EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 709 (May 2026) A&A, 709 (2026) A246 References
Open Access
Issue
A&A
Volume 709, May 2026
Article Number A246
Number of page(s) 12
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/202556979
Published online 25 May 2026
  1. Ackermann, M., Ajello, M., Albert, A., et al. 2015, ApJ, 813, L41 [NASA ADS] [CrossRef] [Google Scholar]
  2. Agazie, G., Anumarlapudi, A., Archibald, A. M., et al. 2023, ApJ, 951, L8 [NASA ADS] [CrossRef] [Google Scholar]
  3. Amaro-Seoane, P., Andrews, J., Sedda, M. A., et al. 2023, Liv. Rev. Relat., 26, 2 [NASA ADS] [CrossRef] [Google Scholar]
  4. Arévalo, P., Lira, P., Sánchez-Sáez, P., et al. 2023, MNRAS, 526, 6078 [CrossRef] [Google Scholar]
  5. Arévalo, P., Churazov, E., Lira, P., et al. 2024, A&A, 684, A133 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Armitage, P. J., & Natarajan, P. 2002, ApJ, 567, L9 [NASA ADS] [CrossRef] [Google Scholar]
  7. Ashton, G., Bernstein, N., Buchner, J., et al. 2022, Nat. Rev. Methods Primers, 2, 39 [NASA ADS] [CrossRef] [Google Scholar]
  8. Barret, D., & Vaughan, S. 2012, ApJ, 746, 131 [NASA ADS] [CrossRef] [Google Scholar]
  9. Begelman, M. C., Blandford, R. D., & Rees, M. J. 1980, Nature, 287, 307 [Google Scholar]
  10. Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2018, PASP, 131, 018002 [Google Scholar]
  11. Benati Gonçalves, H., Panda, S., Storchi Bergmann, T., Cackett, E. M., & Eracleous, M. 2025, ApJ, 988, 27 [Google Scholar]
  12. Bertassi, L., Charisi, M., Buscicchio, R., et al. 2025a, A&A, submitted [arXiv:2512.13688] [Google Scholar]
  13. Bertassi, L., Sottocorno, E., Rigamonti, F., et al. 2025b, A&A, 702, A165 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  14. Bloomfield, P. 2004, Fourier Analysis of Time Series: An Introduction (Wiley) [Google Scholar]
  15. Bortolas, E., Capelo, P. R., Zana, T., et al. 2020, MNRAS, 498, 3601 [Google Scholar]
  16. Bortolas, E., Bonetti, M., Dotti, M., et al. 2022, MNRAS, 512, 3365 [NASA ADS] [CrossRef] [Google Scholar]
  17. Buchner, J. 2023, Stat. Surv., 17, 169 [NASA ADS] [CrossRef] [Google Scholar]
  18. Burke, C. J., Shen, Y., Blaes, O., et al. 2021, Science, 373, 789 [NASA ADS] [CrossRef] [Google Scholar]
  19. Callegari, S., Mayer, L., Kazantzidis, S., et al. 2009, ApJ, 696, L89 [NASA ADS] [CrossRef] [Google Scholar]
  20. Charisi, M., Bartos, I., Haiman, Z., et al. 2016, MNRAS, 463, 2145 [Google Scholar]
  21. Chen, Y.-C., Liu, X., Liao, W.-T., et al. 2020, MNRAS, 499, 2245 [Google Scholar]
  22. Chen, Y.-C., Liu, X., Lazio, J., et al. 2023, ApJ, 958, 29 [NASA ADS] [CrossRef] [Google Scholar]
  23. Chen, Y.-C., Gross, A. C., Liu, X., et al. 2025, ApJ, 988, 126 [Google Scholar]
  24. Cocchiararo, F., Franchini, A., Lupi, A., & Sesana, A. 2024, A&A, 691, A250 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Comerford, J. M., Gerke, B. F., Newman, J. A., et al. 2009, ApJ, 698, 956 [Google Scholar]
  26. Covino, S., Landoni, M., Sandrinelli, A., & Treves, A. 2020, ApJ, 895, 122 [NASA ADS] [CrossRef] [Google Scholar]
  27. Covino, S., Tobar, F., & Treves, A. 2022, MNRAS, 513, 2841 [Google Scholar]
  28. De Rosa, A., Vignali, C., Bogdanović, T., et al. 2019, New Astron. Rev., 86, 101525 [Google Scholar]
  29. Decarli, R., Dotti, M., Fumagalli, M., et al. 2013, MNRAS, 433, 1492 [Google Scholar]
  30. Decarli, R., Dotti, M., Mazzucchelli, C., Montuori, C., & Volonteri, M. 2014, MNRAS, 445, 1558 [NASA ADS] [CrossRef] [Google Scholar]
  31. del Valle, L., Escala, A., Maureira-Fredes, C., et al. 2015, ApJ, 811, 59 [NASA ADS] [CrossRef] [Google Scholar]
  32. Djorgovski, S. G., Drake, A. J., Mahabal, A. A., et al. 2011, ArXiv e-prints [arXiv:1102.5004] [Google Scholar]
  33. D’Orazio, D. J., & Charisi, M. 2023, ArXiv e-prints [arXiv:2310.16896] [Google Scholar]
  34. D’Orazio, D. J., Haiman, Z., & Schiminovich, D. 2015, Nature, 525, 351 [Google Scholar]
  35. Dotti, M., & Ruszkowski, M. 2010, ApJ, 713, L37 [Google Scholar]
  36. Dotti, M., Sesana, A., & Decarli, R. 2012, Adv. Astron., 2012, 940568 [CrossRef] [Google Scholar]
  37. Dotti, M., Rigamonti, F., Rinaldi, S., et al. 2023, A&A, 680, A69 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. EPTA Collaboration and InPTA Collaboration, (Antoniadis, J., et al.) 2024, A&A, 690, A118 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Eracleous, M., Boroson, T. A., Halpern, J. P., & Liu, J. 2012, ApJS, 201, 23 [Google Scholar]
  40. Fiacconi, D., Mayer, L., Roškar, R., & Colpi, M. 2013, ApJ, 777, L14 [NASA ADS] [CrossRef] [Google Scholar]
  41. Foreman-Mackey, D., Agol, E., Angus, R., & Ambikasaran, S. 2017, AJ, 154, 220 [NASA ADS] [CrossRef] [Google Scholar]
  42. Franchini, A., Lupi, A., Sesana, A., & Haiman, Z. 2023, MNRAS, 522, 1569 [NASA ADS] [CrossRef] [Google Scholar]
  43. Gaskell, C. M. 1988, in Active Galactic Nuclei, eds. H. R. Miller, & P. J. Wiita, 307, 61 [Google Scholar]
  44. Governato, F., Colpi, M., & Maraschi, L. 1994, MNRAS, 271, 317 [Google Scholar]
  45. Graham, M. J., Djorgovski, S. G., Stern, D., et al. 2015, Nature, 518, 74 [Google Scholar]
  46. Haiman, Z., Kocsis, B., & Menou, K. 2009, ApJ, 700, 1952 [CrossRef] [Google Scholar]
  47. Haiman, Z., Xin, C., Bogdanović, T., et al. 2023, ArXiv e-prints [arXiv:2306.14990] [Google Scholar]
  48. Hu, B. X., D’Orazio, D. J., Haiman, Z., et al. 2020, MNRAS, 495, 4061 [Google Scholar]
  49. Hwang, H.-C., Shen, Y., Zakamska, N., & Liu, X. 2020, ApJ, 888, 73 [NASA ADS] [CrossRef] [Google Scholar]
  50. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  51. Jeffreys, H. 1998, The Theory of Probability (Oxford: OUP), Oxford Classic Texts Phys. Sci. [Google Scholar]
  52. Jenkins, G., & Watts, D. 1968, Spectral Analysis and Its Applications (Holden-Day) [Google Scholar]
  53. Kasliwal, V. P., Vogeley, M. S., & Richards, G. T. 2015, MNRAS, 451, 4328 [CrossRef] [Google Scholar]
  54. Kelly, B. C., Bechtold, J., & Siemiginowska, A. 2009, ApJ, 698, 895 [Google Scholar]
  55. Kormendy, J., & Gebhardt, K. 2001, AIP Conf. Ser., 586, 363 [Google Scholar]
  56. Kozłowski, S. 2017, A&A, 597, A128 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  57. Kozłowski, S., Kochanek, C. S., Udalski, A., et al. 2010, ApJ, 708, 927 [CrossRef] [Google Scholar]
  58. Li, Y.-R., Wang, J.-M., Ho, L. C., et al. 2016, ApJ, 822, 4 [NASA ADS] [CrossRef] [Google Scholar]
  59. Li, Y.-R., Wang, J.-M., Zhang, Z.-X., et al. 2019, ApJS, 241, 33 [Google Scholar]
  60. Liu, T., Gezari, S., Ayers, M., et al. 2019, ApJ, 884, 36 [Google Scholar]
  61. Lomb, N. R. 1976, Ap&SS, 39, 447 [Google Scholar]
  62. MacLeod, C. L., Ivezić, Ž., Kochanek, C. S., et al. 2010, ApJ, 721, 1014 [Google Scholar]
  63. Mannucci, F., Pancino, E., Belfiore, F., et al. 2022, Nat. Astron., 6, 1185 [NASA ADS] [CrossRef] [Google Scholar]
  64. Mikkola, S., & Valtonen, M. J. 1992, MNRAS, 259, 115 [NASA ADS] [CrossRef] [Google Scholar]
  65. Miles, M. T., Shannon, R. M., Reardon, D. J., et al. 2025, MNRAS, 536, 1489 [Google Scholar]
  66. Paolillo, M., & Papadakis, I. 2025, Nuovo Cimento Riv. Ser., 48, 537 [Google Scholar]
  67. Papadakis, I. E., & McHardy, I. M. 1995, MNRAS, 273, 923 [NASA ADS] [Google Scholar]
  68. Pfister, H., Volonteri, M., Dubois, Y., Dotti, M., & Colpi, M. 2019, MNRAS, 486, 101 [Google Scholar]
  69. Priestley, M. 1981, Spectral Analysis and Time Series (Academic Press) [Google Scholar]
  70. Rasmussen, C. E., & Williams, C. K. I. 2006, Gaussian Processes for Machine Learning [Google Scholar]
  71. Reardon, D. J., Zic, A., Shannon, R. M., et al. 2023, ApJ, 951, L6 [NASA ADS] [CrossRef] [Google Scholar]
  72. Rigamonti, F., Bertassi, L., Buscicchio, R., et al. 2025a, A&A, 702, A242 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  73. Rigamonti, F., Severgnini, P., Sottocorno, E., et al. 2025b, A&A, 693, A117 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  74. Runnoe, J. C., Eracleous, M., Pennell, A., et al. 2017, MNRAS, 468, 1683 [Google Scholar]
  75. Runnoe, J. C., Eracleous, M., Bogdanović, T., Halpern, J. P., & Sigurðsson, S. 2025, ApJ, 984, 17 [Google Scholar]
  76. Sandrinelli, A., Covino, S., Dotti, M., & Treves, A. 2016, AJ, 151, 54 [NASA ADS] [CrossRef] [Google Scholar]
  77. Sandrinelli, A., Covino, S., Treves, A., et al. 2018, A&A, 615, A118 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  78. Scargle, J. D. 1982, ApJ, 263, 835 [Google Scholar]
  79. Schwartzman, E., Clarke, T. E., Nyland, K., et al. 2024, ApJ, 961, 233 [NASA ADS] [Google Scholar]
  80. Scialpi, M., Mannucci, F., Marconcini, C., et al. 2024, A&A, 690, A57 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  81. Severgnini, P., Cicone, C., Della Ceca, R., et al. 2018, MNRAS, 479, 3804 [Google Scholar]
  82. Shen, Y., & Loeb, A. 2010, ApJ, 725, 249 [NASA ADS] [CrossRef] [Google Scholar]
  83. Skilling, J. 2006, Bayesian Anal., 1, 833 [Google Scholar]
  84. Sottocorno, E., Ogborn, M., Bertassi, L., et al. 2026, A&A, 708, A153 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  85. Souza Lima, R., Mayer, L., Capelo, P. R., Bortolas, E., & Quinn, T. R. 2020, ApJ, 899, 126 [Google Scholar]
  86. Su, Z.-B., Cai, Z.-Y., Sun, M., et al. 2024, ApJ, 969, 78 [Google Scholar]
  87. Thorne, K. S., & Braginskii, V. B. 1976, ApJ, 204, L1 [NASA ADS] [CrossRef] [Google Scholar]
  88. Trindade Falcão, A., Turner, T. J., Kraemer, S. B., et al. 2024, ApJ, 972, 185 [Google Scholar]
  89. Tsalmantza, P., Decarli, R., Dotti, M., & Hogg, D. W. 2011, ApJ, 738, 20 [Google Scholar]
  90. Uttley, P., McHardy, I. M., & Papadakis, I. E. 2002, MNRAS, 332, 231 [Google Scholar]
  91. Valtonen, M. J., Lehto, H. J., Nilsson, K., et al. 2008, Nature, 452, 851 [Google Scholar]
  92. van der Klis, M. 1989, in Fourier Techniques in X-Ray Timing, eds. H. Ögelman, & E. P. J. van den Heuvel (Dordrecht, Netherlands: Springer), 27 [Google Scholar]
  93. VanderPlas, J. T. 2018, ApJS, 236, 16 [Google Scholar]
  94. Varisco, L., Bortolas, E., Dotti, M., & Sesana, A. 2021, MNRAS, 508, 1533 [NASA ADS] [CrossRef] [Google Scholar]
  95. Varisco, L., Dotti, M., Bonetti, M., Bortolas, E., & Lupi, A. 2024, A&A, 689, A279 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  96. Vaughan, S., Edelson, R., Warwick, R. S., & Uttley, P. 2003, MNRAS, 345, 1271 [Google Scholar]
  97. Vaughan, S., Uttley, P., Markowitz, A. G., et al. 2016, MNRAS, 461, 3145 [Google Scholar]
  98. Veitch, J., Del Pozzo, W., Lyttle, A., et al. 2024, https://doi.org/10.5281/zenodo.12801702 [Google Scholar]
  99. Verbiest, J. P. W., Lentati, L., Hobbs, G., et al. 2016, MNRAS, 458, 1267 [Google Scholar]
  100. Vio, R., Andreani, P., & Biggs, A. 2010, A&A, 519, A85 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  101. Wang, H., & Shi, Y. 2019, Ap&SS, 364, 27 [Google Scholar]
  102. White, S. D. M., & Rees, M. J. 1978, MNRAS, 183, 341 [Google Scholar]
  103. Whittle, P. 1951, Hypothesis Testing in Time Series Analysis (Almqvist& Wiksells boktr.) [Google Scholar]
  104. Witt, C. A., Charisi, M., Taylor, S. R., & Burke-Spolaor, S. 2022, ApJ, 936, 89 [NASA ADS] [CrossRef] [Google Scholar]
  105. Wu, Q., Scialpi, M., Liao, S., Mannucci, F., & Qi, Z. 2024, A&A, 692, A154 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  106. Xu, H., Chen, S., Guo, Y., et al. 2023, Res. Astron. Astrophys., 23, 075024 [CrossRef] [Google Scholar]
  107. Yu, W., Richards, G. T., Vogeley, M. S., Moreno, J., & Graham, M. J. 2022, ApJ, 936, 132 [NASA ADS] [CrossRef] [Google Scholar]
  108. Zhang, Y.-W., Huang, Y., Bai, J.-M., et al. 2021, AJ, 162, 276 [NASA ADS] [CrossRef] [Google Scholar]
  109. Zhu, X.-J., & Thrane, E. 2020, ApJ, 900, 117 [NASA ADS] [CrossRef] [Google Scholar]
  110. Zu, Y., Kochanek, C. S., Kozłowski, S., & Udalski, A. 2013, ApJ, 765, 106 [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.