EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 688 (August 2024) A&A, 688 (2024) A20 References
Open Access
Issue
A&A
Volume 688, August 2024
Article Number A20
Number of page(s) 23
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202349055
Published online 30 July 2024
  1. Abadi, M., Barham, P., Chen, J., et al. 2016, arXiv e-prints [arXiv:1605.08695] [Google Scholar]
  2. Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2009, ApJS, 182, 543 [Google Scholar]
  3. Aihara, H., AlSayyad, Y., Ando, M., et al. 2019, PASJ, 71, 114 [Google Scholar]
  4. Algera, H. S. B., Inami, H., Oesch, P. A., et al. 2023, MNRAS, 518, 6142 [Google Scholar]
  5. An, F. X., Stach, S. M., Smail, I., et al. 2018, ApJ, 862, 101 [NASA ADS] [CrossRef] [Google Scholar]
  6. An, F. X., Simpson, J. M., Smail, I., et al. 2019, ApJ, 886, 48 [NASA ADS] [CrossRef] [Google Scholar]
  7. Arnouts, S., Moscardini, L., Vanzella, E., et al. 2002, MNRAS, 329, 355 [Google Scholar]
  8. Becker, R. H., White, R. L., & Helfand, D. J. 1995, ApJ, 450, 559 [Google Scholar]
  9. Berta, S., Magnelli, B., Nordon, R., et al. 2011, A&A, 532, A49 [CrossRef] [EDP Sciences] [Google Scholar]
  10. Béthermin, M., Dole, H., Cousin, M., & Bavouzet, N. 2010, A&A, 516, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Béthermin, M., Daddi, E., Magdis, G., et al. 2015, A&A, 573, A113 [Google Scholar]
  12. Béthermin, M., Wu, H.-Y., Lagache, G., et al. 2017, A&A, 607, A89 [Google Scholar]
  13. Béthermin, M., Van Cuyck, M., Beelen, A., & Gkogkou, A. 2022, pySIDES: Simulated Infrared Dusty Extragalactic Sky in Python, Astrophysics Source Code Library, [record ascl:2204.016] [Google Scholar]
  14. Bourne, N., Dunlop, J. S., Merlin, E., et al. 2017, MNRAS, 467, 1360 [NASA ADS] [Google Scholar]
  15. Braak, C. J. F., Boer, M. P., Totir, L. R., et al. 2010, Genetics, 185, 1045 [CrossRef] [Google Scholar]
  16. Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJ, 686, 1503 [Google Scholar]
  17. Brinchmann, J., Charlot, S., White, S. D. M., et al. 2004, MNRAS, 351, 1151 [Google Scholar]
  18. Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000 [NASA ADS] [CrossRef] [Google Scholar]
  19. Bussmann, R. S., Riechers, D., Fialkov, A., et al. 2015, ApJ, 812, 43 [Google Scholar]
  20. Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682 [NASA ADS] [CrossRef] [Google Scholar]
  21. Casey, C. M. 2012, MNRAS, 425, 3094 [Google Scholar]
  22. Casey, C. M., Narayanan, D., & Cooray, A. 2014, Phys. Rep., 541, 45 [Google Scholar]
  23. Casey, C. M., Kartaltepe, J. S., Drakos, N. E., et al. 2023, ApJ, 954, 31 [NASA ADS] [CrossRef] [Google Scholar]
  24. Chabrier, G. 2003, PASP, 115, 763 [Google Scholar]
  25. Chapin, E. L., Chapman, S. C., Coppin, K. E., et al. 2011, MNRAS, 411, 505 [Google Scholar]
  26. Charlot, S., & Fall, S. M. 2000, ApJ, 539, 718 [Google Scholar]
  27. Condon, J. J., Cotton, W. D., Greisen, E. W., et al. 1998, AJ, 115, 1693 [Google Scholar]
  28. Dale, D. A., Helou, G., Magdis, G. E., et al. 2014, ApJ, 784, 83 [Google Scholar]
  29. Delhaize, J., Smolčić, V., Delvecchio, I., et al. 2017, A&A, 602, A4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Devlin, M. J., Ade, P. A. R., Aretxaga, I., et al. 2009, Nature, 458, 737 [NASA ADS] [CrossRef] [Google Scholar]
  31. Dole, H., Rieke, G. H., Lagache, G., et al. 2004, ApJS, 154, 93 [NASA ADS] [CrossRef] [Google Scholar]
  32. Draine, B. T., Aniano, G., Krause, O., et al. 2014, ApJ, 780, 172 [Google Scholar]
  33. Driver, S. P., Popescu, C. C., Tuffs, R. J., et al. 2008, ApJ, 678, L101 [NASA ADS] [CrossRef] [Google Scholar]
  34. Dudzevičiūtė, U., Smail, I., Swinbank, A. M., et al. 2020, MNRAS, 494, 3828 [Google Scholar]
  35. Eales, S., Dunne, L., Clements, D., et al. 2010, PASP, 122, 499 [NASA ADS] [CrossRef] [Google Scholar]
  36. Elbaz, D., Dickinson, M., Hwang, H. S., et al. 2011, A&A, 533, A119 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Euclid Collaboration (Moneti, A., et al.) 2022, A&A, 658, A126 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Euclid Collaboration (Bisigello, L., et al.) 2023, MNRAS, 520, 3529 [NASA ADS] [CrossRef] [Google Scholar]
  39. Fixsen, D. J., Dwek, E., Mather, J. C., Bennett, C. L., & Shafer, R. A. 1998, ApJ, 508, 123 [Google Scholar]
  40. Fritz, J., Franceschini, A., & Hatziminaoglou, E. 2006, MNRAS, 366, 767 [Google Scholar]
  41. Gao, F., Wang, L., Efstathiou, A., et al. 2021, A&A, 654, A117 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  42. Gardner, J. P., Mather, J. C., Clampin, M., et al. 2006, Space Sci. Rev., 123, 485 [Google Scholar]
  43. Geach, J. E., Dunlop, J. S., Halpern, M., et al. 2017, MNRAS, 465, 1789 [Google Scholar]
  44. Gkogkou, A., Béthermin, M., Lagache, G., et al. 2023, A&A, 670, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Gruppioni, C., Béthermin, M., Loiacono, F., et al. 2020, A&A, 643, A8 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Gürkan, G., Hardcastle, M. J., Smith, D. J. B., et al. 2018, MNRAS, 475, 3010 [Google Scholar]
  47. Hatziminaoglou, E., Farrah, D., Humphreys, E., et al. 2018, MNRAS, 480, 4974 [Google Scholar]
  48. Hauser, M. G., & Dwek, E. 2001, ARA&A, 39, 249 [Google Scholar]
  49. Heywood, I., Jarvis, M. J., Hale, C. L., et al. 2022, MNRAS, 509, 2150 [Google Scholar]
  50. Hodge, J. A., Karim, A., Smail, I., et al. 2013, ApJ, 768, 91 [Google Scholar]
  51. Holland, W. S., Bintley, D., Chapin, E. L., et al. 2013, MNRAS, 430, 2513 [Google Scholar]
  52. Hurley, P. D., Oliver, S., Betancourt, M., et al. 2017, MNRAS, 464, 885 [Google Scholar]
  53. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Ivison, R. J., Alexander, D. M., Biggs, A. D., et al. 2010, MNRAS, 402, 245 [Google Scholar]
  55. Jarvis, M. J., Smith, D. J. B., Bonfield, D. G., et al. 2010, MNRAS, 409, 92 [Google Scholar]
  56. Jarvis, M., Taylor, R., Agudo, I., et al. 2016, in MeerKAT Science: On the Pathway to the SKA, 6 [Google Scholar]
  57. Jin, S., Daddi, E., Liu, D., et al. 2018, ApJ, 864, 56 [Google Scholar]
  58. Jonas, J., & MeerKAT Team 2016, in MeerKAT Science: On the Pathway to the SKA, 1 [Google Scholar]
  59. Kingma, D. P., & Ba, J. 2014, arXiv e-prints [arXiv:1412.6980] [Google Scholar]
  60. Komatsu, E., Smith, K. M., Dunkley, J., et al. 2011, ApJS, 192, 18 [Google Scholar]
  61. Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24 [Google Scholar]
  62. Lang, D., Hogg, D. W., & Mykytyn, D. 2016, The Tractor: Probabilistic astronomical source detection and measurement, Astrophysics Source Code Library, [record ascl:1604.008] [Google Scholar]
  63. Larson, D., Dunkley, J., Hinshaw, G., et al. 2011, ApJS, 192, 16 [NASA ADS] [CrossRef] [Google Scholar]
  64. Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, arXiv e-prints [arXiv:1110.3193] [Google Scholar]
  65. Le Floc’h, E., Aussel, H., Ilbert, O., et al. 2009, ApJ, 703, 222 [Google Scholar]
  66. Lee, N., Sanders, D. B., Casey, C. M., et al. 2013, ApJ, 778, 131 [NASA ADS] [CrossRef] [Google Scholar]
  67. Liu, D., Daddi, E., Dickinson, M., et al. 2018, ApJ, 853, 172 [Google Scholar]
  68. Liu, D., Lang, P., Magnelli, B., et al. 2019, ApJS, 244, 40 [Google Scholar]
  69. Long, A. S., Casey, C. M., del P. Lagos, C., et al. 2023, ApJ, 953, 11 [NASA ADS] [CrossRef] [Google Scholar]
  70. Lutz, D., Poglitsch, A., Altieri, B., et al. 2011, A&A, 532, A90 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  71. Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415 [Google Scholar]
  72. Magnelli, B., Lutz, D., Berta, S., et al. 2010, A&A, 518, A28 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  73. Magnelli, B., Lutz, D., Santini, P., et al. 2012, A&A, 539, A155 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  74. Magnelli, B., Popesso, P., Berta, S., et al. 2013, A&A, 553, A132 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  75. Martis, N. S., Marchesini, D., Brammer, G. B., et al. 2016, ApJ, 827, L25 [CrossRef] [Google Scholar]
  76. McCracken, H. J., Milvang-Jensen, B., Dunlop, J., et al. 2012, A&A, 544, A156 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  77. Miller, N. A., Fomalont, E. B., Kellermann, K. I., et al. 2008, ApJS, 179, 114 [NASA ADS] [CrossRef] [Google Scholar]
  78. Moneti, A., McCracken, H. J., Hudelot, W., et al. 2023, VizieR Online Data Catalog, II/373 [Google Scholar]
  79. Nair, V., & Hinton, G. E. 2010, in Proceedings of the 27th International Conference on Machine Learning (ICML-10), 807 [Google Scholar]
  80. Nguyen, H. T., Schulz, B., Levenson, L., et al. 2010, A&A, 518, L5 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  81. Noeske, K. G., Weiner, B. J., Faber, S. M., et al. 2007, ApJ, 660, L43 [CrossRef] [Google Scholar]
  82. Noll, S., Burgarella, D., Giovannoli, E., et al. 2009, A&A, 507, 1793 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Oliver, S. J., Wang, L., Smith, A. J., et al. 2010, A&A, 518, A21 [Google Scholar]
  84. Oliver, S. J., Bock, J., Altieri, B., et al. 2012, MNRAS, 424, 1614 [NASA ADS] [CrossRef] [Google Scholar]
  85. Pannella, M., Carilli, C. L., Daddi, E., et al. 2009, ApJ, 698, L116 [Google Scholar]
  86. Pearson, W. J., Wang, L., van der Tak, F. F. S., et al. 2017, A&A, 603, A102 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  87. Pearson, W. J., Wang, L., Hurley, P. D., et al. 2018, A&A, 615, A146 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  88. Popesso, P., Morselli, L., Concas, A., et al. 2019, MNRAS, 490, 5285 [Google Scholar]
  89. Popesso, P., Concas, A., Cresci, G., et al. 2023, MNRAS, 519, 1526 [Google Scholar]
  90. Puget, J. L., Abergel, A., Bernard, J. P., et al. 1996, A&A, 308, L5 [Google Scholar]
  91. Rieke, G. H., Alonso-Herrero, A., Weiner, B. J., et al. 2009, ApJ, 692, 556 [NASA ADS] [CrossRef] [Google Scholar]
  92. Rodighiero, G., Lari, C., Pozzi, F., et al. 2006, MNRAS, 371, 1891 [NASA ADS] [CrossRef] [Google Scholar]
  93. Roseboom, I. G., Oliver, S. J., Kunz, M., et al. 2010, MNRAS, 409, 48 [Google Scholar]
  94. Roseboom, I. G., Ivison, R. J., Greve, T. R., et al. 2012, MNRAS, 419, 2758 [NASA ADS] [CrossRef] [Google Scholar]
  95. Sanders, D. B., Salvato, M., Aussel, H., et al. 2007, ApJS, 172, 86 [Google Scholar]
  96. Sawicki, M., Arnouts, S., Huang, J., et al. 2019, MNRAS, 489, 5202 [NASA ADS] [Google Scholar]
  97. Schinnerer, E., Sargent, M. T., Bondi, M., et al. 2010, ApJS, 188, 384 [Google Scholar]
  98. Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1 [Google Scholar]
  99. Scudder, J. M., Oliver, S., Hurley, P. D., et al. 2016, MNRAS, 460, 1119 [NASA ADS] [CrossRef] [Google Scholar]
  100. Serra, P., Amblard, A., Temi, P., et al. 2011, ApJ, 740, 22 [Google Scholar]
  101. Shirley, R., Duncan, K., Campos Varillas, M. C., et al. 2021, MNRAS, 507, 129 [NASA ADS] [CrossRef] [Google Scholar]
  102. Simpson, J. M., Smail, I., Swinbank, A. M., et al. 2019, ApJ, 880, 43 [NASA ADS] [CrossRef] [Google Scholar]
  103. Simpson, J. M., Smail, I., Dudzevičiūtė, U., et al. 2020, MNRAS, 495, 3409 [Google Scholar]
  104. Smith, A. J., Wang, L., Oliver, S. J., et al. 2012, MNRAS, 419, 377 [NASA ADS] [CrossRef] [Google Scholar]
  105. Smith, D. J. B., Jarvis, M. J., Hardcastle, M. J., et al. 2014, MNRAS, 445, 2232 [Google Scholar]
  106. Smolčić, V., Novak, M., Bondi, M., et al. 2017, A&A, 602, A1 [Google Scholar]
  107. Speagle, J. S., Steinhardt, C. L., Capak, P. L., & Silverman, J. D. 2014, ApJS, 214, 15 [Google Scholar]
  108. Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. 2014, J. Mach. Learn. Res., 15, 1929 [Google Scholar]
  109. Stalevski, M., Fritz, J., Baes, M., Nakos, T., & Popović, L. Č. 2012, MNRAS, 420, 2756 [Google Scholar]
  110. Stan Development Team 2015, Stan: A C++ library for probability and sampling, version 2.8. 0 [Google Scholar]
  111. Stan Development Team 2018, PyStan: the Python interface to Stan, version 2.19. 1.1 [Google Scholar]
  112. Tibshirani, R. 1996, J. Roy. Statist. Soc. Ser. B: Statist. Methodol., 58, 267 [CrossRef] [Google Scholar]
  113. Wang, L., Viero, M., Clarke, C., et al. 2014, MNRAS, 444, 2870 [Google Scholar]
  114. Wang, L., Norberg, P., Gunawardhana, M. L. P., et al. 2016, MNRAS, 461, 1898 [Google Scholar]
  115. Wang, L., Pearson, W. J., Cowley, W., et al. 2019, A&A, 624, A98 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  116. Wang, L., Gao, F., Best, P. N., et al. 2021, A&A, 648, A8 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  117. Weaver, J. R., Kauffmann, O. B., Ilbert, O., et al. 2022, ApJS, 258, 11 [NASA ADS] [CrossRef] [Google Scholar]
  118. Weaver, J. R., Davidzon, I., Toft, S., et al. 2023, A&A, 677, A184 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  119. Whitaker, K. E., Labbé, I., van Dokkum, P. G., et al. 2011, ApJ, 735, 86 [Google Scholar]
  120. Whitaker, K. E., van Dokkum, P. G., Brammer, G., & Franx, M. 2012, ApJ, 754, L29 [Google Scholar]
  121. Whitaker, K. E., Pope, A., Cybulski, R., et al. 2017, ApJ, 850, 208 [NASA ADS] [CrossRef] [Google Scholar]
  122. Wuyts, S., Förster Schreiber, N. M., van der Wel, A., et al. 2011, ApJ, 742, 96 [NASA ADS] [CrossRef] [Google Scholar]
  123. Zavala, J. A., Casey, C. M., Manning, S. M., et al. 2021, ApJ, 909, 165 [CrossRef] [Google Scholar]
  124. Zou, H. 2006, J. Am. Statist. Assoc., 101, 1418 [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.