] [Google Scholar]
  65. Komatsu, E., Smith, K. M., Dunkley, J., et al. 2011, ApJS, 192, 18 [Google Scholar]
  66. Kuijken, K., Heymans, C., Dvornik, A., et al. 2019, A&A, 625, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  67. Lazar, I., Kaviraj, S., Martin, G., et al. 2023, MNRAS, 520, 2109 [NASA ADS] [CrossRef] [Google Scholar]
  68. LeCun, Y., Bengio, Y., & Hinton, G. 2015, Nature, 521, 436 [Google Scholar]
  69. Leitherer, C., Schaerer, D., Goldader, J. D., et al. 1999, ApJS, 123, 3 [Google Scholar]
  70. Leitherer, C., Ortiz Otálvaro, P. A., Bresolin, F., et al. 2010, ApJS, 189, 309 [Google Scholar]
  71. Lemaître, G., Nogueira, F., & Aridas, C. K. 2017, J. Mach. Learn. Res., 18, 559 [Google Scholar]
  72. Lintott, C. J., Schawinski, K., Slosar, A., et al. 2008, MNRAS, 389, 1179 [NASA ADS] [CrossRef] [Google Scholar]
  73. Liske, J., Baldry, I. K., Driver, S. P., et al. 2015, MNRAS, 452, 2087 [Google Scholar]
  74. Liu, Z., Lin, Y., Cao, Y., et al. 2021, arXiv e-prints [arXiv: 2103.14030] [Google Scholar]
  75. López-Sanjuan, C., Cenarro, A. J., Varela, J., et al. 2015, A&A, 576, A53 [Google Scholar]
  76. Lotz, J. M., Primack, J., & Madau, P. 2004, AJ, 128, 163 [NASA ADS] [CrossRef] [Google Scholar]
  77. Lotz, J. M., Jonsson, P., Cox, T. J., & Primack, J. R. 2010, MNRAS, 404, 575 [Google Scholar]
  78. Man, A. W. S., Toft, S., Zirm, A. W., Wuyts, S., & van der Wel, A. 2012, ApJ, 744, 85 [NASA ADS] [CrossRef] [Google Scholar]
  79. Margalef-Bentabol, B., Huertas-Company, M., Charnock, T., et al. 2020, MNRAS, 496, 2346 [Google Scholar]
  80. Marinacci, F., Vogelsberger, M., Pakmor, R., et al. 2018, MNRAS, 480, 5113 [NASA ADS] [Google Scholar]
  81. Martin, G., Kaviraj, S., Devriendt, J. E. G., Dubois, Y., & Pichon, C. 2018, MNRAS, 480, 2266 [Google Scholar]
  82. Martin, G., Kaviraj, S., Hocking, A., Read, S. C., & Geach, J. E. 2020, MNRAS, 491, 1408 [Google Scholar]
  83. Martin, G., Jackson, R. A., Kaviraj, S., et al. 2021, MNRAS, 500, 4937 [Google Scholar]
  84. Martin, G., Bazkiaei, A. E., Spavone, M., et al. 2022, MNRAS, 513, 1459 [NASA ADS] [CrossRef] [Google Scholar]
  85. McAlpine, S., Harrison, C. M., Rosario, D. J., et al. 2020, MNRAS, 494, 5713 [NASA ADS] [CrossRef] [Google Scholar]
  86. Minghao, C., Kan, W., Bolin, N., et al. 2021, arXiv e-prints [arXiv:2111.14725] [Google Scholar]
  87. Miyazaki, S., Komiyama, Y., Kawanomoto, S., et al. 2018, PASJ, 70, S1 [NASA ADS] [Google Scholar]
  88. Moreno, J., Torrey, P., Ellison, S. L., et al. 2019, MNRAS, 485, 1320 [NASA ADS] [CrossRef] [Google Scholar]
  89. Mundy, C. J., Conselice, C. J., Duncan, K. J., et al. 2017, MNRAS, 470, 3507 [Google Scholar]
  90. Naiman, J. P., Pillepich, A., Springel, V., et al. 2018, MNRAS, 477, 1206 [Google Scholar]
  91. Nelson, D., Pillepich, A., Springel, V., et al. 2018, MNRAS, 475, 624 [Google Scholar]
  92. Nelson, D., Springel, V., Pillepich, A., et al. 2019, Computat. Astrophys. Cosmol., 6, 2 [NASA ADS] [CrossRef] [Google Scholar]
  93. Nevin, R., Blecha, L., Comerford, J., & Greene, J. 2019, ApJ, 872, 76 [NASA ADS] [CrossRef] [Google Scholar]
  94. Nomoto, K., Saio, H., Kato, M., & Hachisu, I. 2007, ApJ, 663, 1269 [Google Scholar]
  95. O’Shea, K., & Nash, R. 2015, arXiv e-prints [arXiv:1511.08458] [Google Scholar]
  96. Pascanu, R., Mikolov, T., & Bengio, Y. 2012, arXiv e-prints [arXiv:1211.5863] [Google Scholar]
  97. Patton, D. R., Wilson, K. D., Metrow, C. J., et al. 2020, MNRAS, 494, 4969 [NASA ADS] [CrossRef] [Google Scholar]
  98. Pearson, W. J., Wang, L., Alpaslan, M., et al. 2019a, A&A, 631, A51 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  99. Pearson, W. J., Wang, L., Trayford, J. W., Petrillo, C. E., & van der Tak, F. F. S. 2019b, A&A, 626, A49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  100. Pearson, W. J., Suelves, L. E., Ho, S. C. C., et al. 2022, A&A, 661, A52 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  101. Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, J. Mach. Learn. Res., 12, 2825 [Google Scholar]
  102. Pillepich, A., Nelson, D., Hernquist, L., et al. 2018a, MNRAS, 475, 648 [Google Scholar]
  103. Pillepich, A., Springel, V., Nelson, D., et al. 2018b, MNRAS, 473, 4077 [Google Scholar]
  104. Planck Collaboration XIII. 2016, A&A, 594, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  105. Qu, Y., Helly, J. C., Bower, R. G., et al. 2017, MNRAS, 464, 1659 [NASA ADS] [CrossRef] [Google Scholar]
  106. Rodriguez-Gomez, V., Genel, S., Vogelsberger, M., et al. 2015, MNRAS, 449, 49 [Google Scholar]
  107. Rodriguez-Gomez, V., Pillepich, A., Sales, L. V., et al. 2016, MNRAS, 458, 2371 [Google Scholar]
  108. Rodriguez-Gomez, V., Sales, L. V., Genel, S., et al. 2017, MNRAS, 467, 3083 [Google Scholar]
  109. Rodriguez-Gomez, V., Snyder, G. F., Lotz, J. M., et al. 2019, MNRAS, 483, 4140 [NASA ADS] [CrossRef] [Google Scholar]
  110. Rose, C., Kartaltepe, J. S., Snyder, G. F., et al. 2023, ApJ, 942, 54 [NASA ADS] [CrossRef] [Google Scholar]
  111. Russakovsky, O., Deng, J., Su, H., et al. 2015, Int. J. Comput. Vis., 115, 211 [Google Scholar]
  112. Satyapal, S., Ellison, S. L., McAlpine, W., et al. 2014, MNRAS, 441, 1297 [Google Scholar]
  113. Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521 [Google Scholar]
  114. Schmidhuber, J. 2015, Neural Networks, 61, 85 [CrossRef] [Google Scholar]
  115. Simmons, B. D., Lintott, C., Willett, K. W., et al. 2017, MNRAS, 464, 4420 [Google Scholar]
  116. Snyder, G. F., Lotz, J. M., Rodriguez-Gomez, V., et al. 2017, MNRAS, 468, 207 [NASA ADS] [CrossRef] [Google Scholar]
  117. Snyder, G. F., Rodriguez-Gomez, V., Lotz, J. M., et al. 2019, MNRAS, 486, 3702 [NASA ADS] [CrossRef] [Google Scholar]
  118. Springel, V., White, S. D. M., Tormen, G., & Kauffmann, G. 2001, MNRAS, 328, 726 [Google Scholar]
  119. Springel, V., Pakmor, R., Pillepich, A., et al. 2018, MNRAS, 475, 676 [Google Scholar]
  120. Srisawat, C., Knebe, A., Pearce, F. R., et al. 2013, MNRAS, 436, 150 [NASA ADS] [CrossRef] [Google Scholar]
  121. Sutherland, R. S., & Dopita, M. A. 1993, ApJS, 88, 253 [Google Scholar]
  122. Tan, M., & Le, Q. V. 2020, arXiv e-prints [arXiv:1905.11946] [Google Scholar]
  123. Teyssier, R. 2002, A&A, 385, 337 [CrossRef] [EDP Sciences] [Google Scholar]
  124. Tweed, D., Devriendt, J., Blaizot, J., Colombi, S., & Slyz, A. 2009, A&A, 506, 647 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  125. Ventou, E., Contini, T., Bouché, N., et al. 2017, A&A, 608, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  126. Vogelsberger, M., Genel, S., Springel, V., et al. 2014a, Nature, 509, 177 [Google Scholar]
  127. Vogelsberger, M., Genel, S., Springel, V., et al. 2014b, MNRAS, 444, 1518 [Google Scholar]
  128. Walmsley, M., Ferguson, A. M. N., Mann, R. G., & Lintott, C. J. 2019, MNRAS, 483, 2968 [NASA ADS] [CrossRef] [Google Scholar]
  129. Walmsley, M., Smith, L., Lintott, C., et al. 2020, MNRAS, 491, 1554 [Google Scholar]
  130. Walmsley, M., Lintott, C., Géron, T., et al. 2022a, MNRAS, 509, 3966 [Google Scholar]
  131. Walmsley, M., Slijepcevic, I., Bowles, M. R., & Scaife, A. 2022b, in Machine Learning for Astrophysics, proceedings of the Thirty-ninth International Conference on Machine Learning (ICML 2022), https://ml4astro.github.io/icml2822, 29 [Google Scholar]
  132. Walmsley, M., Allen, C., Aussel, B., et al. 2023, J. Open Source Softw., 8, 5312 [NASA ADS] [CrossRef] [Google Scholar]
  133. Wang, L., Pearson, W. J., & Rodriguez-Gomez, V. 2020, A&A, 644, A87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  134. White, S. D. M., & Rees, M. J. 1978, MNRAS, 183, 341 [Google Scholar]
  135. Whitney, A., Ferreira, L., Conselice, C. J., & Duncan, K. 2021, ApJ, 919, 139 [NASA ADS] [CrossRef] [Google Scholar]
  136. Wilkinson, S., Ellison, S. L., Bottrell, C., et al. 2022, MNRAS, 516, 4354 [CrossRef] [Google Scholar]
  137. Willett, K. W., Lintott, C. J., Bamford, S. P., et al. 2013, MNRAS, 435, 2835 [Google Scholar]
  138. Willett, K. W., Galloway, M. A., Bamford, S. P., et al. 2017, MNRAS, 464, 4176 [NASA ADS] [CrossRef] [Google Scholar]
  139. Williams, R. J., Quadri, R. F., & Franx, M. 2011, ApJ, 738, L25 [NASA ADS] [CrossRef] [Google Scholar]
  140. Woods, D. F., & Geller, M. J. 2007, AJ, 134, 527 [NASA ADS] [CrossRef] [Google Scholar]
  141. Wright, A. H., Hildebrandt, H., Kuijken, K., et al. 2019, A&A, 632, A34 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  142. Zanisi, L., Huertas-Company, M., Lanusse, F., et al. 2021, MNRAS, 501, 4359 [NASA ADS] [CrossRef] [Google Scholar]
  143. Zeiler, M. D. 2012, arXiv e-prints [arXiv:1212.5701] [Google Scholar]

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