Karlsruhe 2024 – scientific programme

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T: Fachverband Teilchenphysik

T 99: Di-Higgs 3 (bbWW)

T 99.4: Talk

Thursday, March 7, 2024, 16:45–17:00, Geb. 30.41: HS 1

Employing Matrix Elements with Neural Networks to Search for Higgs Self-coupling — •Christoph Ames, Otmar Biebel, Lars Linden, Celine Stauch, Edis Hrustanbegovic, Stefanie Götz, Lukas Von Stumpfeldt, and Youn Jun Cho — Ludwigs-Maximilians-Universität, München

The Higgs boson was discovered in 2012 as predicted by the Standard Model (SM); however not all of its predicted couplings have been measured. One such coupling is the Higgs self-coupling, in which a Higgs boson decays into two further Higgs bosons. By integrating over all possible initial states and by using the details of the end state, the matrix element method evaluates the weight (likelihood) of an event for the specific production cross section. In this work, machine learning is combined with the matrix element method to search for HH → bbW⁺W⁻ using simulated data. A neural network is trained to calculate the matrix element weight of an event and to use this to determine whether the event contains a signal or a background decay.

Keywords: Higgs boson; machine learning; matrix element method