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@MASTERSTHESIS{Bliewert:626028,
      author       = {Bliewert, Bryan},
      othercontributors = {List, Jenny and Heinrich, Lukas and Kasieczka, Gregor},
      title        = {{I}mplementation of the {M}atrix {E}lement {M}ethod and a
                      {J}et {C}lustering {A}lgorithm with {M}achine {L}earning at
                      {F}uture {H}iggs {F}actories},
      school       = {Technische Universität München},
      type         = {Masterarbeit},
      reportid     = {PUBDB-2025-01265},
      pages        = {104},
      year         = {2025},
      note         = {Masterarbeit, Technische Universität München, 2024},
      abstract     = {A top priority of future collider programs is to measure
                      the value of the Higgs self-coupling λ. Through double
                      Higgs production (ZHH), this is possible by direct
                      measurement at lepton col-liders. However, both
                      reconstruction and analysis face challenges due to the high
                      number of jets, misclustering effects in the jet clustering
                      procedure and separation of the signal from irreducible
                      backgrounds (ZZH). In this thesis, approaches and solutions
                      for both are presented. First, a jet clustering algorithm
                      based on Graph Neural Networks and Spectral Clustering is
                      presented and shown to produce nearly identical as the
                      benchmark (Durham algorithm). Then, for the analysis,
                      multiple multivariate methods are explored, such as
                      likelihood-ratio testing with the Matrix-Element-Method and
                      direct classification using machine learning models
                      including transformers and Deep Sets. The best results give
                      a final average precision and AUROC for separating ZHH and
                      ZZH events correctly of $67\%$ and 0.78, respectively.},
      cin          = {FTX},
      cid          = {I:(DE-H253)FTX-20210408},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611)},
      pid          = {G:(DE-HGF)POF4-611},
      experiment   = {EXP:(DE-H253)ILC(machine)-20150101},
      typ          = {PUB:(DE-HGF)19},
      doi          = {10.3204/PUBDB-2025-01265},
      url          = {https://bib-pubdb1.desy.de/record/626028},
}