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Home All issues Volume 710 (June 2026) A&A, 710 (2026) A125 References
Open Access
Issue
A&A
Volume 710, June 2026
Article Number A125
Number of page(s) 14
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202558655
Published online 05 June 2026
  1. Abbott, B. P., Abbott, R., Abbott, T., et al. 2017, ApJ, 848, L13 [CrossRef] [Google Scholar]
  2. Abdo, A. A., Ackermann, M., Ajello, M., et al. 2009a, Nature, 462, 331 [NASA ADS] [CrossRef] [Google Scholar]
  3. Abdo, A. A., Ackermann, M., Arimoto, M., et al. 2009b, Science, 323, 1688 [NASA ADS] [CrossRef] [Google Scholar]
  4. Abraham, S., Mukund, N., Vibhute, A., et al. 2021, MNRAS, 504, 3084 [Google Scholar]
  5. Acciari, V. A., Ansoldi, S., Antonelli, L. A., et al. 2020, Phys. Rev. Lett., 125, 021301 [Google Scholar]
  6. Alajlan, N. 2011, J. King Saud University-Computer Inform. Sci., 23, 7 [Google Scholar]
  7. Berger, E. 2014, ARA&A, 52, 43 [Google Scholar]
  8. Bernardini, M. G., Ghirlanda, G., Campana, S., et al. 2015, MNRAS, 446, 1129 [Google Scholar]
  9. Bhat, P. N., Briggs, M. S., Connaughton, V., et al. 2012, ApJ, 744, 141 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bošnjak, Ž., & Daigne, F. 2014, A&A, 568, A45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Burgess, J. M., Cameron, E., Svinkin, D., & Greiner, J. 2021, A&A, 654, A26 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Chen, L., Lou, Y.-Q., Wu, M., et al. 2005, ApJ, 619, 983 [Google Scholar]
  13. Choi, W., Cho, J., Lee, S., & Jung, Y. 2020, IEEE access, 8, 222841 [Google Scholar]
  14. Dermer, C. D. 2004, ApJ, 614, 284 [NASA ADS] [CrossRef] [Google Scholar]
  15. Folgado, D., Barandas, M., Matias, R., et al. 2018, Pattern Recog., 81, 268 [Google Scholar]
  16. Fong, W.-f., Berger, E., & Fox, D. B. 2013, ApJ, 776, 18 [NASA ADS] [CrossRef] [Google Scholar]
  17. Giao, B. C., & Anh, D. T. 2016, Vietnam J. Comp. Sci., 3, 181 [Google Scholar]
  18. Golkhou, V. Z., Butler, N. R., & Littlejohns, O. M. 2015, ApJ, 811, 93 [NASA ADS] [CrossRef] [Google Scholar]
  19. Gompertz, B. P., Ravasio, M. E., Nicholl, M., et al. 2023, Nat. Astron., 7, 67 [Google Scholar]
  20. Guan, X., Huang, C., Liu, G., Meng, X., & Liu, Q. 2016, Remote Sensing, 8, 19 [Google Scholar]
  21. Keogh, E., & Ratanamahatana, A. 2004, in 3rd Workshop on Mining Temporal and Sequential Data, in conjunction with 10th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (KDD-2004), Seattle, WA, 1, 1 [Google Scholar]
  22. Kostelecký, V. A., & Samuel, S. 1989, Phys. Rev. D, 39, 683 [CrossRef] [PubMed] [Google Scholar]
  23. Lahreche, A., & Boucheham, B. 2021, Expert Systems with Applications, 168, 114374 [Google Scholar]
  24. Lan, L., Piórkowska-Kurpas, A., Wen, X., et al. 2022, ApJ, 937, 62 [Google Scholar]
  25. Lee, H.-S. 2019, J. Exercise Rehabilitation, 15, 526 [Google Scholar]
  26. Leibler, C. N., & Berger, E. 2010, ApJ, 725, 1202 [NASA ADS] [CrossRef] [Google Scholar]
  27. Li, T.-P., Qu, J.-L., Feng, H., et al. 2004, Chinese J. Astron. Astrophys., 4, 583 [Google Scholar]
  28. Lu, R.-J., Liang, Y.-F., Lin, D.-B., et al. 2018, ApJ, 865, 153 [NASA ADS] [CrossRef] [Google Scholar]
  29. MacLachlan, G. A., Shenoy, A., Sonbas, E., et al. 2013, MNRAS, 432, 857 [NASA ADS] [CrossRef] [Google Scholar]
  30. McBreen, S., Foley, S., Watson, D., et al. 2008, ApJ, 677, L85 [NASA ADS] [CrossRef] [Google Scholar]
  31. Meegan, C., Lichti, G., Bhat, P. N., et al. 2009, ApJ, 702, 791 [Google Scholar]
  32. Mei, A., Banerjee, B., Oganesyan, G., et al. 2022, Nature, 612, 236 [NASA ADS] [CrossRef] [Google Scholar]
  33. Morel, M., Achard, C., Kulpa, R., & Dubuisson, S. 2018, Pattern Recog., 74, 77 [Google Scholar]
  34. Niennattrakul, V., & Ratanamahatana, C. A. 2009, arXiv e-prints [arXiv:0903.0041] [Google Scholar]
  35. Norris, J. P., & Bonnell, J. T. 2006, ApJ, 643, 266 [NASA ADS] [CrossRef] [Google Scholar]
  36. Norris, J. P., Nemiroff, R. J., Bonnell, J. T., et al. 1996, ApJ, 459, 393 [NASA ADS] [CrossRef] [Google Scholar]
  37. Norris, J., Marani, G., & Bonnell, J. 2000, ApJ, 534, 248 [NASA ADS] [CrossRef] [Google Scholar]
  38. Norris, J. P., Bonnell, J. T., Kazanas, D., et al. 2005, ApJ, 627, 324 [NASA ADS] [CrossRef] [Google Scholar]
  39. Ratanamahatana, C. A., & Keogh, E. 2004, in Proceedings of the 2004 SIAM international conference on data mining, SIAM, 11 [Google Scholar]
  40. Richter, C., & GuÐnason, J. 2023, in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1 [Google Scholar]
  41. Sakoe, H., & Chiba, S. 2003, IEEE Trans. Acoustics Speech Signal Process., 26, 43 [Google Scholar]
  42. Sari, R., & Piran, T. 1997, arXiv e-prints [arXiv:astro-ph/9701002] [Google Scholar]
  43. Serra, J., & Arcos, J. L. 2012, in Case-Based Reasoning Research and Development - 20th International Conference [Google Scholar]
  44. Shao, L., Zhang, B. B., Wang, F. R., Dai, Z. G., & Liang, E. W. 2017, ApJ, 844, 126 [Google Scholar]
  45. Shen, R.-F., Song, L.-M., & Li, Z. 2005, MNRAS, 362, 59 [Google Scholar]
  46. Strle, B., Mozina, M., & Bratko, I. 2009, in Proceedings of the Workshop on Qualitative Reasoning [Google Scholar]
  47. Troja, E., Fryer, C., O’Connor, B., et al. 2022, Nature, 612, 228 [NASA ADS] [CrossRef] [Google Scholar]
  48. Uhm, Z. L., & Zhang, B. 2016, ApJ, 825, 97 [Google Scholar]
  49. Ukwatta, T., Stamatikos, M., Dhuga, K., et al. 2010, ApJ, 711, 1073 [NASA ADS] [CrossRef] [Google Scholar]
  50. Ukwatta, T., Dhuga, K., Stamatikos, M., et al. 2012a, MNRAS, 419, 614 [Google Scholar]
  51. Ukwatta, T. N., Stamatikos, M., Dhuga, K. S., et al. 2012b, ApJ, 711, 1073 [Google Scholar]
  52. Wei, J.-J., Zhang, B.-B., Shao, L., Wu, X.-F., & Mészáros, P. 2017, ApJ, 834, L13 [Google Scholar]
  53. Wen, Y., Xiao, S., Jiang, Z.-H., et al. 2026, J. High Energy Astrophys., 53, 100590 [Google Scholar]
  54. Woosley, S., & Bloom, J. 2006, ARA&A, 44, 507 [NASA ADS] [CrossRef] [Google Scholar]
  55. Xiao, S., Xiong, S., Zhang, S., et al. 2021, ApJ, 920, 43 [Google Scholar]
  56. Xiao, S., Xiong, S. L., Wang, Y., et al. 2022, ApJ, 924, L29 [Google Scholar]
  57. Xiao, S., Tuo, Y. L., Zhang, S. N., et al. 2023, MNRAS, 521, 5308 [Google Scholar]
  58. Xiao, S., Zhang, Y.-Q., Zhu, Z.-P., et al. 2024, ApJ, 970, 6 [Google Scholar]
  59. Xiong, S., Wang, C., & Huang, Y. 2023, GRB Coordinates Netw., 33406, 1 [Google Scholar]
  60. Yang, J., Chand, V., Zhang, B.-B., et al. 2020, ApJ, 899, 106 [NASA ADS] [CrossRef] [Google Scholar]
  61. Yang, J., Ai, S., Zhang, B.-B., et al. 2022, Nature, 612, 232 [NASA ADS] [CrossRef] [Google Scholar]
  62. Yu, D., Yu, X., Hu, Q., Liu, J., & Wu, A. 2011, Inf. Sci., 181, 2787 [Google Scholar]
  63. Zhang, B.-B., Zhang, B., & Castro-Tirado, A. J. 2016, ApJ, 820, L32 [Google Scholar]
  64. Zhang, Z., Tavenard, R., Bailly, A., et al. 2017, Inf. Sci., 393, 91 [Google Scholar]
  65. Zhao, J., & Itti, L. 2018, Pattern Recog., 74, 171 [Google Scholar]

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