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Detecting anomalous quartic gauge couplings using the isolation forest machine learning algorithm

Published 4 Mar 2021 in hep-ph | (2103.03151v3)

Abstract: The search of new physics~(NP) beyond the Standard Model is one of the most important tasks of high energy physics. A common characteristic of the NP signals is that they are usually few and kinematically different. We use a model independent strategy to study the phenomenology of NP by directly picking out and studying the kinematically unusual events. For this purpose, the isolation forest~(IF) algorithm is applied, which is found to be efficient in identifying the signal events of the anomalous quartic gauge couplings~(aQGCs). The IF algorithm can also be used to constraint the coefficients of aQGCs. As a machine learning algorithm, the IF algorithm shows a good prospect in the future studies of NP.

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References (84)
  1. J. Ellis, Phil. Trans. Roy. Soc. Lond. A 370, 818 (2012).
  2. O. Cremonesi, (2010), 1002.1437.
  3. (2013), 1309.7338.
  4. Muon g-2 Collaboration, G. W. Bennett et al., Phys. Rev. D 73, 072003 (2006).
  5. JHEP 06, 092 (2016), 1510.04239.
  6. LHCb, R. Aaij et al., Phys. Rev. Lett. 113, 151601 (2014), 1406.6482.
  7. Belle, M. Huschle et al., Phys. Rev. D 92, 072014 (2015), 1507.03233.
  8. S. Weinberg, Phys. Rev. Lett. 43, 1566 (1979).
  9. JHEP 10, 085 (2010), 1008.4884.
  10. S. Willenbrock and C. Zhang, Ann. Rev. Nucl. Part. Sci. 64, 83 (2014), 1401.0470.
  11. E. Masso, JHEP 10, 128 (2014), 1406.6376.
  12. C. Anders et al., Rev. Phys. 3, 44 (2018), 1801.04203.
  13. JHEP 08, 016 (2017), 1512.03433, [Erratum: JHEP 09, 019 (2019)].
  14. Phys. Rev. D 74, 073005 (2006), hep-ph/0606118.
  15. Phys. Rev. D 93, 093013 (2016), 1604.03555.
  16. C. Zhang and S.-Y. Zhou, Phys. Rev. D 100, 095003 (2019), 1808.00010.
  17. JHEP 06, 137 (2019), 1902.08977.
  18. Chin. Phys. C 44, 123105 (2020), 2002.03326.
  19. (2021), 2107.01123.
  20. Nucl. Phys. B 961, 115222 (2020), 1912.10686.
  21. M. Born and L. Infeld, Proc. Roy. Soc. Lond. A 144, 425 (1934).
  22. J. Ellis and S.-F. Ge, Phys. Rev. Lett. 121, 041801 (2018), 1802.02416.
  23. D. Espriu and F. Mescia, Phys. Rev. D 90, 015035 (2014), 1403.7386.
  24. JHEP 07, 149 (2014), 1404.2866.
  25. S. Fichet and G. von Gersdorff, JHEP 03, 102 (2014), 1311.6815.
  26. T. Lee, Phys. Rev. D 8, 1226 (1973).
  27. Mod. Phys. Lett. A 31, 1650012 (2015), 1508.00314.
  28. Phys. Rev. D 44, 2118 (1991).
  29. Eur. Phys. J. C 79, 983 (2019), 1905.00627.
  30. K. Mimasu and V. Sanz, JHEP 06, 173 (2015), 1409.4792.
  31. Phys. Rev. D 100, 015020 (2019), 1904.10657.
  32. C. Zhang and S.-Y. Zhou, Phys. Rev. Lett. 125, 201601 (2020), 2005.03047.
  33. C. Degrande, JHEP 02, 101 (2014), 1308.6323.
  34. Chin. Phys. C 44, 063106 (2020), 1902.06631.
  35. (2020), 2008.04298.
  36. A. Senol et al., Nucl. Phys. B 935, 365 (2018), 1805.03475.
  37. (2021), 2102.03623.
  38. Eur. Phys. J. C 78, 759 (2018), 1807.02707.
  39. Nucl. Phys. B 433, 41 (1995), hep-ph/9405214.
  40. G. Kasieczka et al., (2021), 2101.08320.
  41. A. Radovic et al., Nature 560, 41 (2018).
  42. Nature Commun. 5, 4308 (2014), 1402.4735.
  43. Nucl. Phys. B 943, 114613 (2019), 1708.06615.
  44. JHEP 08, 055 (2019), 1807.09088.
  45. Phys. Rev. Lett. 124, 010508 (2020).
  46. Phys. Lett. B 802, 135198 (2020), 1901.05627.
  47. A. De Simone and T. Jacques, Eur. Phys. J. C 79, 289 (2019), 1807.06038.
  48. Int. J. Mod. Phys. A 35, 2050131 (2020).
  49. Phys. Rev. Accel. Beams 23, 102805 (2020).
  50. R. T. D’Agnolo and A. Wulzer, Phys. Rev. D 99, 015014 (2019), 1806.02350.
  51. Phys. Rev. D 101, 075021 (2020), 1808.08992.
  52. JHEP 05, 036 (2019), 1811.10276.
  53. Eur. Phys. J. C 81, 27 (2021), 2006.05432.
  54. M. van Beekveld et al., (2020), 2010.07940.
  55. M. Kuusela et al., J. Phys. Conf. Ser. 368, 012032 (2012), 1112.3329.
  56. L. Ruff et al., Deep one-class classification, in Proceedings of the 35th International Conference on Machine Learning, edited by J. Dy and A. Krause, , Proceedings of Machine Learning Research Vol. 80, pp. 4393–4402, Stockholmsmässan, Stockholm Sweden, 2018, PMLR.
  57. Isolation forest, in 2008 Eighth IEEE International Conference on Data Mining, pp. 413–422, 2008.
  58. Knowledge-Based Systems 195, 105659 (2020).
  59. Rev. Mod. Phys. 89, 035008 (2017), 1610.07572.
  60. JHEP 11, 010 (2008), 0806.4145.
  61. Phys. Rev. D 91, 096007 (2015), 1408.6207.
  62. S. Tizchang and S. M. Etesami, JHEP 07, 191 (2020), 2004.12203.
  63. ATLAS, G. Aad et al., Phys. Rev. Lett. 113, 141803 (2014), 1405.6241.
  64. ATLAS, M. Aaboud et al., JHEP 07, 107 (2017), 1705.01966.
  65. CMS, V. Khachatryan et al., Phys. Lett. B 770, 380 (2017), 1702.03025.
  66. CMS, V. Khachatryan et al., JHEP 06, 106 (2017), 1612.09256.
  67. CMS, A. M. Sirunyan et al., Phys. Lett. B 774, 682 (2017), 1708.02812.
  68. CMS, A. M. Sirunyan et al., Phys. Lett. B 789, 19 (2019), 1806.11073.
  69. ATLAS, M. Aaboud et al., Phys. Lett. B 793, 469 (2019), 1812.09740.
  70. CMS, A. M. Sirunyan et al., Phys. Lett. B 795, 281 (2019), 1901.04060.
  71. CMS, A. M. Sirunyan et al., Phys. Rev. Lett. 120, 081801 (2018), 1709.05822.
  72. CMS, A. M. Sirunyan et al., Phys. Lett. B 798, 134985 (2019), 1905.07445.
  73. CMS, V. Khachatryan et al., JHEP 08, 119 (2016), 1604.04464.
  74. M. Rauch, (2016), 1610.08420.
  75. CMS, A. M. Sirunyan et al., Phys. Lett. B 811, 135988 (2020), 2008.10521.
  76. CMS, A. M. Sirunyan et al., JHEP 06, 076 (2020), 2002.09902.
  77. ATLAS, G. Aad et al., Eur. Phys. J. C 79, 970 (2019), 1907.05120.
  78. J. Alwall et al., JHEP 07, 079 (2014), 1405.0301.
  79. N. D. Christensen and C. Duhr, Comput. Phys. Commun. 180, 1614 (2009), 0806.4194.
  80. T. Sjöstrand et al., Comput. Phys. Commun. 191, 159 (2015), 1410.3012.
  81. DELPHES 3, J. de Favereau et al., JHEP 02, 057 (2014), 1307.6346.
  82. NNPDF, R. D. Ball et al., Nucl. Phys. B 877, 290 (2013), 1308.0598.
  83. Comput. Phys. Commun. 294, 108957 (2024), 2305.00964.
  84. CMS, A. M. Sirunyan et al., JHEP 03, 051 (2020), 1911.04968.
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