Open Access
Issue
A&A
Volume 687, July 2024
Article Number A58
Number of page(s) 14
Section Cosmology (including clusters of galaxies)
DOI https://doi.org/10.1051/0004-6361/202348701
Published online 27 June 2024
  1. Anders, E., & Grevesse, N. 1989, Geochim. Cosmochim. Acta, 53, 197 [Google Scholar]
  2. Angelinelli, M., Vazza, F., Giocoli, C., et al. 2020, MNRAS, 495, 864 [NASA ADS] [CrossRef] [Google Scholar]
  3. Arévalo, P., Churazov, E., Zhuravleva, I., Hernández-Monteagudo, C., & Revnivtsev, M. 2012, MNRAS, 426, 1793 [CrossRef] [Google Scholar]
  4. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  6. Ayromlou, M., Nelson, D., Pillepich, A., et al. 2023, A&A, in press, https://doi.org/10.1051/0004-6361/202348612 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Barret, D., Decourchelle, A., Fabian, A., et al. 2020, Astron. Nachr., 341, 224 [NASA ADS] [CrossRef] [Google Scholar]
  8. Bartalucci, I., Molendi, S., Rasia, E., et al. 2023, A&A, 674, A179 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Biffi, V., Borgani, S., Murante, G., et al. 2016, ApJ, 827, 112 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bingham, E., Chen, J. P., Jankowiak, M., et al. 2019, J. Mach. Learn. Res., 20, 1 [Google Scholar]
  11. Botteon, A., Shimwell, T. W., Cassano, R., et al. 2022, A&A, 660, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Bradbury, J., Frostig, R., Hawkins, P., et al. 2018, JAX: composable transformations of Python+ NumPy programs, https://github.com/google/jax?tab=readme-ov-file#citing-jax [Google Scholar]
  13. Brüggen, M., & Vazza, F. 2015, in Magnetic Fields in Diffuse Media, eds. A. Lazarian, E. M. de Gouveia Dal Pino, & C. Melioli (Berlin, Heidelberg: Springer Berlin Heidelberg), Astrophys. Space Sci. Lib., 407, 599 [CrossRef] [Google Scholar]
  14. Brunetti, G., & Jones, T. W. 2014, IJMPD, 23, 1430007 [NASA ADS] [CrossRef] [Google Scholar]
  15. Brunetti, G., & Lazarian, A. 2016, MNRAS, 458, 2584 [Google Scholar]
  16. Campitiello, M. G., Ettori, S., Lovisari, L.& CHEX-MATE Collaboration 2022, EPJ Web Conf., 257, 00007 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  17. Cappellari, M., & Copin, Y. 2003, MNRAS, 342, 345 [Google Scholar]
  18. CHEX-MATE Collaboration (Arnaud, M., et al.) 2021, A&A, 650, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Churazov, E., Vikhlinin, A., Zhuravleva, I., et al. 2012, MNRAS, 421, 1123 [NASA ADS] [CrossRef] [Google Scholar]
  20. Clerc, N., Cucchetti, E., Pointecouteau, E., & Peille, P. 2019, A&A, 629, A143 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  21. Cucchetti, E., Clerc, N., Pointecouteau, E., Peille, P., & Pajot, F. 2019, A&A, 629, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. De Luca, F., De Petris, M., Yepes, G., et al. 2021, MNRAS, 504, 5383 [NASA ADS] [CrossRef] [Google Scholar]
  23. Dupourqué, S., Clerc, N., Pointecouteau, E., et al. 2023, A&A, 673, A91 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Ebeling, H., Mullis, C. R., & Tully, R. B. 2000, in Mapping the Hidden Universe: The Universe behind the Milky Way – The Universe in HI, eds. R. C. Kraan-Korteweg, P. A. Henning, & H. Andernach (Astronomical Society of the Pacific), ASP Conf. Proc., 218, 79 [Google Scholar]
  25. Eckert, D., Ettori, S., Pointecouteau, E., et al. 2017a, Astron. Nachr., 338, 293 [Google Scholar]
  26. Eckert, D., Gaspari, M., Vazza, F., et al. 2017b, ApJ, 843, L29 [Google Scholar]
  27. Eckert, D., Ghirardini, V., Ettori, S., et al. 2019, A&A, 621, A40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Ettori, S., & Eckert, D. 2022, A&A, 657, L1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. Gaspari, M., & Churazov, E. 2013, A&A, 559, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Gaspari, M., Brighenti, F., Temi, P., & Ettori, S. 2014a, ApJ, 783, L10 [NASA ADS] [CrossRef] [Google Scholar]
  31. Gaspari, M., Churazov, E., Nagai, D., Lau, E. T., & Zhuravleva, I. 2014b, A&A, 569, A67 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  32. Gatuzz, E., Sanders, J. S., Dennerl, K., et al. 2022a, MNRAS, 511, 4511 [NASA ADS] [CrossRef] [Google Scholar]
  33. Gatuzz, E., Sanders, J. S., Canning, R., et al. 2022b, MNRAS, 513, 1932 [NASA ADS] [CrossRef] [Google Scholar]
  34. Gatuzz, E., Sanders, J. S., Dennerl, K., et al. 2023a, MNRAS, 522, 2325 [NASA ADS] [CrossRef] [Google Scholar]
  35. Gatuzz, E., Mohapatra, R., Federrath, C., et al. 2023b, MNRAS, 524, 2945 [NASA ADS] [CrossRef] [Google Scholar]
  36. Ghirardini, V., Eckert, D., Ettori, S., et al. 2019, A&A, 621, A41 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  37. Gianfagna, G., Rasia, E., Cui, W., et al. 2023, MNRAS, 518, 4238 [Google Scholar]
  38. Hennigan, T., Cai, T., Norman, T., & Babuschkin, I. 2021, Haiku: Sonnet for JAX, 2020 https://github.com/google-deepmind/dm-haiku?tab=readme-ov-file#citing-haiku [Google Scholar]
  39. HI4PI Collaboration (Ben Bekhti, N., et al.) 2016, A&A, 594, A116 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Hinton, S. 2016, J. Open Source Softw., 1, 45 [NASA ADS] [CrossRef] [Google Scholar]
  41. Hitomi Collaboration (Aharonian, F., et al.) 2016, Nature, 535, 117 [Google Scholar]
  42. Hoffman, M. D., & Gelman, A. 2014, J. Mach. Learn. Res., 15, 1593 [Google Scholar]
  43. Hofmann, F., Sanders, J. S., Nandra, K., Clerc, N., & Gaspari, M. 2016, A&A, 585, A130 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  45. Huško, F., Lacey, C. G., & Baugh, C. M. 2022, MNRAS, 509, 5918 [Google Scholar]
  46. Khatri, R., & Gaspari, M. 2016, MNRAS, 463, 655 [Google Scholar]
  47. Kolmogorov, A. 1941, Dokl. Akad. Nauk SSSR, 30, 301 [NASA ADS] [Google Scholar]
  48. Kraft, R., Markevitch, M., Kilbourne, C., et al. 2022, arXiv e-prints [arXiv:2211.09827] [Google Scholar]
  49. Kravtsov, A. V., Vikhlinin, A., & Nagai, D. 2006, ApJ, 650, 128 [Google Scholar]
  50. Lau, E. T., Kravtsov, A. V., & Nagai, D. 2009, ApJ, 705, 1129 [NASA ADS] [CrossRef] [Google Scholar]
  51. Lovisari, L., Forman, W. R., Jones, C., et al. 2017, ApJ, 846, 51 [Google Scholar]
  52. Lovisari, L., Ettori, S., Rasia, E., et al. 2024, A&A, 682, A45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Mahdavi, A., Hoekstra, H., Babul, A., & Henry, J. P. 2008, MNRAS, 384, 1567 [NASA ADS] [CrossRef] [Google Scholar]
  54. McNamara, B. R., & Nulsen, P. E. J. 2012, New J. Phys., 14, 055023 [NASA ADS] [CrossRef] [Google Scholar]
  55. Melin, J.-B., Bartlett, J. G., & Delabrouille, J. 2006, A&A, 459, 341 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  56. Mohapatra, R., & Sharma, P. 2019, MNRAS, 484, 4881 [CrossRef] [Google Scholar]
  57. Mohapatra, R., Federrath, C., & Sharma, P. 2020, MNRAS, 493, 5838 [NASA ADS] [CrossRef] [Google Scholar]
  58. Mohapatra, R., Federrath, C., & Sharma, P. 2021, MNRAS, 500, 5072 [Google Scholar]
  59. Nelson, K., Rudd, D. H., Shaw, L., & Nagai, D. 2012, ApJ, 751, 121 [NASA ADS] [CrossRef] [Google Scholar]
  60. Nelson, K., Lau, E. T., Nagai, D., Rudd, D. H., & Yu, L. 2014, ApJ, 782, 107 [NASA ADS] [CrossRef] [Google Scholar]
  61. Ogorzalek, A., Zhuravleva, I., Allen, S. W., et al. 2017, MNRAS, 472, 1659 [NASA ADS] [CrossRef] [Google Scholar]
  62. Ota, N., & Yoshida, H. 2016, PASJ, 68, S19 [NASA ADS] [CrossRef] [Google Scholar]
  63. Ota, N., Fukazawa, Y., Fabian, A. C., et al. 2007, PASJ, 59, S351 [NASA ADS] [CrossRef] [Google Scholar]
  64. Papamakarios, G., Pavlakou, T., & Murray, I. 2017, Advances in Neural Information Processing Systems (Curran Associates, Inc.), 30 [Google Scholar]
  65. Papamakarios, G., Sterratt, D., & Murray, I. 2019, Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (PMLR), 837 [Google Scholar]
  66. Phan, D., Pradhan, N., & Jankowiak, M. 2019, arXiv e-prints [arXiv:1912.11554] [Google Scholar]
  67. Piffaretti, R., & Valdarnini, R. 2008, A&A, 491, 71 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Pinto, C., Sanders, J. S., Werner, N., et al. 2015, A&A, 575, A38 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Planck Collaboration XXVII. 2016, A&A, 594, A27 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  70. Pratt, G. W., Arnaud, M., Biviano, A., et al. 2019, Space Sci. Rev., 215, 25 [Google Scholar]
  71. Rasia, E., Meneghetti, M., Martino, R., et al. 2012, New J. Phys., 14, 055018 [Google Scholar]
  72. Rasia, E., Meneghetti, M., & Ettori, S. 2013, Astron. Rev., 8, 40 [Google Scholar]
  73. Romero, C. E., Gaspari, M., Schellenberger, G., et al. 2023, ApJ, 951, 41 [NASA ADS] [CrossRef] [Google Scholar]
  74. Roncarelli, M., Gaspari, M., Ettori, S., et al. 2018, A&A, 618, A39 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  75. Rossetti, M., Eckert, D., Gastaldello, F., et al. 2024, A&A, 686, A68 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  76. Sanders, J. S., & Fabian, A. C. 2013, MNRAS, 429, 2727 [NASA ADS] [CrossRef] [Google Scholar]
  77. Sanders, J. S., Fabian, A. C., & Smith, R. K. 2011, MNRAS, 410, 1797 [NASA ADS] [Google Scholar]
  78. Schmidt, W., Engels, J. F., Niemeyer, J. C., & Almgren, A. S. 2016, MNRAS, 459, 701 [NASA ADS] [CrossRef] [Google Scholar]
  79. Schuecker, P., Finoguenov, A., Miniati, F., Böhringer, H., & Briel, U. G. 2004, A&A, 426, 387 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  80. Shi, X., & Zhang, C. 2019, MNRAS, 487, 1072 [NASA ADS] [CrossRef] [Google Scholar]
  81. Shi, X., Komatsu, E., Nagai, D., & Lau, E. T. 2016, MNRAS, 455, 2936 [NASA ADS] [CrossRef] [Google Scholar]
  82. Shimwell, T. W., Tasse, C., Hardcastle, M. J., et al. 2019, A&A, 622, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Shimwell, T. W., Hardcastle, M. J., Tasse, C., et al. 2022, A&A, 659, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  84. Simionescu, A., ZuHone, J., Zhuravleva, I., et al. 2019, Space Sci. Rev., 215, 24 [NASA ADS] [CrossRef] [Google Scholar]
  85. Simonte, M., Vazza, F., Brighenti, F., et al. 2022, A&A, 658, A149 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  86. Snowden, S. L., Mushotzky, R. F., Kuntz, K. D., & Davis, D. S. 2008, A&A, 478, 615 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  87. Sugawara, C., Takizawa, M., & Nakazawa, K. 2009, PASJ, 61, 1293 [NASA ADS] [Google Scholar]
  88. Tamura, T., Hayashida, K., Ueda, S., & Nagai, M. 2011, PASJ, 63, S1009 [NASA ADS] [CrossRef] [Google Scholar]
  89. Tamura, T., Yamasaki, N. Y., Iizuka, R., et al. 2014, ApJ, 782, 38 [NASA ADS] [CrossRef] [Google Scholar]
  90. Tejero-Cantero, A., Boelts, J., Deistler, M., et al. 2020, J. Open Source Softw., 5, 2505 [NASA ADS] [CrossRef] [Google Scholar]
  91. Terada, Y., Holland, M., Loewenstein, M., et al. 2021, J. Astron. Telesc. Instrum. Syst., 7, 037001 [NASA ADS] [CrossRef] [Google Scholar]
  92. van der Velden, E. 2020, J. Open Source Softw., 5, 2004 [Google Scholar]
  93. van Haarlem, M. P., Wise, M. W., Gunst, A. W., et al. 2013, A&A, 556, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  94. Vazza, F., Roediger, E., & Brüggen, M. 2012, A&A, 544, A103 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  95. Vazza, F., Angelinelli, M., Jones, T. W., et al. 2018, MNRAS, 481, L120 [NASA ADS] [CrossRef] [Google Scholar]
  96. Vestuto, J. G., Ostriker, E. C., & Stone, J. M. 2003, ApJ, 590, 858 [CrossRef] [Google Scholar]
  97. Vikhlinin, A., Kravtsov, A., Forman, W., et al. 2006, ApJ, 640, 691 [Google Scholar]
  98. Voit, G. M., Meece, G., Li, Y., et al. 2017, ApJ, 845, 80 [Google Scholar]
  99. Weisstein, E. W. 1995, Fourier Transform (Wolfram Research, Inc.) [Google Scholar]
  100. XRISM Science Team 2020, ArXiv e-prints [arXiv:2003.04962] [Google Scholar]
  101. Zhang, Y.-Y., Okabe, N., Finoguenov, A., et al. 2010, ApJ, 711, 1033 [NASA ADS] [CrossRef] [Google Scholar]
  102. Zhang, X., Simionescu, A., Gastaldello, F., et al. 2023, A&A, 672, A42 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  103. Zhang, C., Zhuravleva, I., Markevitch, M., et al. 2024, MNRAS, 530, 4234 [NASA ADS] [CrossRef] [Google Scholar]
  104. Zhuravleva, I., Churazov, E. M., Schekochihin, A. A., et al. 2014a, ApJ, 788, L13 [Google Scholar]
  105. Zhuravleva, I., Churazov, E., Schekochihin, A. A., et al. 2014b, Nature, 515, 85 [Google Scholar]
  106. Zhuravleva, I., Churazov, E., Arévalo, P., et al. 2015, MNRAS, 450, 4184 [NASA ADS] [CrossRef] [Google Scholar]
  107. Zhuravleva, I., Allen, S. W., Mantz, A., & Werner, N. 2018, ApJ, 865, 53 [CrossRef] [Google Scholar]
  108. Zhuravleva, I., Chen, M. C., Churazov, E., et al. 2023, MNRAS, 520, 5157 [Google Scholar]
  109. ZuHone, J. A., & Roediger, E. 2016, J. Plasma Phys., 82, 535820301 [CrossRef] [Google Scholar]
  110. ZuHone, J. A., Markevitch, M., & Zhuravleva, I. 2016, ApJ, 817, 110 [NASA ADS] [CrossRef] [Google Scholar]
  111. ZuHone, J. A., Miller, E. D., Bulbul, E., & Zhuravleva, I. 2018, ApJ, 853, 180 [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.