EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 677 (September 2023) A&A, 677 (2023) L4 References
Open Access
Issue
A&A
Volume 677, September 2023
Article Number L4
Number of page(s) 6
Section Letters to the Editor
DOI https://doi.org/10.1051/0004-6361/202347384
Published online 31 August 2023
  1. Adams, N. J., Conselice, C. J., Ferreira, L., et al. 2023, MNRAS, 518, 4755 [Google Scholar]
  2. Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481 [NASA ADS] [CrossRef] [Google Scholar]
  3. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Atek, H., Shuntov, M., Furtak, L. J., et al. 2023, MNRAS, 519, 1201 [Google Scholar]
  5. Behnel, S., Bradshaw, R., Citro, C., et al. 2011, Comput. Sci. Eng., 13, 31 [Google Scholar]
  6. Bertelli, G., Bressan, A., Chiosi, C., Fagotto, F., & Nasi, E. 1994, A&AS, 106, 275 [NASA ADS] [Google Scholar]
  7. Bouché, N., Dekel, A., Genzel, R., et al. 2010, ApJ, 718, 1001 [Google Scholar]
  8. Bovino, S., Grassi, T., Capelo, P. R., Schleicher, D. R. G., & Banerjee, R. 2016, A&A, 590, A15 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Boylan-Kolchin, M. 2023, Nat. Astron., 7, 731 [NASA ADS] [CrossRef] [Google Scholar]
  10. Branca, L., & Pallottini, A. 2023, MNRAS, 518, 5718 [Google Scholar]
  11. Castellano, M., Fontana, A., Treu, T., et al. 2022, ApJ, 938, L15 [NASA ADS] [CrossRef] [Google Scholar]
  12. Chaves-Montero, J., & Hearin, A. 2021, MNRAS, 506, 2373 [NASA ADS] [CrossRef] [Google Scholar]
  13. Dayal, P., Ferrara, A., Dunlop, J. S., & Pacucci, F. 2014, MNRAS, 445, 2545 [CrossRef] [Google Scholar]
  14. Decataldo, D., Pallottini, A., Ferrara, A., Vallini, L., & Gallerani, S. 2019, MNRAS, 487, 3377 [Google Scholar]
  15. Dekel, A., & Mandelker, N. 2014, MNRAS, 444, 2071 [NASA ADS] [CrossRef] [Google Scholar]
  16. Dekel, A., Sarkar, K. C., Birnboim, Y., Mandelker, N., & Li, Z. 2023, MNRAS, 523, 3201 [NASA ADS] [CrossRef] [Google Scholar]
  17. De Looze, I., Cormier, D., Lebouteiller, V., et al. 2014, A&A, 568, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Dome, T., Tacchella, S., Fialkov, A., et al. 2023, MNRAS, submitted [arXiv:2305.07066] [Google Scholar]
  19. Donnan, C. T., McLeod, D. J., Dunlop, J. S., et al. 2023, MNRAS, 518, 6011 [Google Scholar]
  20. Faucher-Giguère, C.-A. 2018, MNRAS, 473, 3717 [Google Scholar]
  21. Ferrara, A., Vallini, L., Pallottini, A., et al. 2019, MNRAS, 489, 1 [Google Scholar]
  22. Ferrara, A., Pallottini, A., & Dayal, P. 2023, MNRAS, 522, 3986 [NASA ADS] [CrossRef] [Google Scholar]
  23. Finkelstein, S. L., & Bagley, M. B. 2022, ApJ, 938, 25 [NASA ADS] [CrossRef] [Google Scholar]
  24. Finkelstein, S. L., Bagley, M. B., Haro, P. A., et al. 2022, ApJ, 940, L55 [NASA ADS] [CrossRef] [Google Scholar]
  25. Fiore, F., Ferrara, A., Bischetti, M., Feruglio, C., & Travascio, A. 2023, ApJ, 943, L27 [NASA ADS] [CrossRef] [Google Scholar]
  26. Furlanetto, S. R., & Mirocha, J. 2022, MNRAS, 511, 3895 [NASA ADS] [CrossRef] [Google Scholar]
  27. Furlanetto, S. R., Mirocha, J., Mebane, R. H., & Sun, G. 2017, MNRAS, 472, 1576 [NASA ADS] [CrossRef] [Google Scholar]
  28. Gelli, V., Salvadori, S., Ferrara, A., Pallottini, A., & Carniani, S. 2023, ApJ, submitted [arXiv:2303.13574] [Google Scholar]
  29. Gelli, V., Salvadori, S., Pallottini, A., & Ferrara, A. 2020, MNRAS, 498, 4134 [NASA ADS] [CrossRef] [Google Scholar]
  30. Gong, Y., Yue, B., Cao, Y., & Chen, X. 2023, ApJ, 947, 28 [NASA ADS] [CrossRef] [Google Scholar]
  31. Gouttenoire, Y., Trifinopoulos, S., Valogiannis, G., & Vanvlasselaer, M. 2023, ArXiv e-prints [arXiv:2307.01457] [Google Scholar]
  32. Grassi, T., Bovino, S., Schleicher, D. R. G., et al. 2014, MNRAS, 439, 2386 [Google Scholar]
  33. Hahn, O., & Abel, T. 2011, MNRAS, 415, 2101 [Google Scholar]
  34. Harikane, Y., Ouchi, M., Oguri, M., et al. 2023, ApJS, 265, 5 [NASA ADS] [CrossRef] [Google Scholar]
  35. Haslbauer, M., Kroupa, P., Zonoozi, A. H., & Haghi, H. 2022, ApJ, 939, L31 [NASA ADS] [CrossRef] [Google Scholar]
  36. Herrera-Camus, R., Sturm, E., Graciá-Carpio, J., et al. 2018, ApJ, 861, 95 [Google Scholar]
  37. Hirashita, H., & Ferrara, A. 2002, MNRAS, 337, 921 [NASA ADS] [CrossRef] [Google Scholar]
  38. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [Google Scholar]
  39. Kennicutt, R. C., Jr 1998, ApJ, 498, 541 [Google Scholar]
  40. Kohandel, M., Pallottini, A., Ferrara, A., et al. 2020, MNRAS, 499, 1250 [Google Scholar]
  41. Krumholz, M. R., Dekel, A., & McKee, C. F. 2012, ApJ, 745, 69 [Google Scholar]
  42. Lam, S. K., Pitrou, A., & Seibert, S. 2015, in Proc. Second Workshop on the LLVM Compiler Infrastructure in HPC, 1 [Google Scholar]
  43. Leja, J., Carnall, A. C., Johnson, B. D., Conroy, C., & Speagle, J. S. 2019, ApJ, 876, 3 [Google Scholar]
  44. Liu, B., & Bromm, V. 2022, ApJ, 937, L30 [NASA ADS] [CrossRef] [Google Scholar]
  45. Lomb, N. R. 1976, Ap&SS, 39, 447 [Google Scholar]
  46. Looser, T. J., D’Eugenio, F., Maiolino, R., et al. 2023, ArXiv e-prints [arXiv:2302.14155] [Google Scholar]
  47. Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415 [Google Scholar]
  48. Maiolino, R., & Mannucci, F. 2019, A&ARv, 27, 3 [Google Scholar]
  49. Markov, V., Gallerani, S., Pallottini, A., et al. 2023, ArXiv e-prints [arXiv:2304.11178] [Google Scholar]
  50. Mason, C. A., Trenti, M., & Treu, T. 2023, MNRAS, 521, 497 [NASA ADS] [CrossRef] [Google Scholar]
  51. McCaffrey, J., Hardin, S., Wise, J., & Regan, J. 2023, Open J. Astrophys., submitted [arXiv:2304.13755] [Google Scholar]
  52. Mirocha, J., & Furlanetto, S. R. 2023, MNRAS, 519, 843 [Google Scholar]
  53. Muñoz, J. B., Mirocha, J., Furlanetto, S., & Sabti, N. 2023, MNRAS, 526, L47 [CrossRef] [Google Scholar]
  54. Naidu, R. P., Oesch, P. A., van Dokkum, P., et al. 2022, ApJ, 940, L14 [NASA ADS] [CrossRef] [Google Scholar]
  55. Orr, M. E., Hayward, C. C., & Hopkins, P. F. 2019, MNRAS, 486, 4724 [NASA ADS] [CrossRef] [Google Scholar]
  56. Padmanabhan, H., & Loeb, A. 2023, ApJ, 953, L4 [NASA ADS] [CrossRef] [Google Scholar]
  57. Pallottini, A., Ferrara, A., Gallerani, S., Salvadori, S., & D’Odorico, V. 2014, MNRAS, 440, 2498 [NASA ADS] [CrossRef] [Google Scholar]
  58. Pallottini, A., Ferrara, A., Bovino, S., et al. 2017a, MNRAS, 471, 4128 [NASA ADS] [CrossRef] [Google Scholar]
  59. Pallottini, A., Ferrara, A., Gallerani, S., et al. 2017b, MNRAS, 465, 2540 [CrossRef] [Google Scholar]
  60. Pallottini, A., Ferrara, A., Decataldo, D., et al. 2019, MNRAS, 487, 1689 [Google Scholar]
  61. Pallottini, A., Ferrara, A., Gallerani, S., et al. 2022, MNRAS, 513, 5621 [NASA ADS] [Google Scholar]
  62. Parashari, P., & Laha, R. 2023, MNRAS, in press https://doi.org/10.1093/mnrasl/slad107 [Google Scholar]
  63. Planck Collaboration XVI 2014, A&A, 571, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  64. Pontzen, A., Roškar, R., Stinson, G. S., & Woods, R. 2013, Astrophysics Source Code Library [record ascl:1305.002] [Google Scholar]
  65. Popesso, P., Concas, A., Cresci, G., et al. 2023, MNRAS, 519, 1526 [Google Scholar]
  66. Qin, Y., Balu, S., & Wyithe, J. S. B. 2023, MNRAS, in press https://doi.org/10.1093/mnras/stad2448 [Google Scholar]
  67. Roberts-Borsani, G., Morishita, T., Treu, T., et al. 2022, ApJ, 938, L13 [NASA ADS] [CrossRef] [Google Scholar]
  68. Rosdahl, J., & Teyssier, R. 2015, MNRAS, 449, 4380 [Google Scholar]
  69. Rosdahl, J., Blaizot, J., Aubert, D., Stranex, T., & Teyssier, R. 2013, MNRAS, 436, 2188 [Google Scholar]
  70. Sabti, N., Muñoz, J. B., & Kamionkowski, M. 2023, ArXiv e-prints [arXiv:2305.07049] [Google Scholar]
  71. Santini, P., Fontana, A., Castellano, M., et al. 2023, ApJ, 942, L27 [NASA ADS] [CrossRef] [Google Scholar]
  72. Scargle, J. D. 1998, ApJ, 504, 405 [Google Scholar]
  73. Schmidt, M. 1959, ApJ, 129, 243 [NASA ADS] [CrossRef] [Google Scholar]
  74. Shen, X., Vogelsberger, M., Boylan-Kolchin, M., Tacchella, S., & Kannan, R. 2023, MNRAS, in press, https://doi.org/10.1093/mnras/stad2508 [Google Scholar]
  75. Silverman, B. W. 1986, Density Estimation for Statistics and Data Analysis (London: Chapman and Hall) [Google Scholar]
  76. Sun, G., Faucher-Giguère, C.-A., Hayward, C. C., & Shen, X. 2023, MNRAS, submitted [arXiv:2305.02713] [Google Scholar]
  77. Tacchella, S., Bose, S., Conroy, C., Eisenstein, D. J., & Johnson, B. D. 2018, ApJ, 868, 92 [NASA ADS] [CrossRef] [Google Scholar]
  78. Teyssier, R. 2002, A&A, 385, 337 [CrossRef] [EDP Sciences] [Google Scholar]
  79. Topping, M. W., Stark, D. P., Endsley, R., et al. 2022, MNRAS, 516, 975 [NASA ADS] [CrossRef] [Google Scholar]
  80. Treu, T., Roberts-Borsani, G., Bradac, M., et al. 2022, ApJ, 935, 110 [NASA ADS] [CrossRef] [Google Scholar]
  81. VanderPlas, J. T. 2018, ApJS, 236, 16 [Google Scholar]
  82. van der Walt, S., Colbert, S. C., & Varoquaux, G. 2011, Comput. Sci. Eng., 13, 22 [Google Scholar]
  83. Van Rossum, G., & de Boer, J. 1991, CWI Quart., 4, 283 [Google Scholar]
  84. Van Rossum, G., & Drake, F. L. 2009, Python 3 Reference Manual (Scotts Valley: CreateSpace) [Google Scholar]
  85. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Methods, 17, 261 [Google Scholar]
  86. Weingartner, J. C., & Draine, B. T. 2001, ApJ, 563, 842 [NASA ADS] [CrossRef] [Google Scholar]
  87. Wise, J. H., Turk, M. J., Norman, M. L., & Abel, T. 2012, ApJ, 745, 50 [NASA ADS] [CrossRef] [Google Scholar]
  88. Ziparo, F., Ferrara, A., Sommovigo, L., & Kohandel, M. 2023, MNRAS, 520, 2445 [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.